advantages and disadvantages of secondary data in research methodology

Secondary Data: Advantages, Disadvantages, Sources, Types

If you know the advantages and disadvantages of secondary data, you can make informed decisions and create future-oriented strategies.

Wherever you work – in business, marketing, research, or statistics, secondary data sources can help you optimize your current and future results.

Let’s see how

On this page:

What is secondary data? Definition, meaning, importance
Secondary data advantages and disadvantages (comparison chart)
Examples, types, and sources of secondary data.
Infographics in PDF

What is secondary data? Definition and meaning.

Secondary data is the data that have been already collected for another purpose but has some relevance to your current research needs.

In other words, it has already been collected in the past by someone else, not you. And now, you can use the data.

Secondary data is second-hand information. It is not used for the first time. That is why it is called secondary.

Typically, secondary data is found in resources like the Internet, libraries, or reports.

Web information, business reports, mass media products, encyclopedias, and government statistics are among the most popular examples of secondary data.

Advantages And Disadvantages Of Secondary Data

Secondary data advantages and disadvantages - infographic

Download the above infographic in PDF for free.

Let’s break down the infographic.

Advantages of Secondary Data:

Ease of access The secondary data sources are very easy to access. The Internet has changed the way secondary research works. Nowadays, you have so much information available just by clicking with the mouse.
Low cost or free The majority of secondary sources are absolutely free for use or at very low costs. It saves not only your money but your efforts. In comparison with primary research where you have to design and conduct a whole primary study process from the beginning, secondary research allows you to gather data without having to put any money on the table. (see more on our post: primary vs secondary data )
Time-saving As the above advantage suggests, you can perform secondary research in no time. Sometimes it is a matter of a few Google searches to find a source of data.
Allow you to generate new insights from previous analysis Reanalyzing old data can bring unexpected new understandings and points of view or even new relevant conclusions.
Longitudinal analysis Secondary data allows you to perform a longitudinal analysis which means the studies are performed spanning over a large period of time. This can help you to determine different trends. In addition, you can find secondary data from many years back up to a couple of hours ago. It allows you to compare data over time.
Anyone can collect the data Secondary data research can be performed by people that aren’t familiar with the different data collection methods . Practically, anyone can collect it.
A huge amount of secondary data with a wide variety of sources It is the richest type of data available to you in a wide variety of sources and topics.

Disadvantages:

Might be not specific to your needs Secondary data is not specific to the researcher’s needs due to the fact that it was collected in the past for another reason. That is why the secondary data might be unreliable for your current needs. Secondary data sources can give you a huge amount of information, but quantity does not always mean appropriateness.
You have no control over data quality The secondary data might lack quality. The source of the information may be questionable, especially when you gather the data via the Internet. As you relying on secondary data for your data-driven decision-making , you must evaluate the reliability of the information by finding out how the information was collected and analyzed.
Biasness As the secondary data is collected by someone else than you, typically the data is biased in favor of the person who gathered it. This might not cover your requirements as a researcher or marketer.
Not timely Secondary data is collected in the past which means it might be out-of-date. This issue can be crucial in many different situations.
You are not the owner of the information Generally, secondary data is not collected specifically for your company. Instead, it is available to many companies and people either for free or for a little fee. So, this is not exactly a “ competitive advantage ” for you. Your current and potential competitors also have access to the data.

Types Of Secondary Data

There are two types of secondary data, based on the data source:

Internal sources of data : information gathered within the researcher’s company or organization (examples – a database with customer details, sales reports, marketing analysis, your emails, your social media profiles, etc).
External sources of data : the data collected outside the organization (i.e. government statistics, mass media channels, newspapers, etc.)

Also, secondary data can be 2 types depending on the research strands:

Quantitative data – data that can be expressed as a number or can be quantified. Examples – the weight and height of a person, the number of working hours, the volume of sales per month, etc. Quantitative data are easily amenable to statistical manipulation.
Qualitative data – the information that can’t be expressed as a number and can’t be measured. Qualitative data consist of words, pictures, observations, and symbols, not numbers. It is about qualities. Examples – colors of the eyes (brown, blue, green), your socioeconomic status, customer satisfaction, and etc.

Dive deeper into the topic with our posts:

Qualitative vs quantitative data (comparison chart)
40 ways to collect data for business needs

Examples And Sources Of Secondary Data

Internal Sources Of Secondary Data

Examples of internal secondary data sources - infographic

You might have loads of data in your company or organization that you aren’t using.

All types of organizations, whatever they are business or non-profit, collect information during their everyday processes. Orders are performed, costs and sales are recorded, customer inquiries about products are submitted, reports are presented, and so on.

Much of this information is of great use in your research. They can have hidden and unexpected value for you if you are able to incorporate them into your dashboards allowing data analysts with advanced BI training to spot new relationships.

Here is a list of some common and hidden sources of internal information:

1. Sales data

Sales are essential to a company’s profitability.

Examples of sales data are revenue, profitability, price, distribution channels, buyer personas, etc. This information can show you areas of strength and weakness, which will drive your future decisions.

2. Finance data

Collecting and analyzing your financial data is a way to maximize profits. Examples of financial data are overheads and production costs, cash flow reports, amounts spent to manufacture products, etc.

3. General marketing data

Marketing departments are a gold mine when it comes to secondary data sources.

Examples of marketing data are reports on customer profiles, market segmentation , level of customer satisfaction, level of brand awareness, customer engagement through content marketing, customer retention and loyalty, etc.

4. Human resource data

Human resource departments have information about the costs to recruit and train an employee, staff retention rate and churn, the productivity of an individual employee, etc.

Human resource data can help you uncover the areas where a company needs to improve its HR processes to empower staff skills, talent, and achievements.

5. Customer relationship management system (CRM software)

Businesses can also collect and analyze data within their own CRM system.

This system is a great source of secondary data such as clients’ company affiliations, regional or geographical details for customers, and etc.

The average office employee sends dozens of business emails per day and receives even more.

Emails as sources of secondary data, provide important information such as product reviews, opinions, feedback and so on.

7. Your social media profiles

Social Media profiles on networks like Facebook, Tweeter, Linkedin are a great source of information that you can analyze to learn more about, for example, how people are talking about your business and how users share and engage with your content.

Some examples of secondary data that you can collect from social profiles include: likes, shares, mentions, impressions, new followers, comments, URL clicks.

8. Your website analytics

There’s a huge amount of valuable secondary data accessible to you through your website analytics platform.

The most popular platform for insights into your website statistics is Google Analytics and Google Search Console.

Examples of data that you can gather from your website include: visitor’s location, patterns of visitor behavior, keywords used by visitors to find your site and business, visitor’s activities in the site, most popular content, etc.

External Sources Of Secondary Data

Examples of external secondary data sources - a short infographic

External data are any data generated outside the boundaries of the company or organization.

There are many advantages of using external sources of secondary data, especially online ones. They offer endless information which you can acquire efficiently and quickly.

Today, external secondary data is a foundation for creating executive decisions wherever it is in business, in medicine, science, or in statistics.

Here are some key examples of external secondary data.

1. Data.gov

Data.gov provides over free 150,000 datasets available through federal, state, and local governments. They are free, and accessible online.

Here, companies or students can find a ton of data, including information related to consumers, education, manufacturing, public safety, and much more.

2. World Bank Open Data

World Bank Open Data offer free and open access to global development data. Datasets provide population demographics and a vast number of economic indicators from across the world.

3. IMF Economic Data

The International Monetary Fund (IMF) is an organization of 189 countries.

It provides data such as international financial statistics, regional economic reports, foreign exchange rates, debt rates, commodity prices, and investments.

4. Crayon Intel Free

Crayon Intel Free is one of the best free competitor analysis tools that can help you track, analyze, and act on many things that happen outside of your business.

5. Talkwalker’s Free Social Search

Talkwalker’s Free Social Search is a real-time free social media search engine that can provide you with unlimited searches across all major social networks.

It allows you to find out what the internet is saying about you or your competitors in seconds. You can know who’s talking about you with live audience insights.

Feedly is a free news aggregator site that allows you to keep up with all the topics that matter to you. All in one place.

With Feedly, you are able to monitor easily news about your products, your competitors, important posts, content, Tweets or even YouTube videos.

7. Mailcharts

Mailcharts is a quite powerful tool for email marketers as well as for those who want to spy on the competition.

It collects emails from competing campaigns to help you develop your own. Mailhcharts has an enormous library of emails from countless brands.

8. Glassdoor

Glassdoor is one of the world’s largest and most popular job and recruiting sites. It provides a free database with millions of company reviews, CEO approval ratings, interview reviews and questions, salary reports, benefits reviews, office photos, and more.

9. Google Alerts

Google Alerts is one of the most popular free alert services that allows you to follow mentions on the internet about practically anything you want – company, brand, customers, purchasing patterns, and so on.

10. HubSpot Marketing Statistics

HubSpot offers a large and very valuable free repository of marketing data.

You could find the latest marketing statistics and trends in areas such as Organic Search, Conversion Rate Optimization (CRO), Ecomerce, Local SEO, Mobile Search, and others.

11. Crunchbase

Crunchbase is one of the best and most innovative platforms for finding business information about private and public companies.

Crunchbase data include investments and funding information, news, and industry trends, individuals in leadership positions, mergers, and etc.

For many businesses, the sources of secondary data are a key way to gather information about their customers in order to better understand and serve them.

We are living in the big data age. Knowing the advantages and disadvantages of secondary data can ensure better decision making for all management levels and types.

It is a good basis for creating new opportunities, running data-driven marketing , and improving your results and performance.

About The Author

Silvia Valcheva

Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. She has a strong passion for writing about emerging software and technologies such as big data, AI (Artificial Intelligence), IoT (Internet of Things), process automation, etc.

One Response

I am impressed with the breakdown of the secondary. Weldone and more grace!!!

Secondary Research Advantages, Limitations, and Sources

Summary: secondary research should be a prerequisite to the collection of primary data, but it rarely provides all the answers you need. a thorough evaluation of the secondary data is needed to assess its relevance and accuracy..

5 minutes to read. By author Michaela Mora on January 25, 2022 Topics: Relevant Methods & Tips , Business Strategy , Market Research

Secondary research is based on data already collected for purposes other than the specific problem you have. Secondary research is usually part of exploratory market research designs.

The connection between the specific purpose that originates the research is what differentiates secondary research from primary research. Primary research is designed to address specific problems. However, analysis of available secondary data should be a prerequisite to the collection of primary data.

Advantages of Secondary Research

Secondary data can be faster and cheaper to obtain, depending on the sources you use.

Secondary research can help to:

Answer certain research questions and test some hypotheses.
Formulate an appropriate research design (e.g., identify key variables).
Interpret data from primary research as it can provide some insights into general trends in an industry or product category.
Understand the competitive landscape.

Limitations of Secondary Research

The usefulness of secondary research tends to be limited often for two main reasons:

Lack of relevance

Secondary research rarely provides all the answers you need. The objectives and methodology used to collect the secondary data may not be appropriate for the problem at hand.

Given that it was designed to find answers to a different problem than yours, you will likely find gaps in answers to your problem. Furthermore, the data collection methods used may not provide the data type needed to support the business decisions you have to make (e.g., qualitative research methods are not appropriate for go/no-go decisions).

Lack of Accuracy

Secondary data may be incomplete and lack accuracy depending on;

The research design (exploratory, descriptive, causal, primary vs. repackaged secondary data, the analytical plan, etc.)
Sampling design and sources (target audiences, recruitment methods)
Data collection method (qualitative and quantitative techniques)
Analysis point of view (focus and omissions)
Reporting stages (preliminary, final, peer-reviewed)
Rate of change in the studied topic (slowly vs. rapidly evolving phenomenon, e.g., adoption of specific technologies).
Lack of agreement between data sources.

Criteria for Evaluating Secondary Research Data

Before taking the information at face value, you should conduct a thorough evaluation of the secondary data you find using the following criteria:

Purpose : Understanding why the data was collected and what questions it was trying to answer will tell us how relevant and useful it is since it may or may not be appropriate for your objectives.
Methodology used to collect the data : Important to understand sources of bias.
Accuracy of data: Sources of errors may include research design, sampling, data collection, analysis, and reporting.
When the data was collected : Secondary data may not be current or updated frequently enough for the purpose that you need.
Content of the data : Understanding the key variables, units of measurement, categories used and analyzed relationships may reveal how useful and relevant it is for your purposes.
Source reputation : In the era of purposeful misinformation on the Internet, it is important to check the expertise, credibility, reputation, and trustworthiness of the data source.

Secondary Research Data Sources

Compared to primary research, the collection of secondary data can be faster and cheaper to obtain, depending on the sources you use.

Secondary data can come from internal or external sources.

Internal sources of secondary data include ready-to-use data or data that requires further processing available in internal management support systems your company may be using (e.g., invoices, sales transactions, Google Analytics for your website, etc.).

Prior primary qualitative and quantitative research conducted by the company are also common sources of secondary data. They often generate more questions and help formulate new primary research needed.

However, if there are no internal data collection systems yet or prior research, you probably won’t have much usable secondary data at your disposal.

External sources of secondary data include:

Published materials
External databases
Syndicated services.

Published Materials

Published materials can be classified as:

General business sources: Guides, directories, indexes, and statistical data.
Government sources: Census data and other government publications.

External Databases

In many industries across a variety of topics, there are private and public databases that can bed accessed online or by downloading data for free, a fixed fee, or a subscription.

These databases can include bibliographic, numeric, full-text, directory, and special-purpose databases. Some public institutions make data collected through various methods, including surveys, available for others to analyze.

Syndicated Services

These services are offered by companies that collect and sell pools of data that have a commercial value and meet shared needs by a number of clients, even if the data is not collected for specific purposes those clients may have.

Syndicated services can be classified based on specific units of measurements (e.g., consumers, households, organizations, etc.).

The data collection methods for these data may include:

Surveys (Psychographic and Lifestyle, advertising evaluations, general topics)
Household panels (Purchase and media use)
Electronic scanner services (volume tracking data, scanner panels, scanner panels with Cable TV)
Audits (retailers, wholesalers)
Direct inquiries to institutions
Clipping services tracking PR for institutions
Corporate reports

You can spend hours doing research on Google in search of external sources, but this is likely to yield limited insights. Books, articles journals, reports, blogs posts, and videos you may find online are usually analyses and summaries of data from a particular perspective. They may be useful and give you an indication of the type of data used, but they are not the actual data. Whenever possible, you should look at the actual raw data used to draw your own conclusion on its value for your research objectives. You should check professionally gathered secondary research.

Here are some external secondary data sources often used in market research that you may find useful as starting points in your research. Some are free, while others require payment.

Pew Research Center : Reports about the issues, attitudes, and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis, and other empirical social science research.
Data.Census.gov : Data dissemination platform to access demographic and economic data from the U.S. Census Bureau.
Data.gov : The US. government’s open data source with almost 200,00 datasets ranges in topics from health, agriculture, climate, ecosystems, public safety, finance, energy, manufacturing, education, and business.
Google Scholar : A web search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines.
Google Public Data Explorer : Makes large, public-interest datasets easy to explore, visualize and communicate.
Google News Archive : Allows users to search historical newspapers and retrieve scanned images of their pages.
Mckinsey & Company : Articles based on analyses of various industries.
Statista : Business data platform with data across 170+ industries and 150+ countries.
Claritas : Syndicated reports on various market segments.
Mintel : Consumer reports combining exclusive consumer research with other market data and expert analysis.
MarketResearch.com : Data aggregator with over 350 publishers covering every sector of the economy as well as emerging industries.
Packaged Facts : Reports based on market research on consumer goods and services industries.
Dun & Bradstreet : Company directory with business information.

What Is Market Research?
Step by Step Guide to the Market Research Process
How to Leverage UX and Market Research To Understand Your Customers
Why Your Business Needs Discovery Research
Your Market Research Plan to Succeed As a Startup
Top Reason Why Businesses Fail & What To Do About It
What To Value In A Market Research Vendor
Don’t Let The Budget Dictate Your Market Research Approach
How To Use Research To Find High-Order Brand Benefits
How To Prioritize What To Research
Don’t Just Trust Your Gut — Do Research
Understanding the Pros and Cons of Mixed-Mode Research

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Secondary Data: sources, advantages and disadvantages.

In book: SAGE Encyclopedia of Communication Research Methods (pp.4:1577-1579)
Publisher: SAGE Publications, Inc
Editors: Dr. Mike Allen

University of Warsaw

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Home » Secondary Data – Types, Methods and Examples

Secondary Data – Types, Methods and Examples

Table of Contents

Secondary Data

Definition:

Secondary data refers to information that has been collected, processed, and published by someone else, rather than the researcher gathering the data firsthand. This can include data from sources such as government publications, academic journals, market research reports, and other existing datasets.

Secondary Data Types

Types of secondary data are as follows:

Published data: Published data refers to data that has been published in books, magazines, newspapers, and other print media. Examples include statistical reports, market research reports, and scholarly articles.
Government data: Government data refers to data collected by government agencies and departments. This can include data on demographics, economic trends, crime rates, and health statistics.
Commercial data: Commercial data is data collected by businesses for their own purposes. This can include sales data, customer feedback, and market research data.
Academic data: Academic data refers to data collected by researchers for academic purposes. This can include data from experiments, surveys, and observational studies.
Online data: Online data refers to data that is available on the internet. This can include social media posts, website analytics, and online customer reviews.
Organizational data: Organizational data is data collected by businesses or organizations for their own purposes. This can include data on employee performance, financial records, and customer satisfaction.
Historical data : Historical data refers to data that was collected in the past and is still available for research purposes. This can include census data, historical documents, and archival records.
International data: International data refers to data collected from other countries for research purposes. This can include data on international trade, health statistics, and demographic trends.
Public data : Public data refers to data that is available to the general public. This can include data from government agencies, non-profit organizations, and other sources.
Private data: Private data refers to data that is not available to the general public. This can include confidential business data, personal medical records, and financial data.
Big data: Big data refers to large, complex datasets that are difficult to manage and analyze using traditional data processing methods. This can include social media data, sensor data, and other types of data generated by digital devices.

Secondary Data Collection Methods

Secondary Data Collection Methods are as follows:

Published sources: Researchers can gather secondary data from published sources such as books, journals, reports, and newspapers. These sources often provide comprehensive information on a variety of topics.
Online sources: With the growth of the internet, researchers can now access a vast amount of secondary data online. This includes websites, databases, and online archives.
Government sources : Government agencies often collect and publish a wide range of secondary data on topics such as demographics, crime rates, and health statistics. Researchers can obtain this data through government websites, publications, or data portals.
Commercial sources: Businesses often collect and analyze data for marketing research or customer profiling. Researchers can obtain this data through commercial data providers or by purchasing market research reports.
Academic sources: Researchers can also obtain secondary data from academic sources such as published research studies, academic journals, and dissertations.
Personal contacts: Researchers can also obtain secondary data from personal contacts, such as experts in a particular field or individuals with specialized knowledge.

Secondary Data Formats

Secondary data can come in various formats depending on the source from which it is obtained. Here are some common formats of secondary data:

Numeric Data: Numeric data is often in the form of statistics and numerical figures that have been compiled and reported by organizations such as government agencies, research institutions, and commercial enterprises. This can include data such as population figures, GDP, sales figures, and market share.
Textual Data: Textual data is often in the form of written documents, such as reports, articles, and books. This can include qualitative data such as descriptions, opinions, and narratives.
Audiovisual Data : Audiovisual data is often in the form of recordings, videos, and photographs. This can include data such as interviews, focus group discussions, and other types of qualitative data.
Geospatial Data: Geospatial data is often in the form of maps, satellite images, and geographic information systems (GIS) data. This can include data such as demographic information, land use patterns, and transportation networks.
Transactional Data : Transactional data is often in the form of digital records of financial and business transactions. This can include data such as purchase histories, customer behavior, and financial transactions.
Social Media Data: Social media data is often in the form of user-generated content from social media platforms such as Facebook, Twitter, and Instagram. This can include data such as user demographics, content trends, and sentiment analysis.

Secondary Data Analysis Methods

Secondary data analysis involves the use of pre-existing data for research purposes. Here are some common methods of secondary data analysis:

Descriptive Analysis: This method involves describing the characteristics of a dataset, such as the mean, standard deviation, and range of the data. Descriptive analysis can be used to summarize data and provide an overview of trends.
Inferential Analysis: This method involves making inferences and drawing conclusions about a population based on a sample of data. Inferential analysis can be used to test hypotheses and determine the statistical significance of relationships between variables.
Content Analysis: This method involves analyzing textual or visual data to identify patterns and themes. Content analysis can be used to study the content of documents, media coverage, and social media posts.
Time-Series Analysis : This method involves analyzing data over time to identify trends and patterns. Time-series analysis can be used to study economic trends, climate change, and other phenomena that change over time.
Spatial Analysis : This method involves analyzing data in relation to geographic location. Spatial analysis can be used to study patterns of disease spread, land use patterns, and the effects of environmental factors on health outcomes.
Meta-Analysis: This method involves combining data from multiple studies to draw conclusions about a particular phenomenon. Meta-analysis can be used to synthesize the results of previous research and provide a more comprehensive understanding of a particular topic.

Secondary Data Gathering Guide

Here are some steps to follow when gathering secondary data:

Define your research question: Start by defining your research question and identifying the specific information you need to answer it. This will help you identify the type of secondary data you need and where to find it.
Identify relevant sources: Identify potential sources of secondary data, including published sources, online databases, government sources, and commercial data providers. Consider the reliability and validity of each source.
Evaluate the quality of the data: Evaluate the quality and reliability of the data you plan to use. Consider the data collection methods, sample size, and potential biases. Make sure the data is relevant to your research question and is suitable for the type of analysis you plan to conduct.
Collect the data: Collect the relevant data from the identified sources. Use a consistent method to record and organize the data to make analysis easier.
Validate the data: Validate the data to ensure that it is accurate and reliable. Check for inconsistencies, missing data, and errors. Address any issues before analyzing the data.
Analyze the data: Analyze the data using appropriate statistical and analytical methods. Use descriptive and inferential statistics to summarize and draw conclusions from the data.
Interpret the results: Interpret the results of your analysis and draw conclusions based on the data. Make sure your conclusions are supported by the data and are relevant to your research question.
Communicate the findings : Communicate your findings clearly and concisely. Use appropriate visual aids such as graphs and charts to help explain your results.

Examples of Secondary Data

Here are some examples of secondary data from different fields:

Healthcare : Hospital records, medical journals, clinical trial data, and disease registries are examples of secondary data sources in healthcare. These sources can provide researchers with information on patient demographics, disease prevalence, and treatment outcomes.
Marketing : Market research reports, customer surveys, and sales data are examples of secondary data sources in marketing. These sources can provide marketers with information on consumer preferences, market trends, and competitor activity.
Education : Student test scores, graduation rates, and enrollment statistics are examples of secondary data sources in education. These sources can provide researchers with information on student achievement, teacher effectiveness, and educational disparities.
Finance : Stock market data, financial statements, and credit reports are examples of secondary data sources in finance. These sources can provide investors with information on market trends, company performance, and creditworthiness.
Social Science : Government statistics, census data, and survey data are examples of secondary data sources in social science. These sources can provide researchers with information on population demographics, social trends, and political attitudes.
Environmental Science : Climate data, remote sensing data, and ecological monitoring data are examples of secondary data sources in environmental science. These sources can provide researchers with information on weather patterns, land use, and biodiversity.

Purpose of Secondary Data

The purpose of secondary data is to provide researchers with information that has already been collected by others for other purposes. Secondary data can be used to support research questions, test hypotheses, and answer research objectives. Some of the key purposes of secondary data are:

To gain a better understanding of the research topic : Secondary data can be used to provide context and background information on a research topic. This can help researchers understand the historical and social context of their research and gain insights into relevant variables and relationships.
To save time and resources: Collecting new primary data can be time-consuming and expensive. Using existing secondary data sources can save researchers time and resources by providing access to pre-existing data that has already been collected and organized.
To provide comparative data : Secondary data can be used to compare and contrast findings across different studies or datasets. This can help researchers identify trends, patterns, and relationships that may not have been apparent from individual studies.
To support triangulation: Triangulation is the process of using multiple sources of data to confirm or refute research findings. Secondary data can be used to support triangulation by providing additional sources of data to support or refute primary research findings.
To supplement primary data : Secondary data can be used to supplement primary data by providing additional information or insights that were not captured by the primary research. This can help researchers gain a more complete understanding of the research topic and draw more robust conclusions.

When to use Secondary Data

Secondary data can be useful in a variety of research contexts, and there are several situations in which it may be appropriate to use secondary data. Some common situations in which secondary data may be used include:

When primary data collection is not feasible : Collecting primary data can be time-consuming and expensive, and in some cases, it may not be feasible to collect primary data. In these situations, secondary data can provide valuable insights and information.
When exploring a new research area : Secondary data can be a useful starting point for researchers who are exploring a new research area. Secondary data can provide context and background information on a research topic, and can help researchers identify key variables and relationships to explore further.
When comparing and contrasting research findings: Secondary data can be used to compare and contrast findings across different studies or datasets. This can help researchers identify trends, patterns, and relationships that may not have been apparent from individual studies.
When triangulating research findings: Triangulation is the process of using multiple sources of data to confirm or refute research findings. Secondary data can be used to support triangulation by providing additional sources of data to support or refute primary research findings.
When validating research findings : Secondary data can be used to validate primary research findings by providing additional sources of data that support or refute the primary findings.

Characteristics of Secondary Data

Secondary data have several characteristics that distinguish them from primary data. Here are some of the key characteristics of secondary data:

Non-reactive: Secondary data are non-reactive, meaning that they are not collected for the specific purpose of the research study. This means that the researcher has no control over the data collection process, and cannot influence how the data were collected.
Time-saving: Secondary data are pre-existing, meaning that they have already been collected and organized by someone else. This can save the researcher time and resources, as they do not need to collect the data themselves.
Wide-ranging : Secondary data sources can provide a wide range of information on a variety of topics. This can be useful for researchers who are exploring a new research area or seeking to compare and contrast research findings.
Less expensive: Secondary data are generally less expensive than primary data, as they do not require the researcher to incur the costs associated with data collection.
Potential for bias : Secondary data may be subject to biases that were present in the original data collection process. For example, data may have been collected using a biased sampling method or the data may be incomplete or inaccurate.
Lack of control: The researcher has no control over the data collection process and cannot ensure that the data were collected using appropriate methods or measures.
Requires careful evaluation : Secondary data sources must be evaluated carefully to ensure that they are appropriate for the research question and analysis. This includes assessing the quality, reliability, and validity of the data sources.

Advantages of Secondary Data

There are several advantages to using secondary data in research, including:

Time-saving : Collecting primary data can be time-consuming and expensive. Secondary data can be accessed quickly and easily, which can save researchers time and resources.
Cost-effective: Secondary data are generally less expensive than primary data, as they do not require the researcher to incur the costs associated with data collection.
Large sample size : Secondary data sources often have larger sample sizes than primary data sources, which can increase the statistical power of the research.
Access to historical data : Secondary data sources can provide access to historical data, which can be useful for researchers who are studying trends over time.
No ethical concerns: Secondary data are already in existence, so there are no ethical concerns related to collecting data from human subjects.
May be more objective : Secondary data may be more objective than primary data, as the data were not collected for the specific purpose of the research study.

Limitations of Secondary Data

While there are many advantages to using secondary data in research, there are also some limitations that should be considered. Some of the main limitations of secondary data include:

Lack of control over data quality : Researchers do not have control over the data collection process, which means they cannot ensure the accuracy or completeness of the data.
Limited availability: Secondary data may not be available for the specific research question or study design.
Lack of information on sampling and data collection methods: Researchers may not have access to information on the sampling and data collection methods used to gather the secondary data. This can make it difficult to evaluate the quality of the data.
Data may not be up-to-date: Secondary data may not be up-to-date or relevant to the current research question.
Data may be incomplete or inaccurate : Secondary data may be incomplete or inaccurate due to missing or incorrect data points, data entry errors, or other factors.
Biases in data collection: The data may have been collected using biased sampling or data collection methods, which can limit the validity of the data.
Lack of control over variables: Researchers have limited control over the variables that were measured in the original data collection process, which can limit the ability to draw conclusions about causality.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

Research Data – Types Methods and Examples

Information in Research – Types and Examples

Qualitative Data – Types, Methods and Examples

Quantitative Data – Types, Methods and Examples

Primary Data – Types, Methods and Examples

Secondary Data: Analysis, Benefits, Importance, and Sources

Competently using data has proven to be the path towards success for many entities across different fields. In business, it meant competitive advantage, innovation, and profit. However, in order to achieve all these benefits, companies need to understand and take advantage of different kinds of data analysis and handling practices. One important distinction to be aware of is between primary data analysis and secondary data analysis. The importance of collecting new data is often and rightly stressed. So, let’s look closer at why it’s vital to utilize secondary data as well, and what benefits can come from analyzing secondary data.

What is secondary data?

As mentioned, when businesses collect data themselves, it’s considered primary data. So, what makes up secondary data? Simply because of the fact that it has already been collected by a primary source and is now being used by someone else (a secondary source) for their own purposes.

Likewise, primary research is when the data is collected by researchers themselves and is essentially new data. Conversely, secondary research or secondary data analysis is when analysts utilize data from previous research or outside primary sources instead of collecting data themselves.

Therefore, secondary data is any data that is already available before the research begins. Secondary data collection involves getting or buying data that has already been produced or recorded, instead of producing new data. More specifically, secondary data is information originally created and used by a primary source for a specific purpose that is then collected and analyzed by a second party.

Secondary data sources

Primary research is done with the data collected from authentic sources. This means that, for example, researchers conduct interviews or carry out field tests to get the data for the analysis.

Sources of secondary data, on the other hand, don’t need to be authentic. Any source information collected for whichever purpose can be a source for secondary data analysis. Naturally, this means that there are many such sources.

For businesses and other organizations, all these sources can be divided into internal and external. Internal sources are those that come from within the organization. For example, researchers may use existing data from accounting, customer feedback, or operational reports when doing marketing research to improve a firm’s marketing strategies. This data is still secondary as it was originally recorded for other purposes, but as it originates within the same company as the marketing research itself, it’s internal data.

All other sources, those that are outside of the organization, are external sources of secondary data. Of course, this group of sources is extensive and varies immensely. Here are some of the most common examples of such sources.

Public legal sources and government publications (including public libraries and their sources for administrative data, as well as census data)
Media (either broadcasted, printed, or otherwise released by TV, newspaper, or information from other media companies)
Literature and literature review (including releases from academic publishers , like Cambridge University Press or Sage Publications)
Industry reports and other published market or industry research
Professional data providers
International organizations

Primary data vs. secondary data

The difference between primary and secondary data is not only source type or whether they have been used before. These two types of data usually differ in their features which have important implications when choosing which type of analysis to conduct.

Data collected for primary research is raw data that can be structured according to the goals of the analysis. Secondary data usually has already been structured or processed, often more than once, thus at first, it is presented for analysis in a form that was meant to suit something else.

Qualitative data is more often used in primary research. Secondary research is more associated with quantitative data, such as administrative data or census data, often studied by social scientists. However, there are also valid qualitative data research methods that can be applied for secondary data in marketing research or other business-relevant analysis. Here are some advantages and disadvantages of secondary data analysis as compared to primary research

Advantages of secondary research

Saving time and effort.

Collecting secondary data for research is much faster and easier than primary data collection. This allows researchers to save time by going straight to the analysis process. Additionally, researchers stay focused on the research goals without having to worry about finding and utilizing primary sources, which can be a lot of work on its own.

Cost-effectiveness

Secondary research is generally the cheaper option. It is quite costly to organize focus groups, hire people to question persons of interest, or build and maintain various sensors able to record large amounts of data. Meanwhile, secondary data may cost next to nothing to get as all the data one could use is already available and often easily accessible from free institutions like public libraries. Even when such data is not enough and one has to turn to data providers or otherwise spend money to acquire secondary data, it’s still cheaper than primary data collection.

Cleaned and structured data

Secondary data has often been cleaned before using it for primary purposes. This means that the data already ascends to at least some data quality standards. There may be many quality issues with just gathered primary data. Thus researchers have to put additional resources to clean it. Additionally, secondary data is usually structured, which, as mentioned, may not suit the particular requirements of secondary research at hand, but it does bring some organization and readability, which can prove time-saving.

The large volume of data

Finally, there’s only so much primary data that researchers can collect before having to start the actual analysis. With secondary data, there’s no such limit. There is more information available in secondary sources than one could handle in a lifetime of data analysis. Thus, secondary data researchers certainly don’t have many restrictions on what sources to choose from.

Disadvantages of secondary research

Differing requirements.

The biggest among the disadvantages of secondary data research is that one can’t quite be sure that the data will suit the goals of the research exactly. Primary data analysts can gather exactly what they need. Secondary researchers, on the other hand, work with what they were able to find from what is available.

Control over the collection process

Secondary data analysts can’t be completely sure that the data was collected according to rigid standards and therefore is valid and representative. They may check the source and try to find out as much about the collection as possible, but there will always be a degree of uncertainty.

Lacking uniqueness

Primary researchers work on unique data that no one else has had before. Therefore they have a greater chance of arriving at unique insights. Secondary data analysis can be unique too, but only for as long as no one else uses the same data for the same research purposes.

disadvantages of secondary research visual

Five Metrics for evaluating and analyzing secondary data

The first step of secondary data analysis is the evaluation of data. Although, as mentioned, it’s impossible to have complete quality control over secondary data, researchers can still exercise some control. The following criteria are crucial when evaluating secondary data in order to determine their suitability for the analysis at hand.

Reliability of the source How trusty is the data source? Is it a reputable data provider or an established publisher? Researchers should also check to find out as much as possible about the circumstances of data collection .
Relevance Not all trustworthy information is relevant data for a particular analysis. Researchers must first establish clear analysis goals to determine data relevance and then check what kind of information particular data sources hold.
Overall quality Of course, analysts need to pay attention to any errors, redundancies, or other possible issues with the data they’re considering for usage. Poor data quality costs businesses between $9.7 million and $14.2 million every year.
Freshness How new is the data? When was it last updated? Outdated information may no longer answer the questions raised by the analysis goals.
Accessibility The format of the data and how it is accessed are also pivotal for data analysis. The easier it is to access data, the more efficient and reliable secondary research will be.

The importance of secondary data analysis in business

For years business heads and data analysts have been lamenting the fact that most data never get to be analyzed. For example, a few years ago, it was estimated that only about 0.5% of all data is ever analyzed and utilized.

Having this in mind, one can’t help but wonder whether it’s worth spending money on additional data production when so much existing data never gets used. Of course, primary research is often necessary, for example, when new qualitative data is required, but it is equally important not to overlook the potential of secondary data.

Especially when it comes to secondary quantitative data, the large volumes of public web data already available would suggest first going for secondary research. Thus, combining the two research methods is the surest way for businesses to benefit from data analysis.

Wrapping up

Researchers can either collect new data for analysis or get secondary data from some of the many diverse sources. Whichever path is chosen, the key to success and business benefits is, as always, attention to data quality and choosing the right method for the right goals.

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What Is Secondary Data? A Complete Guide

What is secondary data, and why is it important? Find out in this post.

Within data analytics, there are many ways of categorizing data. A common distinction, for instance, is that between qualitative and quantitative data . In addition, you might also distinguish your data based on factors like sensitivity. For example, is it publicly available or is it highly confidential?

Probably the most fundamental distinction between different types of data is their source. Namely, are they primary, secondary, or third-party data? Each of these vital data sources supports the data analytics process in its own way. In this post, we’ll focus specifically on secondary data. We’ll look at its main characteristics, provide some examples, and highlight the main pros and cons of using secondary data in your analysis.

We’ll cover the following topics:

What is secondary data?

What’s the difference between primary, secondary, and third-party data?
What are some examples of secondary data?
How to analyse secondary data
Advantages of secondary data
Disadvantages of secondary data
Wrap-up and further reading

Ready to learn all about secondary data? Then let’s go.

1. What is secondary data?

Secondary data (also known as second-party data) refers to any dataset collected by any person other than the one using it.

Secondary data sources are extremely useful. They allow researchers and data analysts to build large, high-quality databases that help solve business problems. By expanding their datasets with secondary data, analysts can enhance the quality and accuracy of their insights. Most secondary data comes from external organizations. However, secondary data also refers to that collected within an organization and then repurposed.

Secondary data has various benefits and drawbacks, which we’ll explore in detail in section four. First, though, it’s essential to contextualize secondary data by understanding its relationship to two other sources of data: primary and third-party data. We’ll look at these next.

2. What’s the difference between primary, secondary, and third-party data?

To best understand secondary data, we need to know how it relates to the other main data sources: primary and third-party data.

What is primary data?

‘Primary data’ (also known as first-party data) are those directly collected or obtained by the organization or individual that intends to use them. Primary data are always collected for a specific purpose. This could be to inform a defined goal or objective or to address a particular business problem.

For example, a real estate organization might want to analyze current housing market trends. This might involve conducting interviews, collecting facts and figures through surveys and focus groups, or capturing data via electronic forms. Focusing only on the data required to complete the task at hand ensures that primary data remain highly relevant. They’re also well-structured and of high quality.

As explained, ‘secondary data’ describes those collected for a purpose other than the task at hand. Secondary data can come from within an organization but more commonly originate from an external source. If it helps to make the distinction, secondary data is essentially just another organization’s primary data.

Secondary data sources are so numerous that they’ve started playing an increasingly vital role in research and analytics. They are easier to source than primary data and can be repurposed to solve many different problems. While secondary data may be less relevant for a given task than primary data, they are generally still well-structured and highly reliable.

What is third-party data?

‘Third-party data’ (sometimes referred to as tertiary data) refers to data collected and aggregated from numerous discrete sources by third-party organizations. Because third-party data combine data from numerous sources and aren’t collected with a specific goal in mind, the quality can be lower.

Third-party data also tend to be largely unstructured. This means that they’re often beset by errors, duplicates, and so on, and require more processing to get them into a usable format. Nevertheless, used appropriately, third-party data are still a useful data analytics resource. You can learn more about structured vs unstructured data here .

OK, now that we’ve placed secondary data in context, let’s explore some common sources and types of secondary data.

3. What are some examples of secondary data?

External secondary data.

Before we get to examples of secondary data, we first need to understand the types of organizations that generally provide them. Frequent sources of secondary data include:

Government departments
Public sector organizations
Industry associations
Trade and industry bodies
Educational institutions
Private companies
Market research providers

While all these organizations provide secondary data, government sources are perhaps the most freely accessible. They are legally obliged to keep records when registering people, providing services, and so on. This type of secondary data is known as administrative data. It’s especially useful for creating detailed segment profiles, where analysts hone in on a particular region, trend, market, or other demographic.

Types of secondary data vary. Popular examples of secondary data include:

Tax records and social security data
Census data (the U.S. Census Bureau is oft-referenced, as well as our favorite, the U.S. Bureau of Labor Statistics )
Electoral statistics
Health records
Books, journals, or other print media
Social media monitoring, internet searches, and other online data
Sales figures or other reports from third-party companies
Libraries and electronic filing systems
App data, e.g. location data, GPS data, timestamp data, etc.

Internal secondary data

As mentioned, secondary data is not limited to that from a different organization. It can also come from within an organization itself.

Sources of internal secondary data might include:

Sales reports
Annual accounts
Quarterly sales figures
Customer relationship management systems
Emails and metadata
Website cookies

In the right context, we can define practically any type of data as secondary data. The key takeaway is that the term ‘secondary data’ doesn’t refer to any inherent quality of the data themselves, but to how they are used. Any data source (external or internal) used for a task other than that for which it was originally collected can be described as secondary data.

4. How to analyse secondary data

The process of analysing secondary data can be performed either quantitatively or qualitatively, depending on the kind of data the researcher is dealing with. The quantitative method of secondary data analysis is used on numerical data and is analyzed mathematically. The qualitative method uses words to provide in-depth information about data.

There are different stages of secondary data analysis, which involve events before, during, and after data collection. These stages include:

Statement of purpose: Before collecting secondary data, you need to know your statement of purpose. This means you should have a clear awareness of the goal of the research work and how this data will help achieve it. This will guide you to collect the right data, then choosing the best data source and method of analysis.
Research design: This is a plan on how the research activities will be carried out. It describes the kind of data to be collected, the sources of data collection, the method of data collection, tools used, and method of analysis. Once the purpose of the research has been identified, the researcher should design a research process that will guide the data analysis process.
Developing the research questions: Once you’ve identified the research purpose, an analyst should also prepare research questions to help identify secondary data. For example, if a researcher is looking to learn more about why working adults are increasingly more interested in the “gig economy” as opposed to full-time work, they may ask, “What are the main factors that influence adults decisions to engage in freelance work?” or, “Does education level have an effect on how people engage in freelance work?
Identifying secondary data: Using the research questions as a guide, researchers will then begin to identify relevant data from the sources provided. If the kind of data to be collected is qualitative, a researcher can filter out qualitative data—for example.
Evaluating secondary data: Once relevant data has been identified and collates, it will be evaluated to ensure it fulfils the criteria of the research topic. Then, it is analyzed either using the quantitative or qualitative method, depending on the type of data it is.

You can learn more about secondary data analysis in this post .

5. Advantages of secondary data

Secondary data is suitable for any number of analytics activities. The only limitation is a dataset’s format, structure, and whether or not it relates to the topic or problem at hand.

When analyzing secondary data, the process has some minor differences, mainly in the preparation phase. Otherwise, it follows much the same path as any traditional data analytics project.

More broadly, though, what are the advantages and disadvantages of using secondary data? Let’s take a look.

Advantages of using secondary data

It’s an economic use of time and resources: Because secondary data have already been collected, cleaned, and stored, this saves analysts much of the hard work that comes from collecting these data firsthand. For instance, for qualitative data, the complex tasks of deciding on appropriate research questions or how best to record the answers have already been completed. Secondary data saves data analysts and data scientists from having to start from scratch.

It provides a unique, detailed picture of a population: Certain types of secondary data, especially government administrative data, can provide access to levels of detail that it would otherwise be extremely difficult (or impossible) for organizations to collect on their own. Data from public sources, for instance, can provide organizations and individuals with a far greater level of population detail than they could ever hope to gather in-house. You can also obtain data over larger intervals if you need it., e.g. stock market data which provides decades’-worth of information.

Secondary data can build useful relationships: Acquiring secondary data usually involves making connections with organizations and analysts in fields that share some common ground with your own. This opens the door to a cross-pollination of disciplinary knowledge. You never know what nuggets of information or additional data resources you might find by building these relationships.

Secondary data tend to be high-quality: Unlike some data sources, e.g. third-party data, secondary data tends to be in excellent shape. In general, secondary datasets have already been validated and therefore require minimal checking. Often, such as in the case of government data, datasets are also gathered and quality-assured by organizations with much more time and resources available. This further benefits the data quality , while benefiting smaller organizations that don’t have endless resources available.

It’s excellent for both data enrichment and informing primary data collection: Another benefit of secondary data is that they can be used to enhance and expand existing datasets. Secondary data can also inform primary data collection strategies. They can provide analysts or researchers with initial insights into the type of data they might want to collect themselves further down the line.

6. Disadvantages of secondary data

They aren’t always free: Sometimes, it’s unavoidable—you may have to pay for access to secondary data. However, while this can be a financial burden, in reality, the cost of purchasing a secondary dataset usually far outweighs the cost of having to plan for and collect the data firsthand.

The data isn’t always suited to the problem at hand: While secondary data may tick many boxes concerning its relevance to a business problem, this is not always true. For instance, secondary data collection might have been in a geographical location or time period ill-suited to your analysis. Because analysts were not present when the data were initially collected, this may also limit the insights they can extract.

The data may not be in the preferred format: Even when a dataset provides the necessary information, that doesn’t mean it’s appropriately stored. A basic example: numbers might be stored as categorical data rather than numerical data. Another issue is that there may be gaps in the data. Categories that are too vague may limit the information you can glean. For instance, a dataset of people’s hair color that is limited to ‘brown, blonde and other’ will tell you very little about people with auburn, black, white, or gray hair.

You can’t be sure how the data were collected: A structured, well-ordered secondary dataset may appear to be in good shape. However, it’s not always possible to know what issues might have occurred during data collection that will impact their quality. For instance, poor response rates will provide a limited view. While issues relating to data collection are sometimes made available alongside the datasets (e.g. for government data) this isn’t always the case. You should therefore treat secondary data with a reasonable degree of caution.

Being aware of these disadvantages is the first step towards mitigating them. While you should be aware of the risks associated with using secondary datasets, in general, the benefits far outweigh the drawbacks.

7. Wrap-up and further reading

In this post we’ve explored secondary data in detail. As we’ve seen, it’s not so different from other forms of data. What defines data as secondary data is how it is used rather than an inherent characteristic of the data themselves.

To learn more about data analytics, check out this free, five-day introductory data analytics short course . You can also check out these articles to learn more about the data analytics process:

What is data cleaning and why is it important?
What is data visualization? A complete introductory guide
10 Great places to find free datasets for your next project

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Secondary Analysis Research

In secondary data analysis (SDA) studies, investigators use data collected by other researchers to address different questions. Like primary data researchers, SDA investigators must be knowledgeable about their research area to identify datasets that are a good fit for an SDA. Several sources of datasets may be useful for SDA, and examples of some of these will be discussed. Advanced practice providers must be aware of possible advantages, such as economic savings, the ability to examine clinically significant research questions in large datasets that may have been collected over time (longitudinal data), generating new hypotheses or clarifying research questions, and avoiding overburdening sensitive populations or investigating sensitive areas. When reading an SDA report, the reader should be able to determine that the authors identified the limitation or disadvantages of their research. For example, a primary dataset cannot “fit” an SDA researcher’s study exactly, SDAs are inherently limited by the inability to definitively examine causality given their retrospective nature, and data may be too old to address current issues.

Secondary analysis of data collected by another researcher for a different purpose, or SDA, is increasing in the medical and social sciences. This is not surprising, given the immense body of health care–related research performed worldwide and the potential beneficial clinical implications of the timely expansion of primary research ( Johnston, 2014 ; Tripathy, 2013 ). Oncology advanced practitioners should understand why and how SDA studies are done, their potential advantages and disadvantages, as well as the importance of reading primary and secondary analysis research reports with the same discriminatory, evaluative eye for possible applicability to their practice setting.

To perform a primary research study, an investigator identifies a problem or question in a particular population that is amenable to the study, designs a research project to address that question, decides on a quantitative or qualitative methodology, determines an adequate sample size and recruits representative subjects, and systematically collects and analyzes data to address specific research questions. On the other hand, an SDA addresses new questions from that dataset previously gathered for a different primary study ( Castle, 2003 ). This might sound “easier,” but investigators who carry out SDA research must have a broad knowledge base and be up to date regarding the state of the science in their area of interest to identify important research questions, find appropriate datasets, and apply the same research principles as primary researchers.

Most SDAs use quantitative data, but some qualitative studies lend themselves to SDA. The researcher must have access to source data, as opposed to secondary source data (e.g., a medical record review). Original qualitative data sources could be videotaped or audiotaped interviews or transcripts, or other notes from a qualitative study ( Rew, Koniak-Griffin, Lewis, Miles, & O’Sullivan, 2000 ). Another possible source for qualitative analysis is open-ended survey questions that reflect greater meaning than forced-response items.

SECONDARY ANALYSIS PROCESS

An SDA researcher starts with a research question or hypothesis, then identifies an appropriate dataset or sets to address it; alternatively, they are familiar with a dataset and peruse it to identify other questions that might be answered by the available data ( Cheng & Phillips, 2014 ). In reality, SDA researchers probably move back and forth between these approaches. For example, an investigator who starts with a research question but does not find a dataset with all needed variables usually must modify the research question(s) based on the best available data.

Secondary data analysis researchers access primary data via formal (public or institutional archived primary research datasets) or informal data sharing sources (pooled datasets separately collected by two or more researchers, or other independent researchers in carrying out secondary analysis; Heaton, 2008 ). There are numerous sources of datasets for secondary analysis. For example, a graduate student might opt to perform a secondary analysis of an advisor’s research. University and government online sites may also be useful, such as the NYU Libraries Data Sources ( https://guides.nyu.edu/c.php?g=276966&p=1848686 ) or the National Cancer Institute, which has many subcategories of datasets ( https://www.cancer.gov/research/resources/search?from=0&toolTypes=datasets_databases ). The Google search engine is useful, and researchers can enter the search term “Archive sources of datasets (add key words related to oncology).”

In one secondary analysis method, researchers reuse their own data—either a single dataset or combined respective datasets to investigate new or additional questions for a new SDA.

Example of a Secondary Data Analysis

An example highlighting this method of reusing one’s own data is Winters-Stone and colleagues’ SDA of data from four previous primary studies they performed at one institution, published in the Journal of Clinical Oncology (JCO) in 2017. Their pooled sample was 512 breast cancer survivors (age 63 ± 6 years) who had been diagnosed and treated for nonmetastatic breast cancer 5.8 years (± 4.1 years) earlier. The investigators divided the cohort, which had no diagnosed neurologic conditions, into two groups: women who reported symptoms consistent with lower-extremity chemotherapy-induced peripheral neuropathy (CIPN; numbness, tingling, or discomfort in feet) vs. CIPN-negative women who did not have symptoms. The objectives of the study were to define patient-reported prevalence of CIPN symptoms in women who had received chemotherapy, compare objective and subjective measures of CIPN in these cancer survivors, and examine the relationship between CIPN symptom severity and outcomes. Objective and subjective measures were used to compare groups for manifestations influenced by CIPN (physical function, disability, and falls). Actual chemotherapy regimens administered had not been documented (a study limitation, but regimens likely included a taxane that is neurotoxic); therefore, investigators could only confirm that symptoms began during chemotherapy and how severely patients rated symptoms.

Up to 10 years after completing chemotherapy, 47% of women who had received chemotherapy were still having significant and potentially life-threatening sensory symptoms consistent with CIPN, did worse on physical function tests, reported poorer functioning, had greater disability, and had nearly twice the rate of falls compared with CIPN-negative women ( Winters-Stone et al., 2017 ). Furthermore, symptom severity was related to worse outcomes, while worsening cancer was not.

Stout (2017) recognized the importance of this secondary analysis in an accompanying editorial published in JCO, remarking that it was the first study that included both patient-reported subjective measures and objective measures of a clinically significant problem. Winter-Stone and others (2017) recognized that by analyzing what essentially became a large sample, they were able to achieve a more comprehensive understanding of the significance and impact of CIPN, and thus to challenge the notion that while CIPN may improve over time, it remains a major cancer survivorship issue. Thus, oncology advanced practitioners must systematically address CIPN at baseline and over time in vulnerable patients, and collaborate with others to implement potentially helpful interventions such as physical and occupational therapy ( Silver & Gilchrist, 2011 ). Other primary or secondary research projects might focus on the usefulness of such interventions.

ADVANTAGES OF SECONDARY DATA ANALYSIS

The advantages of doing SDA research that are cited most often are the economic savings—in time, money, and labor—and the convenience of using existing data rather than collecting primary data, which is usually the most time-consuming and expensive aspect of research ( Johnston, 2014 ; Rew et al., 2000 ; Tripathy, 2013 ). If there is a cost to access datasets, it is usually small (compared to performing the data collection oneself), and detailed information about data collection and statistician support may also be available ( Cheng & Phillips, 2014 ). Secondary data analysis may help a new investigator increase his/her clinical research expertise and avoid data collection challenges (e.g., recruiting study participants, obtaining large-enough sample sizes to yield convincing results, avoiding study dropout, and completing data collection within a reasonable time). Secondary data analyses may also allow for examining more variables than would be feasible in smaller studies, surveys of more diverse samples, and the ability to rethink data and use more advanced statistical techniques in analysis ( Rew et al., 2000 ).

Secondary Data Analysis to Answer Additional Research Questions

Another advantage is that an SDA of a large dataset, possibly combining data from more than one study or by using longitudinal data, can address high-impact, clinically important research questions that might be prohibitively expensive or time-consuming for primary study, and potentially generate new hypotheses ( Smith et al., 2011 ; Tripathy, 2013 ). Schadendorf and others (2015) did one such SDA: a pooled analysis of 12 phase II and phase III studies of ipilimumab (Yervoy) for patients with metastatic melanoma. The study goal was to more accurately estimate the long-term survival benefit of ipilimumab every 3 weeks for greater than or equal to 4 doses in 1,861 patients with advanced melanoma, two thirds of whom had been previously treated and one third who were treatment naive. Almost 89% of patients had received ipilimumab at 3 mg/kg (n = 965), 10 mg/kg (n = 706), or other doses, and about 54% had been followed for longer than 5 years. Across all studies, overall survival curves plateaued between 2 and 3 years, suggesting a durable survival benefit for some patients.

Irrespective of prior therapy, ipilimumab dose, or treatment regimen, median overall survival was 13.5 months in treatment naive patients and 10.7 months in previously treated patients ( Schadendorf et al., 2015 ). In addition, survival curves consistently plateaued at approximately year 3 and continued for up to 10 years (longest follow-up). This suggested that most of the 20% to 26% of patients who reached the plateau had a low risk of death from melanoma thereafter. The authors viewed these results as “encouraging,” given the historic median overall survival in patients with advanced melanoma of 8 to 10 months and 5-year survival of approximately 10%. They identified limitations of their SDA (discussed later in this article). Three-year survival was numerically (but not statistically significantly) greater for the patients who received ipilimumab at 10 mg/kg than at 3 mg/kg doses, which had been noted in one of the included studies.

The importance of this secondary analysis was clearly relevant to prescribers of anticancer therapies, and led to a subsequent phase III trial in the same population to answer the ipilimumab dose question. Ascierto and colleagues’ (2017) study confirmed ipilimumab at 10 mg/kg led to a significantly longer overall survival than at 3 mg/kg (15.7 months vs. 11.5 months) in a subgroup of patients not previously treated with a BRAF inhibitor or immune checkpoint inhibitor. However, this was attained at the cost of greater treatment-related adverse events and more frequent discontinuation secondary to severe ipilimumab-related adverse events. Both would be critical points for advanced practitioners to discuss with patients and to consider in relationship to the particular patient’s ability to tolerate a given regimen.

Secondary Data Analysis to Avoid Study Repetition and Over-Research

Secondary data analysis research also avoids study repetition and over-research of sensitive topics or populations ( Tripathy, 2013 ). For example, people treated for cancer in the United Kingdom are surveyed annually through the National Cancer Patient Experience Survey (NCPES), and questions regarding sexual orientation were first included in the 2013 NCPES. Hulbert-Williams and colleagues (2017) did a more rigorous SDA of this survey to gain an understanding of how lesbian, gay, or bisexual (LGB) patients’ experiences with cancer differed from heterosexual patients.

Sixty-four percent of those surveyed responded (n = 68,737) to the question regarding their “best description of sexual orientation.” 89.3% indicated “heterosexual/straight,” 425 (0.6%) indicated “lesbian or gay,” and 143 (0.2%) indicated “bisexual.” One insight gained from the study was that although the true population proportion of LGB was not known, the small number of self-identified LGB patients most likely did not reflect actual numbers and may have occurred because of ongoing unwillingness to disclose sexual orientation, along with the older mean age of the sample. Other cancer patients who selected “prefer not to answer” (3%), “other” (0.9%), or left the question blank (6%), were not included in the SDA to correctly avoid bias in assuming these responses were related to sexual orientation.

Bisexual respondents were significantly more likely to report that nurses or other health-care professionals informed them about their diagnosis, but that it was subsequently difficult to contact nurse specialists and get understandable answers from them; they were dissatisfied with their interaction with hospital nurses and the care and help provided by both health and social care services after leaving the hospital. Bisexual and lesbian/gay respondents wanted to be involved in treatment decision-making, but therapy choices were not discussed with them, and they were all less satisfied than heterosexuals with the information given to them at diagnosis and during treatment and aftercare—an important clinical implication for oncology advanced practitioners.

Hulbert-Williams and colleagues (2017) proposed that while health-care communication and information resources are not explicitly homophobic, we may perpetuate heterosexuality as “normal” by conversational cues and reliance on heterosexual imagery that implies a context exclusionary of LGB individuals. Sexual orientation equality is about matching care to individual needs for all patients regardless of sexual orientation rather than treating everyone the same way, which does not seem to have happened according to the surveyed respondents’ perceptions. In addition, although LGB respondents replied they did not have or chose to exclude significant others from their cancer experience, there was no survey question that clarified their primary relationship status. This is not a unique strategy for persons with cancer, as LGB individuals may do this to protect family and friends from the negative consequences of homophobia.

Hulbert-Williams and others (2017) identified that this dataset might be useful to identify care needs for patients who identify as LGBT or LGBTQ (queer or questioning; no universally used acronym) and be used to obtain more targeted information from subsequent surveys. There is a relatively small body of data for advanced practitioners and other providers that aid in the assessment and care (including supportive, palliative, and survivorship care) of LGBT individuals—a minority group with many subpopulations that may have unique needs. One such effort is the white paper action plan that came out of the first summit on cancer in the LGBT communities. In 2014, participants from the United States, the United Kingdom, and Canada met to identify LGBT communities’ concerns and needs for cancer research, clinical cancer care, health-care policy, and advocacy for cancer survivorship and LGBT health equity ( Burkhalter et al., 2016 ).

More specifically, Healthy People 2020 now includes two objectives regarding LGBT issues: (1) to increase the number of population-based data systems used to monitor Healthy People 2020 objectives, including a standardized set of questions that identify lesbian, gay, bisexual, and transgender populations; and (2) to increase the number of states and territories that include questions that identify sexual orientation and gender identity on state-level surveys or data systems ( Office of Disease Prevention and Health Promotion, 2019 ). We should help each patient to designate significant others’ (family or friends) degree of involvement in care, while recognizing that LGB patients may exclude their significant others if this process involves disclosing sexual orientation, as this may lead to continued social isolation of cancer patients. This SDA by Hulbert-Williams and colleagues (2017) produced findings in a relatively unexplored area of the overall care experiences of LGB patients.

DISADVANTAGES OF SECONDARY DATA ANALYSIS

Many drawbacks of SDA research center around the fact that a primary investigator collected data reflecting his/her unique perspectives and questions, which may not fit an SDA researcher’s questions ( Rew et al., 2000 ). Secondary data analysis researchers have no control over a desired study population, variables of interest, and study design, and probably did not have a role in collecting the primary data ( Castle, 2003 ; Johnston, 2014 ; Smith et al., 2011 ).

Furthermore, the primary data may not include particular demographic information (e.g., respondent zip codes, race, ethnicity, and specific ages) that were deleted to protect respondent confidentiality, or some other different variables that might be important in the SDA may not have been examined at all ( Cheng & Phillips, 2014 ; Johnston, 2014 ). Although primary data collection takes longer than SDA data collection, identifying and procuring suitable SDA data, analyzing the overall quality of the data, determining any limitations inherent in the original study, and determining whether there is an appropriate fit between the purpose of the original study and the purpose of the SDA can be very time consuming ( Castle, 2003 ; Cheng & Phillips, 2014 ; Rew et al., 2000 ).

Secondary data analysis research may be limited to descriptive, exploratory, and correlational designs and nonparametric statistical tests. By their nature, SDA studies are observational and retrospective, and the investigator cannot examine causal relationships (by a randomized, controlled design). An SDA investigator is challenged to decide whether archival data can be shaped to match new research questions; this means the researcher must have an in-depth understanding of the dataset and know how to alter research questions to match available data and recoded variables.

For example, in their pooled analysis of ipilimumab for advanced melanoma, Schadendorf and colleagues (2015) recognized study limitations that might also be disadvantages of other SDAs. These included the fact that they could not make definitive conclusions about the relationship of survival to ipilimumab dose because the study was not randomized, had no control group, and could not account for key baseline prognostic factors. Other limitations were differences in patient populations in several studies included in the SDA, studies that had been done over 10 years ago (although no other new therapies had improved overall survival during that time), and the fact that treatments received after ipilimumab could have affected overall survival.

READING SECONDARY ANALYSIS RESEARCH

Primary and secondary data investigators apply the same research principles, which should be evident in research reports ( Cheng & Phillips, 2014 ; Hulbert-Williams et al., 2017 ; Johnston, 2014 ; Rew et al., 2000 ; Smith et al., 2011 ; Tripathy, 2013 ).

● Did the investigator(s) make a logical and convincing case for the importance of their study?
● Is there a clear research question and/or study goals or objectives?
● Are there operational definitions for the variables of interest?
● Did the authors acknowledge the source of the original data and acquire ethical approval (as necessary)?
● Did the authors discuss the strengths and weaknesses of the dataset? For example, how old are the data? Is the dataset sufficiently large to have confidence in the results (adequately powered)?
● How well do the data seem to “fit” the SDA research question and design?
● Does the methods section allow you, the reader, to “see” how the study was done (e.g., how the sample was selected, the tools/instruments that were used, as well their validity and reliability to measure what was intended, the data collection process, and how the data was analyzed)?
● Do the findings, discussion, and conclusions—positive or negative—allow you to answer the “So what?” question, and does your evaluation match the investigator’s conclusion?

Answering these questions allows the advanced practice provider reader to assess the possible value of a secondary analysis (similarly to a primary research) report and its applicability to practice, and to identify further issues or areas for scientific inquiry.

The author has no conflicts of interest to disclose.

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secondary research advantages and disadvantages

Secondary research plays a significant role in the world of data analysis and decision-making. By utilizing existing data gathered by others, this research method offers numerous advantages and disadvantages. Understanding these pros and cons can empower researchers to make informed choices when it comes to leveraging secondary research. In this article, we will delve into the advantages and disadvantages of secondary research to help you navigate this valuable research approach.

Advantages of Secondary Research

Advantages
1. Cost-effective
2. Time-saving
3. Access to vast data
4. Helps in designing primary research
5. Provides historical data
6. Useful for comparative analysis

1. Cost-effective

One of the most notable advantages of secondary research is its cost-effectiveness. Since secondary research relies on existing data, there is no need to allocate funds for primary data collection. Researchers can access a wealth of information through libraries, databases, and online sources without incurring significant expenses. This cost-saving aspect makes secondary research an attractive option for individuals and organizations with limited budgets.

2. Time-saving

Secondary research is also known for its time-saving nature. Instead of spending precious time and effort on conducting primary data collection, researchers can utilize existing data to gain insights and draw conclusions. This method eliminates the need for lengthy planning, recruitment of participants, and data collection processes. By leveraging pre-existing data sources, researchers can accelerate their analysis and make well-informed decisions in a shorter span of time.

3. Access to vast data

Secondary research offers access to a vast amount of data from a variety of sources. Libraries, government agencies, research organizations, and online databases provide researchers with a plethora of reports, studies, surveys, and other relevant information. This wide range of available data can broaden the scope of analysis and enable researchers to gather insights from multiple perspectives.

4. Helps in designing primary research

Before conducting primary research, utilizing secondary research can be immensely valuable in designing the research process. By reviewing existing studies, reports, and data, researchers can identify gaps, refine their research questions, and design their primary research methodology more effectively. Secondary research acts as a foundation for primary research projects, aiding in the formulation of hypotheses and experimental designs for more focused investigations.

5. Provides historical data

Secondary research often incorporates historical data, which can be instrumental in assessing trends, patterns, and changes over time. By examining past research and data collected in different time periods, researchers can gain a historical context that enriches their understanding of current phenomena. Historical data allows for longitudinal analysis and provides a valuable perspective on how things have evolved, helping researchers to make more accurate predictions and draw meaningful conclusions.

6. Useful for comparative analysis

Comparative analysis is simplified through secondary research, as existing data from different sources can be combined and compared. By examining data from multiple studies or sources, researchers can identify similarities, differences, and anomalies across different populations, regions, or timeframes. This comparative approach enhances the validity and reliability of research findings, enabling researchers to generalize or contextualize their conclusions.

Disadvantages of Secondary Research

Disadvantages
1. Quality of data varies
2. Lack of control over data collection
3. Potential bias in sources
4. Limited customization
5. Data may not be up to date
6. Incompatibility of data sources

1. Quality of data varies

The quality of secondary data can vary significantly depending on its source. Researchers must carefully evaluate the reliability, credibility, and validity of the data they choose to utilize. Some sources may employ rigorous data collection methods, while others may lack proper methodologies, leading to inaccurate or biased findings. It is crucial to critically assess the quality and authenticity of secondary data to ensure its suitability for the research project.

2. Lack of control over data collection

Unlike primary research, where researchers have direct control over data collection processes, secondary research relies on data gathered by others. Researchers have no influence over the design, methodology, or execution of data collection. This lack of control can introduce potential biases, limitations, or gaps in the data. Researchers must be vigilant in considering the limitations and potential biases associated with the original data collection procedures.

3. Potential bias in sources

Sources of secondary data may be influenced by various biases, including the bias of the original researchers or organizations. If the source has a particular agenda or viewpoint, this bias can affect the conclusions drawn from the secondary data. Researchers need to be aware of the potential biases in the sources they rely on and employ appropriate analytical techniques to mitigate them. By cross-referencing data from multiple sources, researchers can minimize the impact of individual biases.

4. Limited customization

While secondary research offers a wide range of existing data, there may be limitations to customization. The collected data may not precisely align with the specific research objectives or requirements at hand. Researchers may encounter restrictions in terms of variables, sample size, or methodologies employed in the original studies. This lack of customization may necessitate additional primary research to fill in the gaps or collect more targeted data.

5. Data may not be up to date

Secondary data sources may not always provide the most current information. As research studies and reports take time to be published, the data collected might not reflect the current situation or dynamic changes in the industry. This time lag can limit the timeliness and relevance of the data and may require researchers to seek supplementary primary data to complement the existing secondary data.

6. Incompatibility of data sources

Combining data from different sources can be challenging due to compatibility issues. Data collected by various researchers or organizations may use different methodologies, variables, or measurement scales, making direct comparisons difficult. Researchers must invest time and effort to reconcile and harmonize these disparate data sources to ensure compatibility and consistency in their analysis.

The Benefits of Knowing the Secondary Research Advantages and Disadvantages

Understanding the advantages and disadvantages of secondary research empowers researchers to make informed decisions when it comes to data collection and analysis. By recognizing the cost-effectiveness, time-saving potential, access to extensive data, and historical insights offered by secondary research, researchers can leverage existing resources effectively. Moreover, being aware of the limitations and challenges associated with secondary research enables researchers to critically evaluate data quality, address potential biases, customize the research methodology, and stay updated with current information. Armed with this knowledge, researchers can harness the power of secondary research to enhance their studies and contribute to the advancement of knowledge in their respective fields.

In conclusion, secondary research presents a wealth of advantages for researchers, including cost savings, time efficiency, access to vast datasets, and the ability to inform primary research design. Nevertheless, there are also limitations to consider, such as variations in data quality, lack of control over data collection, potential biases, limited customization, outdated information, and compatibility issues. Understanding these advantages and disadvantages enables researchers to navigate the world of secondary research more effectively, ultimately leading to more robust and insightful research outcomes.

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Secondary Research: Definition, Methods and Examples.

In the world of research, there are two main types of data sources: primary and secondary. While primary research involves collecting new data directly from individuals or sources, secondary research involves analyzing existing data already collected by someone else. Today we’ll discuss secondary research.

One common source of this research is published research reports and other documents. These materials can often be found in public libraries, on websites, or even as data extracted from previously conducted surveys. In addition, many government and non-government agencies maintain extensive data repositories that can be accessed for research purposes.

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While secondary research may not offer the same level of control as primary research, it can be a highly valuable tool for gaining insights and identifying trends. Researchers can save time and resources by leveraging existing data sources while still uncovering important information.

What is Secondary Research: Definition

Secondary research is a research method that involves using already existing data. Existing data is summarized and collated to increase the overall effectiveness of the research.

One of the key advantages of secondary research is that it allows us to gain insights and draw conclusions without having to collect new data ourselves. This can save time and resources and also allow us to build upon existing knowledge and expertise.

When conducting secondary research, it’s important to be thorough and thoughtful in our approach. This means carefully selecting the sources and ensuring that the data we’re analyzing is reliable and relevant to the research question . It also means being critical and analytical in the analysis and recognizing any potential biases or limitations in the data.

LEARN ABOUT: Level of Analysis

Secondary research is much more cost-effective than primary research , as it uses already existing data, unlike primary research, where data is collected firsthand by organizations or businesses or they can employ a third party to collect data on their behalf.

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Secondary Research Methods with Examples

Secondary research is cost-effective, one of the reasons it is a popular choice among many businesses and organizations. Not every organization is able to pay a huge sum of money to conduct research and gather data. So, rightly secondary research is also termed “ desk research ”, as data can be retrieved from sitting behind a desk.

The following are popularly used secondary research methods and examples:

1. Data Available on The Internet

One of the most popular ways to collect secondary data is the internet. Data is readily available on the internet and can be downloaded at the click of a button.

This data is practically free of cost, or one may have to pay a negligible amount to download the already existing data. Websites have a lot of information that businesses or organizations can use to suit their research needs. However, organizations need to consider only authentic and trusted website to collect information.

2. Government and Non-Government Agencies

Data for secondary research can also be collected from some government and non-government agencies. For example, US Government Printing Office, US Census Bureau, and Small Business Development Centers have valuable and relevant data that businesses or organizations can use.

There is a certain cost applicable to download or use data available with these agencies. Data obtained from these agencies are authentic and trustworthy.

3. Public Libraries

Public libraries are another good source to search for data for this research. Public libraries have copies of important research that were conducted earlier. They are a storehouse of important information and documents from which information can be extracted.

The services provided in these public libraries vary from one library to another. More often, libraries have a huge collection of government publications with market statistics, large collection of business directories and newsletters.

4. Educational Institutions

Importance of collecting data from educational institutions for secondary research is often overlooked. However, more research is conducted in colleges and universities than any other business sector.

The data that is collected by universities is mainly for primary research. However, businesses or organizations can approach educational institutions and request for data from them.

5. Commercial Information Sources

Local newspapers, journals, magazines, radio and TV stations are a great source to obtain data for secondary research. These commercial information sources have first-hand information on economic developments, political agenda, market research, demographic segmentation and similar subjects.

Businesses or organizations can request to obtain data that is most relevant to their study. Businesses not only have the opportunity to identify their prospective clients but can also know about the avenues to promote their products or services through these sources as they have a wider reach.

Key Differences between Primary Research and Secondary Research

Understanding the distinction between primary research and secondary research is essential in determining which research method is best for your project. These are the two main types of research methods, each with advantages and disadvantages. In this section, we will explore the critical differences between the two and when it is appropriate to use them.


Research is conducted first hand to obtain data. Researcher “owns” the data collected.	Research is based on data collected from previous researches.
is based on raw data.	Secondary research is based on tried and tested data which is previously analyzed and filtered.
The data collected fits the needs of a researcher, it is customized. Data is collected based on the absolute needs of organizations or businesses.	Data may or may not be according to the requirement of a researcher.
Researcher is deeply involved in research to collect data in primary research.	As opposed to primary research, secondary research is fast and easy. It aims at gaining a broader understanding of subject matter.
Primary research is an expensive process and consumes a lot of time to collect and analyze data.	Secondary research is a quick process as data is already available. Researcher should know where to explore to get most appropriate data.

How to Conduct Secondary Research?

We have already learned about the differences between primary and secondary research. Now, let’s take a closer look at how to conduct it.

Secondary research is an important tool for gathering information already collected and analyzed by others. It can help us save time and money and allow us to gain insights into the subject we are researching. So, in this section, we will discuss some common methods and tips for conducting it effectively.

Here are the steps involved in conducting secondary research:

1. Identify the topic of research: Before beginning secondary research, identify the topic that needs research. Once that’s done, list down the research attributes and its purpose.

2. Identify research sources: Next, narrow down on the information sources that will provide most relevant data and information applicable to your research.

3. Collect existing data: Once the data collection sources are narrowed down, check for any previous data that is available which is closely related to the topic. Data related to research can be obtained from various sources like newspapers, public libraries, government and non-government agencies etc.

4. Combine and compare: Once data is collected, combine and compare the data for any duplication and assemble data into a usable format. Make sure to collect data from authentic sources. Incorrect data can hamper research severely.

4. Analyze data: Analyze collected data and identify if all questions are answered. If not, repeat the process if there is a need to dwell further into actionable insights.

Advantages of Secondary Research

Secondary research offers a number of advantages to researchers, including efficiency, the ability to build upon existing knowledge, and the ability to conduct research in situations where primary research may not be possible or ethical. By carefully selecting their sources and being thoughtful in their approach, researchers can leverage secondary research to drive impact and advance the field. Some key advantages are the following:

1. Most information in this research is readily available. There are many sources from which relevant data can be collected and used, unlike primary research, where data needs to collect from scratch.

2. This is a less expensive and less time-consuming process as data required is easily available and doesn’t cost much if extracted from authentic sources. A minimum expenditure is associated to obtain data.

3. The data that is collected through secondary research gives organizations or businesses an idea about the effectiveness of primary research. Hence, organizations or businesses can form a hypothesis and evaluate cost of conducting primary research.

4. Secondary research is quicker to conduct because of the availability of data. It can be completed within a few weeks depending on the objective of businesses or scale of data needed.

As we can see, this research is the process of analyzing data already collected by someone else, and it can offer a number of benefits to researchers.

Disadvantages of Secondary Research

On the other hand, we have some disadvantages that come with doing secondary research. Some of the most notorious are the following:

1. Although data is readily available, credibility evaluation must be performed to understand the authenticity of the information available.

2. Not all secondary data resources offer the latest reports and statistics. Even when the data is accurate, it may not be updated enough to accommodate recent timelines.

3. Secondary research derives its conclusion from collective primary research data. The success of your research will depend, to a greater extent, on the quality of research already conducted by primary research.

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In conclusion, secondary research is an important tool for researchers exploring various topics. By leveraging existing data sources, researchers can save time and resources, build upon existing knowledge, and conduct research in situations where primary research may not be feasible.

There are a variety of methods and examples of secondary research, from analyzing public data sets to reviewing previously published research papers. As students and aspiring researchers, it’s important to understand the benefits and limitations of this research and to approach it thoughtfully and critically. By doing so, we can continue to advance our understanding of the world around us and contribute to meaningful research that positively impacts society.

QuestionPro can be a useful tool for conducting secondary research in a variety of ways. You can create online surveys that target a specific population, collecting data that can be analyzed to gain insights into consumer behavior, attitudes, and preferences; analyze existing data sets that you have obtained through other means or benchmark your organization against others in your industry or against industry standards. The software provides a range of benchmarking tools that can help you compare your performance on key metrics, such as customer satisfaction, with that of your peers.

Using QuestionPro thoughtfully and strategically allows you to gain valuable insights to inform decision-making and drive business success. Start today for free! No credit card is required.

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The strengths and limitations of secondary data

Table of Contents

Last Updated on February 14, 2023 by Karl Thompson

There is a huge amount of secondary data available, it is often easier to work with than people in primary research, however you are limited to what is available and you are subject to the biases of the people who produced it!

What is secondary data?

Information which has been collected previously, by someone else, other than the researcher. Secondary data can either be qualitative, such as diaries, newspapers or government reports, or quantitative, as with official statistics, such as league tables.

Strengths of using secondary data in social research

Limitations of using secondary data, signposting.

This was a brief post, for revision purposes, designed as last minute revision for the AS and A Level sociology exams.

For more detailed posts on research methods, including secondary data, please see my page on research methods .

For more advice on the A-level sociology exams (AQA focus) please see my exams, essays and short answer questions page.

Please click here to return to the homepage – ReviseSociology.com

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Secondary research: definition, methods, & examples.

19 min read This ultimate guide to secondary research helps you understand changes in market trends, customers buying patterns and your competition using existing data sources.

In situations where you’re not involved in the data gathering process ( primary research ), you have to rely on existing information and data to arrive at specific research conclusions or outcomes. This approach is known as secondary research.

In this article, we’re going to explain what secondary research is, how it works, and share some examples of it in practice.

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What is secondary research?

Secondary research, also known as desk research, is a research method that involves compiling existing data sourced from a variety of channels . This includes internal sources (e.g.in-house research) or, more commonly, external sources (such as government statistics, organizational bodies, and the internet).

Secondary research comes in several formats, such as published datasets, reports, and survey responses , and can also be sourced from websites, libraries, and museums.

The information is usually free — or available at a limited access cost — and gathered using surveys , telephone interviews, observation, face-to-face interviews, and more.

When using secondary research, researchers collect, verify, analyze and incorporate it to help them confirm research goals for the research period.

As well as the above, it can be used to review previous research into an area of interest. Researchers can look for patterns across data spanning several years and identify trends — or use it to verify early hypothesis statements and establish whether it’s worth continuing research into a prospective area.

How to conduct secondary research

There are five key steps to conducting secondary research effectively and efficiently:

1. Identify and define the research topic

First, understand what you will be researching and define the topic by thinking about the research questions you want to be answered.

Ask yourself: What is the point of conducting this research? Then, ask: What do we want to achieve?

This may indicate an exploratory reason (why something happened) or confirm a hypothesis. The answers may indicate ideas that need primary or secondary research (or a combination) to investigate them.

2. Find research and existing data sources

If secondary research is needed, think about where you might find the information. This helps you narrow down your secondary sources to those that help you answer your questions. What keywords do you need to use?

Which organizations are closely working on this topic already? Are there any competitors that you need to be aware of?

Create a list of the data sources, information, and people that could help you with your work.

3. Begin searching and collecting the existing data

Now that you have the list of data sources, start accessing the data and collect the information into an organized system. This may mean you start setting up research journal accounts or making telephone calls to book meetings with third-party research teams to verify the details around data results.

As you search and access information, remember to check the data’s date, the credibility of the source, the relevance of the material to your research topic, and the methodology used by the third-party researchers. Start small and as you gain results, investigate further in the areas that help your research’s aims.

4. Combine the data and compare the results

When you have your data in one place, you need to understand, filter, order, and combine it intelligently. Data may come in different formats where some data could be unusable, while other information may need to be deleted.

After this, you can start to look at different data sets to see what they tell you. You may find that you need to compare the same datasets over different periods for changes over time or compare different datasets to notice overlaps or trends. Ask yourself: What does this data mean to my research? Does it help or hinder my research?

5. Analyze your data and explore further

In this last stage of the process, look at the information you have and ask yourself if this answers your original questions for your research. Are there any gaps? Do you understand the information you’ve found? If you feel there is more to cover, repeat the steps and delve deeper into the topic so that you can get all the information you need.

If secondary research can’t provide these answers, consider supplementing your results with data gained from primary research. As you explore further, add to your knowledge and update your findings. This will help you present clear, credible information.

Primary vs secondary research

Unlike secondary research, primary research involves creating data first-hand by directly working with interviewees, target users, or a target market. Primary research focuses on the method for carrying out research, asking questions, and collecting data using approaches such as:

Interviews (panel, face-to-face or over the phone)
Questionnaires or surveys
Focus groups

Using these methods, researchers can get in-depth, targeted responses to questions, making results more accurate and specific to their research goals. However, it does take time to do and administer.

Unlike primary research, secondary research uses existing data, which also includes published results from primary research. Researchers summarize the existing research and use the results to support their research goals.

Both primary and secondary research have their places. Primary research can support the findings found through secondary research (and fill knowledge gaps), while secondary research can be a starting point for further primary research. Because of this, these research methods are often combined for optimal research results that are accurate at both the micro and macro level.


First-hand research to collect data. May require a lot of time	The research collects existing, published data. May require a little time
Creates raw data that the researcher owns	The researcher has no control over data method or ownership
Relevant to the goals of the research	May not be relevant to the goals of the research
The researcher conducts research. May be subject to researcher bias	The researcher collects results. No information on what researcher bias existsSources of secondary research
Can be expensive to carry out	More affordable due to access to free data

Sources of Secondary Research

There are two types of secondary research sources: internal and external. Internal data refers to in-house data that can be gathered from the researcher’s organization. External data refers to data published outside of and not owned by the researcher’s organization.

Internal data

Internal data is a good first port of call for insights and knowledge, as you may already have relevant information stored in your systems. Because you own this information — and it won’t be available to other researchers — it can give you a competitive edge . Examples of internal data include:

Database information on sales history and business goal conversions
Information from website applications and mobile site data
Customer-generated data on product and service efficiency and use
Previous research results or supplemental research areas
Previous campaign results

External data

External data is useful when you: 1) need information on a new topic, 2) want to fill in gaps in your knowledge, or 3) want data that breaks down a population or market for trend and pattern analysis. Examples of external data include:

Government, non-government agencies, and trade body statistics
Company reports and research
Competitor research
Public library collections
Textbooks and research journals
Media stories in newspapers
Online journals and research sites

Three examples of secondary research methods in action

How and why might you conduct secondary research? Let’s look at a few examples:

1. Collecting factual information from the internet on a specific topic or market

There are plenty of sites that hold data for people to view and use in their research. For example, Google Scholar, ResearchGate, or Wiley Online Library all provide previous research on a particular topic. Researchers can create free accounts and use the search facilities to look into a topic by keyword, before following the instructions to download or export results for further analysis.

This can be useful for exploring a new market that your organization wants to consider entering. For instance, by viewing the U.S Census Bureau demographic data for that area, you can see what the demographics of your target audience are , and create compelling marketing campaigns accordingly.

2. Finding out the views of your target audience on a particular topic

If you’re interested in seeing the historical views on a particular topic, for example, attitudes to women’s rights in the US, you can turn to secondary sources.

Textbooks, news articles, reviews, and journal entries can all provide qualitative reports and interviews covering how people discussed women’s rights. There may be multimedia elements like video or documented posters of propaganda showing biased language usage.

By gathering this information, synthesizing it, and evaluating the language, who created it and when it was shared, you can create a timeline of how a topic was discussed over time.

3. When you want to know the latest thinking on a topic

Educational institutions, such as schools and colleges, create a lot of research-based reports on younger audiences or their academic specialisms. Dissertations from students also can be submitted to research journals, making these places useful places to see the latest insights from a new generation of academics.

Information can be requested — and sometimes academic institutions may want to collaborate and conduct research on your behalf. This can provide key primary data in areas that you want to research, as well as secondary data sources for your research.

Advantages of secondary research

There are several benefits of using secondary research, which we’ve outlined below:

Easily and readily available data – There is an abundance of readily accessible data sources that have been pre-collected for use, in person at local libraries and online using the internet. This data is usually sorted by filters or can be exported into spreadsheet format, meaning that little technical expertise is needed to access and use the data.
Faster research speeds – Since the data is already published and in the public arena, you don’t need to collect this information through primary research. This can make the research easier to do and faster, as you can get started with the data quickly.
Low financial and time costs – Most secondary data sources can be accessed for free or at a small cost to the researcher, so the overall research costs are kept low. In addition, by saving on preliminary research, the time costs for the researcher are kept down as well.
Secondary data can drive additional research actions – The insights gained can support future research activities (like conducting a follow-up survey or specifying future detailed research topics) or help add value to these activities.
Secondary data can be useful pre-research insights – Secondary source data can provide pre-research insights and information on effects that can help resolve whether research should be conducted. It can also help highlight knowledge gaps, so subsequent research can consider this.
Ability to scale up results – Secondary sources can include large datasets (like Census data results across several states) so research results can be scaled up quickly using large secondary data sources.

Disadvantages of secondary research

The disadvantages of secondary research are worth considering in advance of conducting research :

Secondary research data can be out of date – Secondary sources can be updated regularly, but if you’re exploring the data between two updates, the data can be out of date. Researchers will need to consider whether the data available provides the right research coverage dates, so that insights are accurate and timely, or if the data needs to be updated. Also, fast-moving markets may find secondary data expires very quickly.
Secondary research needs to be verified and interpreted – Where there’s a lot of data from one source, a researcher needs to review and analyze it. The data may need to be verified against other data sets or your hypotheses for accuracy and to ensure you’re using the right data for your research.
The researcher has had no control over the secondary research – As the researcher has not been involved in the secondary research, invalid data can affect the results. It’s therefore vital that the methodology and controls are closely reviewed so that the data is collected in a systematic and error-free way.
Secondary research data is not exclusive – As data sets are commonly available, there is no exclusivity and many researchers can use the same data. This can be problematic where researchers want to have exclusive rights over the research results and risk duplication of research in the future.

When do we conduct secondary research?

Now that you know the basics of secondary research, when do researchers normally conduct secondary research?

It’s often used at the beginning of research, when the researcher is trying to understand the current landscape . In addition, if the research area is new to the researcher, it can form crucial background context to help them understand what information exists already. This can plug knowledge gaps, supplement the researcher’s own learning or add to the research.

Secondary research can also be used in conjunction with primary research. Secondary research can become the formative research that helps pinpoint where further primary research is needed to find out specific information. It can also support or verify the findings from primary research.

You can use secondary research where high levels of control aren’t needed by the researcher, but a lot of knowledge on a topic is required from different angles.

Secondary research should not be used in place of primary research as both are very different and are used for various circumstances.

Questions to ask before conducting secondary research

Before you start your secondary research, ask yourself these questions:

Is there similar internal data that we have created for a similar area in the past?

If your organization has past research, it’s best to review this work before starting a new project. The older work may provide you with the answers, and give you a starting dataset and context of how your organization approached the research before. However, be mindful that the work is probably out of date and view it with that note in mind. Read through and look for where this helps your research goals or where more work is needed.

What am I trying to achieve with this research?

When you have clear goals, and understand what you need to achieve, you can look for the perfect type of secondary or primary research to support the aims. Different secondary research data will provide you with different information – for example, looking at news stories to tell you a breakdown of your market’s buying patterns won’t be as useful as internal or external data e-commerce and sales data sources.

How credible will my research be?

If you are looking for credibility, you want to consider how accurate the research results will need to be, and if you can sacrifice credibility for speed by using secondary sources to get you started. Bear in mind which sources you choose — low-credibility data sites, like political party websites that are highly biased to favor their own party, would skew your results.

What is the date of the secondary research?

When you’re looking to conduct research, you want the results to be as useful as possible , so using data that is 10 years old won’t be as accurate as using data that was created a year ago. Since a lot can change in a few years, note the date of your research and look for earlier data sets that can tell you a more recent picture of results. One caveat to this is using data collected over a long-term period for comparisons with earlier periods, which can tell you about the rate and direction of change.

Can the data sources be verified? Does the information you have check out?

If you can’t verify the data by looking at the research methodology, speaking to the original team or cross-checking the facts with other research, it could be hard to be sure that the data is accurate. Think about whether you can use another source, or if it’s worth doing some supplementary primary research to replicate and verify results to help with this issue.

We created a front-to-back guide on conducting market research, The ultimate guide to conducting market research , so you can understand the research journey with confidence.

In it, you’ll learn more about:

What effective market research looks like
The use cases for market research
The most important steps to conducting market research
And how to take action on your research findings

Download the free guide for a clearer view on secondary research and other key research types for your business.

Related resources

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Advantages of Secondary Research – A Definitive Guide

Published by Jamie Walker at October 19th, 2021 , Revised On August 29, 2023

An intuitive approach is to thoroughly evaluate the advantages and disadvantages of primary and secondary research before selecting the most suitable method for your research. This article presents the key advantages of secondary research so you can select the most appropriate research approach for your academic study.

Also read about the disadvantages of secondary research

Also read about the advantages of primary research

Also, read about the disadvantages of primary research

Under secondary data collection, a researcher fetches the data from the previous studies and uses it for his own research work. Researchers usually use secondary data to address new research objectives or to explore a different aspect of the original research topic of a previous study.

Points to Consider Before Undertaking Secondary Research

Before choosing secondary research, a researcher needs to assess a number of factors. Since the researcher has not collected the data they are going to work on, it is important that they acquaint themselves with it. The researcher should consider;

What was the method used to collect the data?
The population of the study
The aim of the study
Determine the response categories for each question that was displayed to respondents
Assessing whether or not to apply weights when analysing the data

Types of Secondary Data

Secondary research, like primary research, can be qualitative, quantitative, or a combination of both . Interviews or focus groups are examples of secondary qualitative data that can be used to glean a deeper understanding of a research problem or topic.

On the other hand, quantitative data is the statistical or numerical information that was obtained through surveys or questionnaires in previous studies.

Advantages of Secondary Research

The key advantage of secondary research is that data is readily available in most cases, especially from internet sources.
Secondary research sources such as online libraries, academic databases, journals, e-books, online articles, and government repositories can be accessed to collect data on any given topic . It saves time for the researcher and enables them to collect a relatively large dataset.
Many researchers appreciate the fact that secondary research is inexpensive as no direct data is being gathered from a real population.
Secondary research is beneficial in many ways, one of which is that it enables the researchers to anticipate the gaps in research on a specific topic . In other words, it can serve to generate preliminary ideas before a more in-depth study and the collection of primary data commences.
The implementation of secondary research at the beginning of an investigation will not only uncover gaps in existing data but can also shed light on whether the proposed research has already been completed and whether the information it seeks is available. As a result, this may alleviate the necessity for time-consuming and costly primary research.
Another distinct feature of secondary research is that the data is often publicly accessible and therefore does not require permission or consent from the study participants to be used. Moreover, handling secondary data appropriately can reduce the concerns about potential ethical violations during the research process.

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When to Use Secondary Research

When the goal of the proposed project is to discover knowledge gaps.
When the research project is based on previous work and is meant to explore new patterns and correlations in current data sets rather than producing fresh results.
When a researcher has a preconceived concept of what they want to accomplish and is aware that genuine data (for example, business or government reports) is already available.
There has been a recent data collection of information that is relevant to the study’s objectives, and collecting fresh data would not be cost-effective or feasible.

Sources for Secondary Research Data Collection

By the time you understand that secondary research entails a process of assimilation and integration of data from a diverse range of sources, you will begin to see how this new data repository can yield a number of new findings. The most common sources of secondary data collection include;

Online Sources: An online data collection is a common approach for secondary research since it offers researchers access to a large number of both free and commercial sources that may be readily obtained. Indeed, it might be argued that internet sources bring everything together with other relevant secondary research data sources at one click.
Library sources: Libraries, both public and private, are extremely significant sources of knowledge. Many of them, in particular, have copies of dissertations that have been contributed by academics and students. Libraries are also a great place to go for commercial research and business reports. Educational institutions, including libraries, typically contain copies of a variety of primary research that they are ready to offer in order to further knowledge and understanding in a certain field.
Government Reports: Government websites have the potential to reveal valuable research data, as they are audited and credible, and can therefore be used to draw findings in a wide range of study settings. However, caution should be exercised when attempting to access sensitive material.
Peer review journals
Textbooks and newspaper

The use of existing data to address your research questions/objectives or solve research problems is called secondary research. There are many circumstances in which secondary research can be beneficial. In this article, we have highlighted some of the most important aspects and forms of secondary research and explain why it is preferable to acquiring your own data.

Regardless of your research topic or problem, there is always a huge pool of information and potential data sets that can be collected and used for initial response. So if you are looking for data that is easy to obtain for your research, secondary research could be the right option for you.

Need Help with Secondary Data Collection?

If you are a student, a researcher, or a business looking to collect secondary research for a report, a dissertation, an essay, or another type of project, feel free to get in touch with us. You can also read about our secondary data collection service here . Our experts include highly qualified academicians, doctors, and researchers who are sure to collect authentic, reliable, up to date and relevant sources for your research study.

Frequently Asked Questions

How to perform secondary research.

To perform secondary research:

Define research objectives.
Collect existing data and sources.
Analyze scholarly articles, books, reports.
Extract relevant information.
Compare and synthesize findings.
Properly cite sources used.

Secondary Data Analysis | Definition, Advantages & Methods

Dr. Ana Morales has taught 6th-8th mathematics for over 19 years. She has a Master's degree in Mathematics Education and a doctorate in Educational Leadership and Curriculum Development from Nova Southeastern University. Dr. Morales also has the state of Florida's teacher certification for mathematics grades 5th-9th.

Laura received her Master's degree in Pure Mathematics from Michigan State University, and her Bachelor's degree in Mathematics from Grand Valley State University. She has 20 years of experience teaching collegiate mathematics at various institutions.

What are examples of secondary data?

Some examples of secondary data include sales data, finance data, government records, educational records, reports, company websites, and trade publications. In addition, data collected from government entities such as the US census is commonly used as secondary data.

What is an example of secondary data analysis?

A researcher wants to study the effectiveness of a math program implemented at a local elementary school. The researcher has access to different types of math testing data from the school that has been collected for other purposes for the past three years. To validate these secondary data, the researcher must sort it out and determine which information is suitable for the study. This includes selecting only the data from students who participated in the math program in the study. The researcher also needs to determine which secondary data collection is most reliable, such as a teacher-made test or standardized state test.

What is secondary data analysis, analyzing secondary data, lesson summary.

When conducting a study, a researcher uses data to answer the research questions. Data utilized for a study can be primary data , or data collected by the researcher first hand specifically for their own purpose, or secondary data , or data previously collected by someone else for another purpose. However, a researcher should not consider secondary data unless it meets certain characteristics such as the data being reliable, being suitable to the new study, and providing the information needed for the new study.

Secondary data analysis is the process of analyzing data collected by others. This process is important because it saves time and prevents unnecessary duplication of research. However, since the secondary data was collected for a different purpose, the researcher must learn about the purpose of the data collection, the population of the study, the objective of the original study, and each of the research questions answered with the data.

Secondary data can be obtained from many different sources. For instance, many researchers share their data with each other, and many government entities collect data and make it available for secondary analysis.

Advantages of Secondary Data

When considering the types of data, there are advantages of secondary data . Some of these advantages include:

Secondary data is cost-efficient because it eliminates the cost of data collection.
Researchers save time because the data has already been collected, so they don't have to collect new data.
It is easy to access most secondary data.
Since secondary data can be accessed from different time periods, it can be perfect for longitudinal analyses.

Disadvantages of Secondary Data

Equally important, there are disadvantages of secondary data that must be taken into consideration when using data.

The following are some of the disadvantages of utilizing secondary data:

The secondary data may not be a perfect fit for the new study because it was collected for another purpose.
There is a lot of secondary data available, therefore it can be very time-consuming and overwhelming trying to sort through it all to figure out what fits the purpose of the new study.
There is no control over the quality and reliability of the data because it was collected by another researcher.
The secondary data was collected in the past so it may be outdated.
The secondary data may be incomplete for the purpose of the new study.

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0:03 What Is Secondary Data?
1:25 Secondary Data Analysis
2:44 Secondary Data…
3:28 Secondary Data…
4:38 Lesson Summary

To conduct secondary data analysis, the first step the researcher must do it to identify where to find the data. Data could come from a variety of sources. Identifying the data source is important because it must match the research process and match with the type of data the researcher needs. Some popular sources of secondary data include government documents, business reports , reference books or encyclopedias , the internet, and mass media. A researcher may find data from an internal source, or data generated by someone else within the research company or organization. On the other hand, external data sources are those generated or collected outside the organization. Secondary data can also be classified as quantitative or qualitative. Quantitative data can be expressed as a number; for example, the number of working hours or the age of a person. Qualitative data cannot be expressed as a number, for example, socioeconomic status or eye color. It is important that the source of the data can is credible, or can be trusted, and that the type of the data matches with what the researcher needs.

Equally important, the researcher must determine which of the secondary data collected is relevant to the new study. For example, will the data provide the right information to help the researcher answer the research question(s)? Validating the secondary data is an important process for analyzing secondary data. To validate the secondary data, the researcher must determine:

The purpose for which the data was collected
What collection methods were used
The specific population in the study and the validity of the sample
The credibility of the data collector
Any limitations of the data set
Any political circumstances or history surrounding the data collected

Once the data sources are identified and determined to be valid, the researcher must spend a significant amount of time reading through the data to sort out only the relevant information for the current study. After the researcher understands the data set and how it was collected, the data can be prepared for interpretation and cross-analysis. Analysis of secondary data follows regular statistics procedures. Once the results of analyzing the data are obtained, the data can be interpreted. The important thing to keep in mind with interpreting secondary data is to remember that the data were originally collected for some other purpose, so there may need to be restrictions or provisions that need to be made in interpreting the results. Finally, after analysis and interpretation, the researcher can make recommendations and conclusions based on the findings.

As an example, Mrs. Johnson wants to study the effectiveness of a reading program on elementary school students. Her research question is, "Does the new reading program improve reading in elementary school students?" In order to track students' reading progress, Mrs. Johnson could create a reading assessment for the students who are receiving the reading program, which would be collecting primary data. Because this would take a lot of time and resources, Mrs. Johnson instead decides to utilize the data from state reading assessments conducted for elementary school students. Data provided by the state includes information about the entire population of her school. Therefore, Mrs. Johnson will need to sort out the information regarding students who have participated in the reading program. Mrs. Johnson knows the data is credible because it comes from a state-run reading assessment, which can be trusted. To validate the secondary data, Mrs. Johnson must determine what type of information will be most useful to her study and make sure the data will help her answer her research question. Finally, Mrs. Johnson can use cross analyze and interpret the data, and finally make conclusions on whether or not the reading program was helpful.

Secondary data is data that has previously been collected by someone else first hand for another purpose. A researcher working on a new study may utilize secondary data if the data meets some criteria, such as it is reliable, it is appropriate for the new study, and it provides the information needed. One of the main secondary data advantages includes that it is cost-efficient because it eliminates the cost of data collection. However, there are also secondary data disadvantages that a researcher must take into account before considering secondary data. One of the main disadvantages is that there is a lot of secondary data available, therefore it can be very time-consuming and overwhelming trying to sort through all of it figure out what fits the purpose of the new study.

Secondary data analysis is the process of analyzing data collected by others. This process is important because it saves time and prevents unnecessary duplication of research. To conduct secondary data analysis, the first step the researcher must do is to identify where to find the data, which can come from a variety of sources, including the internet, mass media, government documents, business reports, and more. Equally important, the researcher must determine which of the secondary data collected is relevant to the new study and if the data is valid. Since the secondary data was collected for a different purpose, the researcher must learn about the purpose of the data collection, the population of the study, the objective of the original study, and each of the research questions answered with the data. The final steps of the secondary data analysis include interpreting and cross analyzing the data and making recommendations and conclusions based on the findings.

Video Transcript

What is secondary data.

Suppose you and a group of your peers are doing a research project for a class you are taking. Your group decides to do the project on the homeless population in your city. To get started, you want to collect data regarding your city.

Your group heads to the library and finds various publications on subjects such as city population, gender, ethnic groups, economic environment, and homeless statistics from past years. You're thrilled that there are numerous articles, books, journals, technical reports, official statistics, and other publications with this type of data because it makes finding information for your project a lot easier. After all, the more data that is already out there, the less you have to collect!

These different sources that you and your classmates have found at the library provide a specific type of data called secondary data. Secondary data is data that you find in a resource, whether it be in the library or on the Internet. It may be anything from government statistics to reference books to research studies. The key aspect is that you did not collect the information yourself.

You and your classmates record the secondary data that you've collected, along with the sources they come from, and head over to the student center to make some sense out of all this data and how it relates to your project. In other words, it's time for some secondary data analysis!

Secondary Data Analysis

Now that we now know what secondary data is, it's time to analyze that data. Secondary data analysis is simply the analysis of secondary data. Thankfully, you've already done part of the analysis, and that is collecting the data. Other parts of analyzing secondary data include the following:

Determining which of the data you collected is associated with your project (what data can be used)
Interpreting the secondary data to better understand your city's demographics and the homeless situation in your city
Cross-analyzing the secondary data to find out what is happening in your city regarding homelessness and why it is happening
Making recommendations, judgments, and giving ideas on how to improve homelessness in your city based on the secondary data

The analysis of secondary data involves closely and carefully weeding through the data to find data you can use for your specific purposes, figuring out how that data applies to your project, and drawing conclusions based on your findings.

It looks like you and your group are all set with secondary data, so you head out to collect some data of your own. Data that you collect is called primary data . Between the secondary and primary data analysis, you're sure to have a great project! Let's hope the teacher agrees!

Secondary Data Analysis Advantages

As with any research method, there are advantages and disadvantages to secondary data analysis.

We've already mentioned one big advantage of secondary data analysis, and that is that the data is already collected, so you don't have to do it. This can save a lot of time and energy when conducting research. Some other advantages are that secondary data is more cost efficient because it eliminates the step of collecting the data yourself. Because secondary data can be found from many years back up to a few hours ago, it provides a great way of comparing data over time. And, secondary data is great for people that aren't familiar with research methods. Anyone can collect secondary data and analyze it or be trained to analyze it.

Secondary Data Analysis Disadvantages

Wow, with those advantages, I'm sold! Secondary data analysis sounds great. Before we get too excited, let's consider some of the disadvantages of secondary data analysis.

The data was collected for another purpose, so it will probably have some imperfections regarding how it correlates to your specific study or research. Because of this, it may be harder to draw conclusions about your specific purpose from data. There is a lot of secondary data out there, so there is a lot of weeding through the data to figure out what works best for your purpose. This can be time-consuming and overwhelming.

Because you didn't collect the data, it is impossible to know the quality of the data and reliability of its source. Because the data was collected for something else, it may be incomplete for your purposes and not have all of the information you need. And, secondary data comes from research that has been done in the past: it may not give you a clear picture of what is happening in the present. Despite its disadvantages, it is clear that secondary data analysis is very useful and has great value in research and analysis.

Secondary data is data that has already been collected and used for another purpose. Secondary data analysis is simply the analysis of secondary data and involves collecting, reviewing, and drawing conclusions from your findings.

There are advantages and disadvantages to secondary data analysis. The advantages mostly revolve around the fact that the data is already collected. This saves time, money, and energy when conducting research. The disadvantages also come from the fact that the data has already been collected. Because of this, the data may not be of good quality, may not be what you need for your specific purpose, or may not be up to date.

All in all, secondary data analysis is an important and significant type of data analysis when it comes to research. Although it should not be your sole type of data and analysis when conducting research, it is a perfect addition to primary data to make for a thorough and complete research project.

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Research Methods

Secondary research.

Primary Research

What is Secondary Research?

Advantages and disadvantages of secondary research, secondary research in literature reviews, secondary research - going beyond literature reviews, main stages of secondary research, useful resources, using material on this page.

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Secondary research

Secondary research uses research and data that has already been carried out. It is sometimes referred to as desk research. It is a good starting point for any type of research as it enables you to analyse what research has already been undertaken and identify any gaps.

You may only need to carry out secondary research for your assessment or you may need to use secondary research as a starting point, before undertaking your own primary research .

Searching for both primary and secondary sources can help to ensure that you are up to date with what research has already been carried out in your area of interest and to identify the key researchers in the field.

"Secondary sources are the books, articles, papers and similar materials written or produced by others that help you to form your background understanding of the subject. You would use these to ﬁnd out about experts’ ﬁndings, analyses or perspectives on the issue and decide whether to draw upon these explicitly in your research." (Cottrell, 2014, p. 123).

Examples of secondary research sources include:.

journal articles
official statistics, such as government reports or organisations which have collected and published data

Primary research involves gathering data which has not been collected before. Methods to collect it can include interviews, focus groups, controlled trials and case studies. Secondary research often comments on and analyses this primary research.

Gopalakrishnan and Ganeshkumar (2013, p. 10) explain the difference between primary and secondary research:

"Primary research is collecting data directly from patients or population, while secondary research is the analysis of data already collected through primary research. A review is an article that summarizes a number of primary studies and may draw conclusions on the topic of interest which can be traditional (unsystematic) or systematic".

Secondary Data

As secondary data has already been collected by someone else for their research purposes, it may not cover all of the areas of interest for your research topic. This research will need to be analysed alongside other research sources and data in the same subject area in order to confirm, dispute or discuss the findings in a wider context.

"Secondary source data, as the name infers, provides second-hand information. The data come ‘pre-packaged’, their form and content reflecting the fact that they have been produced by someone other than the researcher and will not have been produced specifically for the purpose of the research project. The data, none the less, will have some relevance for the research in terms of the information they contain, and the task for the researcher is to extract that information and re-use it in the context of his/her own research project." (Denscombe, 2021, p. 268)

In the video below Dr. Benedict Wheeler (Senior Research Fellow at the European Center for Environment and Human Health at the University of Exeter Medical School) discusses secondary data analysis. Secondary data was used for his research on how the environment affects health and well-being and utilising this secondary data gave access to a larger data set.

As with all research, an important part of the process is to critically evaluate any sources you use. There are tools to help with this in the Being Critical section of the guide.

Louise Corti, from the UK Data Archive, discusses using secondary data in the video below. T he importance of evaluating secondary research is discussed - this is to ensure the data is appropriate for your research and to investigate how the data was collected.

There are advantages and disadvantages to secondary research:

Advantages:

Usually low cost
Easily accessible
Provides background information to clarify / refine research areas
Increases breadth of knowledge
Shows different examples of research methods
Can highlight gaps in the research and potentially outline areas of difficulty
Can incorporate a wide range of data
Allows you to identify opposing views and supporting arguments for your research topic
Highlights the key researchers and work which is being undertaken within the subject area
Helps to put your research topic into perspective

Disadvantages

Can be out of date
Might be unreliable if it is not clear where or how the research has been collected - remember to think critically
May not be applicable to your specific research question as the aims will have had a different focus

Literature reviews

Secondary research for your major project may take the form of a literature review . this is where you will outline the main research which has already been written on your topic. this might include theories and concepts connected with your topic and it should also look to see if there are any gaps in the research., as the criteria and guidance will differ for each school, it is important that you check the guidance which you have been given for your assessment. this may be in blackboard and you can also check with your supervisor..

The videos below include some insights from academics regarding the importance of literature reviews.

Malcolm Williams, Professor and Director of the Cardiff School of Social Sciences, discusses how to build upon previous research by conducting a thorough literature review.	Professor Geoff Payne discusses research design and how the literature review can help determine what research methods to use as well as help to further plan your project.

Secondary research which goes beyond literature reviews

For some dissertations/major projects there might only be a literature review (discussed above ). For others there could be a literature review followed by primary research and for others the literature review might be followed by further secondary research.

You may be asked to write a literature review which will form a background chapter to give context to your project and provide the necessary history for the research topic. However, you may then also be expected to produce the rest of your project using additional secondary research methods, which will need to produce results and findings which are distinct from the background chapter t o avoid repetition .

Remember, as the criteria and guidance will differ for each School, it is important that you check the guidance which you have been given for your assessment. This may be in Blackboard and you can also check with your supervisor.

Although this type of secondary research will go beyond a literature review, it will still rely on research which has already been undertaken. And, "just as in primary research, secondary research designs can be either quantitative, qualitative, or a mixture of both strategies of inquiry" (Manu and Akotia, 2021, p. 4).

Your secondary research may use the literature review to focus on a specific theme, which is then discussed further in the main project. Or it may use an alternative approach. Some examples are included below. Remember to speak with your supervisor if you are struggling to define these areas.

Some approaches of how to conduct secondary research include:

A systematic review is a structured literature review that involves identifying all of the relevant primary research using a rigorous search strategy to answer a focused research question.
This involves comprehensive searching which is used to identify themes or concepts across a number of relevant studies.
The review will assess the q uality of the research and provide a summary and synthesis of all relevant available research on the topic.
The systematic review LibGuide goes into more detail about this process (The guide is aimed a PhD/Researcher students. However, students on other levels of study may find parts of the guide helpful too).
Scoping reviews aim to identify and assess available research on a specific topic (which can include ongoing research).
They are "particularly useful when a body of literature has not yet been comprehensively reviewed, or exhibits a complex or heterogeneous nature not amenable to a more precise systematic review of the evidence. While scoping reviews may be conducted to determine the value and probable scope of a full systematic review, they may also be undertaken as exercises in and of themselves to summarize and disseminate research findings, to identify research gaps, and to make recommendations for the future research." (Peters et al., 2015) .
This is designed to summarise the current knowledge and provide priorities for future research.
"A state-of-the-art review will often highlight new ideas or gaps in research with no official quality assessment." ( MacAdden, 2020).
"Bibliometric analysis is a popular and rigorous method for exploring and analyzing large volumes of scientific data." (Donthu et al., 2021)
Quantitative methods and statistics are used to analyse the bibliographic data of published literature. This can be used to measure the impact of authors, publications, or topics within a subject area.

The bibliometric analysis often uses the data from a citation source such as Scopus or Web of Science .

This is a technique used to combine the statistic results of prior quantitative studies in order to increase precision and validity.
"It goes beyond the parameters of a literature review, which assesses existing literature, to actually perform calculations based on the results collated, thereby coming up with new results" (Curtis and Curtis, 2011, p. 220)

(Adapted from: Grant and Booth, 2009, cited in Sarhan and Manu, 2021, p. 72)

Grounded Theory is used to create explanatory theory from data which has been collected.
"Grounded theory data analysis strategies can be used with different types of data, including secondary data." (Whiteside, Mills and McCalman, 2012)
This allows you to use a specific theory or theories which can then be applied to your chosen topic/research area.
You could focus on one case study which is analysed in depth, or you could examine more than one in order to compare and contrast the important aspects of your research question.
"Good case studies often begin with a predicament that is poorly comprehended and is inadequately explained or traditionally rationalised by numerous conflicting accounts. Therefore, the aim is to comprehend an existent problem and to use the acquired understandings to develop new theoretical outlooks or explanations." (Papachroni and Lochrie, 2015, p. 81)

Main stages of secondary research for a dissertation/major project

In general, the main stages for conducting secondary research for your dissertation or major project will include:

	or ) before you dedicate too much time to your research, to make sure there is adequate published research available in that area.
	, or . You will need to justify which choice you make.
	databases for your subject area. Use your to identify these.

Click on the image below to access the reading list which includes resources used in this guide as well as some additional useful resources.

Link to online reading list of additional resources and further reading

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License .

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12 Pros and Cons of Secondary Research

Secondary research is the research method of collecting all the data and documents available from other sources. Some major companies or statistics written in some books or information gathered from some newspaper or thesis or individual research all these data are eligible to be secondary data.

It is a convenient and powerful tool for researchers looking to ask broad questions on a large scale. It benefits researchers as all the data are already taken down so it can be time-consuming but the area where it takes time might be if those data are ideal for the researcher’s goal or not.

A large amount of information can be gathered with a small effort and summarizing and relating it increases the effectiveness of research. Some pros and cons of secondary research are pointed out below.

Pros Of Secondary Research

1. accessibility .

A few years ago when you needed to collect some data then going to libraries or particular organizations was a must. And it was even impossible to gather such data by the public. The Internet has played a great role in accessing the data so easily in a single click.

The problem here will be your patience to search where it is, it’s accessed for free. Some market research or the poll by the organization or product or comment on some of the sites about the product or some news. Anything necessary for your analysis will be available you just need to search in the right place.

2. Low Cost

When the data already exists and is collected and summarized. The large sum of money is saved where you don’t need to pay the institution for the data or organize some workshops to know the people’s opinion, you can easily use social media platforms which saves you the manpower and its cost. Researchers are easily tempted by secondary data, which can be easily accessed and prepared in a short period of time without any investment.

3. Saves Time

The data are collected or documented already on the social platform in magazines or on the internet. Using internet large numbers of data are gathered by the researchers without their own effort.

The data are already been documented by the organization or the researchers which you can just collect directly and start analysis over it. This saves lots and lots of time for you where you can study the variables and ups and downs regarding the data.

4. May Help Clarify Research Question

Where primary research is most expensive because it requires both the effort and time. Secondary research tips lots of important questions that are needed while conducting primary research.

The data collected through secondary research gives an organization or the personnel an idea about the effectiveness and the overview of the issue without conducting the primary research. This saves lots of money and time here.

5. Government & Agencies

There are many database analysis performed by the government itself for the census, for health issue protocols and other general information about the citizens. This research are being carried out for a long period of time and covers almost the entire population.

Likewise, many NGO’s and INGO’s conduct such data collection during their campaign in some scarcity or spreading awareness. Including such information provided by the government publicly increases the authenticity and accuracy of your secondary research data.

6. Understand The Problem

The secondary researcher needs to analyze and examine the data they collect from the source. In this process, the researcher goes deep into the procedure of how and when were the data collected and the difficulties encountered while gathering the data.

Some reports of multinational companies while attempting the large market research already includes the obstacles faced like the people declining and people interested during research.

These data are useful to plan how’s your research feedback is going to be or how to conduct or what to change during the research to get the desired outcome or what area to cover to make our outcome more subtle or accurate.

7. New Conclusion Or Data

The data analyzed and collected are very vast varied and shows the perspective of lots of issues with different variables. This continuous and frequent analysis of these data may develop or give the statistical graph of the new variable.

For example, knowing how many hospitals are there and the number of aware citizens about healthcare gives us the data about how many doctors are needed to carry the campaign and how many connected district, city or province is going to need new hospitals and new technology.

This helps us come up with a new conclusion while verifying and confirming how the previous research was carried out.

Cons Of Secondary Research

1. quality of research.

As we know the secondary research is derived from the conclusion of the primary research, how hard we analyze it depends on the quality of the research conducted primarily.

If the originator is concerned about organizations or institutions those data might be false and may have been shown to attract clients or shareholders. Thus the validity of the data is necessary but reliability on other’s data prevents it.

2. May Not Fulfill Researcher’s Need

Secondary research data does not show exactly how or what the researcher was looking for. It is the collection of lots of data from lots of perspectives and people, some may be easy to ignore and some may be hard to validate and find its authenticity.

The researcher will be looking for data with some concern or with some particular question in mind but the data might not be collected regarding the particular issue or agenda. Meanwhile, all the data studied are not collected by the researcher they have no control over what the secondary data set may contain.

3. Incomplete Information

Not being able to get complete information about the data he/she wants to collect will affect the researcher’s study. As they are unable to know exactly how and when the procedure went wrong during execution.

It will not only be difficult to continue the research process but also confuses the researcher about where the issue is leading them.

4. Outdated Information

The most important thing one must consider while using secondary data is to note the date when the information was collected. They must be aware of how are those products and companies doing in the current situation.

It helps them to verify and ignore the achieved data. It is not possible to get all the updated reports or statistics of the data. One must be aware of not using the most outdated information in their research.

5. Lack Of Quality Data

The mindset of the researcher will be something else, they have to work on the data collected or data found in the research process. Since they are not able to carry out primary research, they should be depending on someone else’s data disregarding its quality.

As we know data are available in many forms and we are unable to know who performed the research we are forced to note down and analyze the data compromising its quality and validity.

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Library Guides

Dissertations 4: methodology: methods.

Introduction & Philosophy
Methodology

Primary & Secondary Sources, Primary & Secondary Data

When describing your research methods, you can start by stating what kind of secondary and, if applicable, primary sources you used in your research. Explain why you chose such sources, how well they served your research, and identify possible issues encountered using these sources.

Definitions

There is some confusion on the use of the terms primary and secondary sources, and primary and secondary data. The confusion is also due to disciplinary differences (Lombard 2010). Whilst you are advised to consult the research methods literature in your field, we can generalise as follows:

Secondary sources

Secondary sources normally include the literature (books and articles) with the experts' findings, analysis and discussions on a certain topic (Cottrell, 2014, p123). Secondary sources often interpret primary sources.

Primary sources

Primary sources are "first-hand" information such as raw data, statistics, interviews, surveys, law statutes and law cases. Even literary texts, pictures and films can be primary sources if they are the object of research (rather than, for example, documentaries reporting on something else, in which case they would be secondary sources). The distinction between primary and secondary sources sometimes lies on the use you make of them (Cottrell, 2014, p123).

Primary data

Primary data are data (primary sources) you directly obtained through your empirical work (Saunders, Lewis and Thornhill 2015, p316).

Secondary data

Secondary data are data (primary sources) that were originally collected by someone else (Saunders, Lewis and Thornhill 2015, p316).

Comparison between primary and secondary data

Primary data	Secondary data
Data collected directly	Data collected from previously done research, existing research is summarised and collated to enhance the overall effectiveness of the research.
Examples: Interviews (face-to-face or telephonic), Online surveys, Focus groups and Observations	Examples: data available via the internet, non-government and government agencies, public libraries, educational institutions, commercial/business information
Advantages: •Data collected is first hand and accurate. •Data collected can be controlled. No dilution of data. •Research method can be customized to suit personal requirements and needs of the research.	Advantages: •Information is readily available •Less expensive and less time-consuming •Quicker to conduct
Disadvantages: •Can be quite extensive to conduct, requiring a lot of time and resources •Sometimes one primary research method is not enough; therefore a mixed method is require, which can be even more time consuming.	Disadvantages: •It is necessary to check the credibility of the data •May not be as up to date •Success of your research depends on the quality of research previously conducted by others.

Use

Virtually all research will use secondary sources, at least as background information.

Often, especially at the postgraduate level, it will also use primary sources - secondary and/or primary data. The engagement with primary sources is generally appreciated, as less reliant on others' interpretations, and closer to 'facts'.

The use of primary data, as opposed to secondary data, demonstrates the researcher's effort to do empirical work and find evidence to answer her specific research question and fulfill her specific research objectives. Thus, primary data contribute to the originality of the research.

Ultimately, you should state in this section of the methodology:

What sources and data you are using and why (how are they going to help you answer the research question and/or test the hypothesis.

If using primary data, why you employed certain strategies to collect them.

What the advantages and disadvantages of your strategies to collect the data (also refer to the research in you field and research methods literature).

Quantitative, Qualitative & Mixed Methods

The methodology chapter should reference your use of quantitative research, qualitative research and/or mixed methods. The following is a description of each along with their advantages and disadvantages.

Quantitative research

Quantitative research uses numerical data (quantities) deriving, for example, from experiments, closed questions in surveys, questionnaires, structured interviews or published data sets (Cottrell, 2014, p93). It normally processes and analyses this data using quantitative analysis techniques like tables, graphs and statistics to explore, present and examine relationships and trends within the data (Saunders, Lewis and Thornhill, 2015, p496).

Advantages	Disadvantages
The study can be undertaken on a broader scale, generating large amounts of data that contribute to generalisation of results	Quantitative methods can be difficult, expensive and time consuming (especially if using primary data, rather than secondary data).
Suitable when the phenomenon is relatively simple, and can be analysed according to identified variables.	Not everything can be easily measured.
	Less suitable for complex social phenomena.
	Less suitable for why type questions.

Qualitative research 

Qualitative research is generally undertaken to study human behaviour and psyche. It uses methods like in-depth case studies, open-ended survey questions, unstructured interviews, focus groups, or unstructured observations (Cottrell, 2014, p93). The nature of the data is subjective, and also the analysis of the researcher involves a degree of subjective interpretation. Subjectivity can be controlled for in the research design, or has to be acknowledged as a feature of the research. Subject-specific books on (qualitative) research methods offer guidance on such research designs. 

Advantages	Disadvantages
Qualitative methods are good for in-depth analysis of individual people, businesses, organisations, events.	The findings can be accurate about the particular case, but not generally applicable.
Sample sizes don’t need to be large, so the studies can be cheaper and simpler.	More prone to subjectivity.

Mixed methods

Mixed-method approaches combine both qualitative and quantitative methods, and therefore combine the strengths of both types of research. Mixed methods have gained popularity in recent years. 

When undertaking mixed-methods research you can collect the qualitative and quantitative data either concurrently or sequentially. If sequentially, you can for example, start with a few semi-structured interviews, providing qualitative insights, and then design a questionnaire to obtain quantitative evidence that your qualitative findings can also apply to a wider population (Specht, 2019, p138).

Ultimately, your methodology chapter should state:

Whether you used quantitative research, qualitative research or mixed methods.

Why you chose such methods (and refer to research method sources).

Why you rejected other methods.

How well the method served your research.

The problems or limitations you encountered.

Doug Specht, Senior Lecturer at the Westminster School of Media and Communication, explains mixed methods research in the following video:

LinkedIn Learning Video on Academic Research Foundations: Quantitative

The video covers the characteristics of quantitative research, and explains how to approach different parts of the research process, such as creating a solid research question and developing a literature review. He goes over the elements of a study, explains how to collect and analyze data, and shows how to present your data in written and numeric form.

Link to quantitative research video

Some Types of Methods

There are several methods you can use to get primary data. To reiterate, the choice of the methods should depend on your research question/hypothesis.

Whatever methods you will use, you will need to consider:

why did you choose one technique over another? What were the advantages and disadvantages of the technique you chose?

what was the size of your sample? Who made up your sample? How did you select your sample population? Why did you choose that particular sampling strategy?)

ethical considerations (see also tab...)

safety considerations

validity

feasibility

recording

procedure of the research (see box procedural method...).

Check Stella Cottrell's book Dissertations and Project Reports: A Step by Step Guide for some succinct yet comprehensive information on most methods (the following account draws mostly on her work). Check a research methods book in your discipline for more specific guidance.

Experiments

Experiments are useful to investigate cause and effect, when the variables can be tightly controlled. They can test a theory or hypothesis in controlled conditions. Experiments do not prove or disprove an hypothesis, instead they support or not support an hypothesis. When using the empirical and inductive method it is not possible to achieve conclusive results. The results may only be valid until falsified by other experiments and observations.

For more information on Scientific Method, click here .

Observations

Observational methods are useful for in-depth analyses of behaviours in people, animals, organisations, events or phenomena. They can test a theory or products in real life or simulated settings. They generally a qualitative research method.

Questionnaires and surveys

Questionnaires and surveys are useful to gain opinions, attitudes, preferences, understandings on certain matters. They can provide quantitative data that can be collated systematically; qualitative data, if they include opportunities for open-ended responses; or both qualitative and quantitative elements.

Interviews

Interviews are useful to gain rich, qualitative information about individuals' experiences, attitudes or perspectives. With interviews you can follow up immediately on responses for clarification or further details. There are three main types of interviews: structured (following a strict pattern of questions, which expect short answers), semi-structured (following a list of questions, with the opportunity to follow up the answers with improvised questions), and unstructured (following a short list of broad questions, where the respondent can lead more the conversation) (Specht, 2019, p142).

This short video on qualitative interviews discusses best practices and covers qualitative interview design, preparation and data collection methods.

Focus groups

In this case, a group of people (normally, 4-12) is gathered for an interview where the interviewer asks questions to such group of participants. Group interactions and discussions can be highly productive, but the researcher has to beware of the group effect, whereby certain participants and views dominate the interview (Saunders, Lewis and Thornhill 2015, p419). The researcher can try to minimise this by encouraging involvement of all participants and promoting a multiplicity of views.

This video focuses on strategies for conducting research using focus groups.

Check out the guidance on online focus groups by Aliaksandr Herasimenka, which is attached at the bottom of this text box.

Case study

Case studies are often a convenient way to narrow the focus of your research by studying how a theory or literature fares with regard to a specific person, group, organisation, event or other type of entity or phenomenon you identify. Case studies can be researched using other methods, including those described in this section. Case studies give in-depth insights on the particular reality that has been examined, but may not be representative of what happens in general, they may not be generalisable, and may not be relevant to other contexts. These limitations have to be acknowledged by the researcher.

Content analysis

Content analysis consists in the study of words or images within a text. In its broad definition, texts include books, articles, essays, historical documents, speeches, conversations, advertising, interviews, social media posts, films, theatre, paintings or other visuals. Content analysis can be quantitative (e.g. word frequency) or qualitative (e.g. analysing intention and implications of the communication). It can detect propaganda, identify intentions of writers, and can see differences in types of communication (Specht, 2019, p146). Check this page on collecting, cleaning and visualising Twitter data.

Extra links and resources:

Research Methods

A clear and comprehensive overview of research methods by Emerald Publishing. It includes: crowdsourcing as a research tool; mixed methods research; case study; discourse analysis; ground theory; repertory grid; ethnographic method and participant observation; interviews; focus group; action research; analysis of qualitative data; survey design; questionnaires; statistics; experiments; empirical research; literature review; secondary data and archival materials; data collection.

Doing your dissertation during the COVID-19 pandemic

Resources providing guidance on doing dissertation research during the pandemic: Online research methods; Secondary data sources; Webinars, conferences and podcasts;

Virtual Focus Groups Guidance on managing virtual focus groups

5 Minute Methods Videos

The following are a series of useful videos that introduce research methods in five minutes. These resources have been produced by lecturers and students with the University of Westminster's School of Media and Communication.

Case Study Research

Research Ethics

Quantitative Content Analysis

Sequential Analysis

Qualitative Content Analysis

Thematic Analysis

Social Media Research

Mixed Method Research

Procedural Method

In this part, provide an accurate, detailed account of the methods and procedures that were used in the study or the experiment (if applicable!).

Include specifics about participants, sample, materials, design and methods.

If the research involves human subjects, then include a detailed description of who and how many participated along with how the participants were selected.

Describe all materials used for the study, including equipment, written materials and testing instruments.

Identify the study's design and any variables or controls employed.

Write out the steps in the order that they were completed.

Indicate what participants were asked to do, how measurements were taken and any calculations made to raw data collected.

Specify statistical techniques applied to the data to reach your conclusions.

Provide evidence that you incorporated rigor into your research. This is the quality of being thorough and accurate and considers the logic behind your research design.

Highlight any drawbacks that may have limited your ability to conduct your research thoroughly.

You have to provide details to allow others to replicate the experiment and/or verify the data, to test the validity of the research.

Bibliography

Cottrell, S. (2014). Dissertations and project reports: a step by step guide. Hampshire, England: Palgrave Macmillan.

Lombard, E. (2010). Primary and secondary sources. The Journal of Academic Librarianship , 36(3), 250-253

Saunders, M.N.K., Lewis, P. and Thornhill, A. (2015). Research Methods for Business Students. New York: Pearson Education.

Specht, D. (2019). The Media And Communications Study Skills Student Guide . London: University of Westminster Press.

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Methodology

Primary Research | Definition, Types, & Examples

Primary Research | Definition, Types, & Examples

Published on January 14, 2023 by Tegan George . Revised on January 12, 2024.

Primary research is a research method that relies on direct data collection , rather than relying on data that’s already been collected by someone else. In other words, primary research is any type of research that you undertake yourself, firsthand, while using data that has already been collected is called secondary research .

Primary research is often used in qualitative research , particularly in survey methodology, questionnaires, focus groups, and various types of interviews . While quantitative primary research does exist, it’s not as common.

When to use primary research, types of primary research, examples of primary research, advantages and disadvantages of primary research, other interesting articles, frequently asked questions.

Primary research is any research that you conduct yourself. It can be as simple as a 2-question survey, or as in-depth as a years-long longitudinal study . The only key is that data must be collected firsthand by you.

Primary research is often used to supplement or strengthen existing secondary research. It is usually exploratory in nature, concerned with examining a research question where no preexisting knowledge exists. It is also sometimes called original research for this reason.

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Primary research can take many forms, but the most common types are:

Surveys and questionnaires
Observational studies
Interviews and focus groups

Surveys and questionnaires collect information about a group of people by asking them questions and analyzing the results. They are a solid choice if your research topic seeks to investigate something about the characteristics, preferences, opinions, or beliefs of a group of people.

Surveys and questionnaires can take place online, in person, or through the mail. It is best to have a combination of open-ended and closed-ended questions, and how the questions are phrased matters. Be sure to avoid leading questions, and ask any related questions in groups, starting with the most basic ones first.

Observational studies are an easy and popular way to answer a research question based purely on what you, the researcher, observes. If there are practical or ethical concerns that prevent you from conducting a traditional experiment , observational studies are often a good stopgap.

There are three types of observational studies: cross-sectional studies , cohort studies, and case-control studies. If you decide to conduct observational research, you can choose the one that’s best for you. All three are quite straightforward and easy to design—just beware of confounding variables and observer bias creeping into your analysis.

Similarly to surveys and questionnaires, interviews and focus groups also rely on asking questions to collect information about a group of people. However, how this is done is slightly different. Instead of sending your questions out into the world, interviews and focus groups involve two or more people—one of whom is you, the interviewer, who asks the questions.

There are 3 main types of interviews:

Structured interviews ask predetermined questions in a predetermined order.
Unstructured interviews are more flexible and free-flowing, proceeding based on the interviewee’s previous answers.
Semi-structured interviews fall in between, asking a mix of predetermined questions and off-the-cuff questions.

While interviews are a rich source of information, they can also be deceptively challenging to do well. Be careful of interviewer bias creeping into your process. This is best mitigated by avoiding double-barreled questions and paying close attention to your tone and delivery while asking questions.

Alternatively, a focus group is a group interview, led by a moderator. Focus groups can provide more nuanced interactions than individual interviews, but their small sample size means that external validity is low.

Primary research can often be quite simple to pursue yourself. Here are a few examples of different research methods you can use to explore different topics.

Primary research is a great choice for many research projects, but it has distinct advantages and disadvantages.

Advantages of primary research

Advantages include:

The ability to conduct really tailored, thorough research, down to the “nitty-gritty” of your topic . You decide what you want to study or observe and how to go about doing that.
You maintain control over the quality of the data collected, and can ensure firsthand that it is objective, reliable , and valid .
The ensuing results are yours, for you to disseminate as you see fit. You maintain proprietary control over what you find out, allowing you to share your findings with like-minded individuals or those conducting related research that interests you for replication or discussion purposes.

Disadvantages of primary research

Disadvantages include:

In order to be done well, primary research can be very expensive and time consuming. If you are constrained in terms of time or funding, it can be very difficult to conduct your own high-quality primary research.
Primary research is often insufficient as a standalone research method, requiring secondary research to bolster it.
Primary research can be prone to various types of research bias . Bias can manifest on the part of the researcher as observer bias , Pygmalion effect , or demand characteristics . It can occur on the part of participants as a Hawthorne effect or social desirability bias .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Chi square goodness of fit test
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
Non-probability sampling
Quantitative research
Inclusion and exclusion criteria

Research bias

Rosenthal effect
Implicit bias
Cognitive bias
Selection bias
Negativity bias
Status quo bias

The 3 main types of primary research are:

Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomization , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.

When conducting research, collecting original data has significant advantages:

You can tailor data collection to your specific research aims (e.g. understanding the needs of your consumers or user testing your website)
You can control and standardize the process for high reliability and validity (e.g. choosing appropriate measurements and sampling methods )

However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

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Secondary Research: Meaning, Sources, Advantages, Disadvantages

On: Market Research , Marketing , Secondary Research Modified: May 7, 2024

Table of Contents

What’s it: Secondary research, or desk research, is a type of research using external data sources, not original data sources. In other words, you are not first hand and therefore have no control over the accuracy of the data. For example, you don’t know whether the data is representative or not.

Secondary research is different from primary research. For the latter, you take it from the original source. For consumer research, for example, you might survey or interview consumers. We call the data collected as primary data. You have control over data quality because you develop a methodology for data collection, including sampling.

There are many examples of secondary research sources. You can take from company reports, research agency reports, government agency publications, news articles, and so on.

Secondary research is a valuable step. You save time, money, and effort by not having to retrieve data directly. You may use all the secondary data if they answer your hypothesis. Or, you may collect some data you need and collect it directly for the rest of the data. Of course, that saves more money than having to extract all the data from the original source.

Secondary research sources

There are many examples of data sources for secondary research. It varies depending on the research objectives. For example, data sources could come from:

Research company reports. Examples are Nielsen , Euromonitor International , Kantar , Gartner , and Ipsos or consulting agencies such as McKinsey , Boston Consulting Group , and Bain & Company .
Academic textbooks or journals. They are usually poor in data with more qualitative information. They are usually useful in developing hypotheses as well as research methodologies. For example, you may have several alternative variables to research buying behavior but don’t know which ones are significant. Well, textbooks and academic journals can help you in this case.
Government publications. The central statistical agency is an example. You can find a variety of valuable data there, including demographic, geographic, economic data, and so on.
Trade association (business association). They are associations for domestic companies or companies from various countries. For international associations, the International Organization of Motor Vehicle Manufacturers (OICA) is an example. Usually, they present regular reports on the state of the markets in which their members operate.
Media . Business newspapers and magazines are valuable sources for gathering data. They may be printed or digital. Usually, they present some data to support the articles they write. Some may be free, while for others, you may need to subscribe. The Wall Street Journal, Bloomberg, The Financial Times are notable examples.
Company report. There are many reporting sources you can use. They may be annual reports, company financial reports, public expose materials, press releases, and prospectuses.

Advantages of secondary research

Advantages of secondary research are:

Easy, cheap, and fast . You don’t have to be involved in developing complicated data collection methods. You also don’t have to run surveys or interviews to collect data. You just sit at the table and look it up on the internet.

More varied . You can collect data from a variety of sources. Besides, you can compare these various data and choose which ones support your argument.

Good starting point. It is useful to help plan primary research. For example, you can collect some secondary data to answer some of your hypotheses and collect other data through primary research. In other cases, for consumer research, you may need secondary data on demographics and geography to determine a representative sample.

Disadvantages of secondary research

The main drawbacks of secondary research are:

Inaccurate . You don’t know how the data is retrieved, whether it is accurate or not. For example, a data provider might use an unrepresentative sample and therefore be biased if you use it to conclude about the population.

Expired . More lag time between data collection and data publication. Thus, the data may no longer be relevant to current conditions. The data provider does not update it regularly, so data is unavailable for several years.

Less relevant. Secondary data is to meet the needs of the provider, not for you. Thus, they may be less relevant to answering your research hypotheses.

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What is Secondary Research?
Secondary research is a research method that uses data that was collected by someone else. In other words, whenever you conduct research using data that already exists, you are conducting secondary research. On the other hand, any type of research that you undertake yourself is called primary research. Example: Secondary research.
Secondary Data: Advantages, Disadvantages, Sources, Types
There are two types of secondary data, based on the data source: Internal sources of data: information gathered within the researcher's company or organization (examples - a database with customer details, sales reports, marketing analysis, your emails, your social media profiles, etc).; External sources of data: the data collected outside the organization (i.e. government statistics, mass ...
Secondary Research Advantages, Limitations, and Sources
Compared to primary research, the collection of secondary data can be faster and cheaper to obtain, depending on the sources you use. Secondary data can come from internal or external sources. Internal sources of secondary data include ready-to-use data or data that requires further processing available in internal management support systems ...
Secondary Data: sources, advantages and disadvantages.
Despite the many advantages associated with the use of secondary data, there are some. disadvantages: Inappropriateness of the data. Data collected by a researcher (primary data) are. collected ...
Secondary Data
This includes assessing the quality, reliability, and validity of the data sources. Advantages of Secondary Data. There are several advantages to using secondary data in research, including: Time-saving: Collecting primary data can be time-consuming and expensive. Secondary data can be accessed quickly and easily, which can save researchers ...
Secondary Data: Analysis, Benefits, Importance, and Sources
Here are some advantages and disadvantages of secondary data analysis as compared to primary research. Advantages of secondary research Saving time and effort. Collecting secondary data for research is much faster and easier than primary data collection. This allows researchers to save time by going straight to the analysis process.
What is Secondary Data? [Examples, Sources & Advantages]
5. Advantages of secondary data. Secondary data is suitable for any number of analytics activities. The only limitation is a dataset's format, structure, and whether or not it relates to the topic or problem at hand. When analyzing secondary data, the process has some minor differences, mainly in the preparation phase.
Secondary Data Analysis: Using existing data to answer new questions
Introduction. Secondary data analysis is a valuable research approach that can be used to advance knowledge across many disciplines through the use of quantitative, qualitative, or mixed methods data to answer new research questions (Polit & Beck, 2021).This research method dates to the 1960s and involves the utilization of existing or primary data, originally collected for a variety, diverse ...
PDF An Introduction to Secondary Data Analysis
Secondary analysis of qualitative data is a topic unto itself and is not discussed in this volume. The interested reader is referred to references such as James and Sorenson (2000) and Heaton (2004). Advantages and Disadvantages of Secondary Data Analysis. The choice of primary or secondary data need not be an either/or ques-tion.
Secondary Analysis Research
Secondary analysis of data collected by another researcher for a different purpose, or SDA, is increasing in the medical and social sciences. This is not surprising, given the immense body of health care-related research performed worldwide and the potential beneficial clinical implications of the timely expansion of primary research (Johnston, 2014; Tripathy, 2013).
secondary research advantages and disadvantages
5. Provides historical data. 6. Useful for comparative analysis. 1. Cost-effective. One of the most notable advantages of secondary research is its cost-effectiveness. Since secondary research relies on existing data, there is no need to allocate funds for primary data collection.
Secondary Research: Definition, Methods & Examples
So, rightly secondary research is also termed " desk research ", as data can be retrieved from sitting behind a desk. The following are popularly used secondary research methods and examples: 1. Data Available on The Internet. One of the most popular ways to collect secondary data is the internet.
The strengths and limitations of secondary data
Strengths of using secondary data in social research. There is a lot of it! It is the richest vein of information available to researchers in many topic areas. Also, some large data sets might not exist if it wasn't for the government collecting data. Sometimes documents and official statistics might be the only means of researching the past.
Secondary Research: Definition, Methods & Examples
Disadvantages of secondary research. The disadvantages of secondary research are worth considering in advance of conducting research: Secondary research data can be out of date - Secondary sources can be updated regularly, but if you're exploring the data between two updates, the data can be out of date. Researchers will need to consider ...
Secondary Data In Research Methodology (With Examples)
In this article, we define what secondary data in research methodology is, explain the differences between primary and secondary data, list secondary data research methods, provide examples of secondary research, offer a step-by-step guide detailing how to use secondary data in research and discuss the advantages and disadvantages of using it.
Secondary Qualitative Research Methodology Using Online Data within the
The main three disadvantages related to the data are the following: (1) data fitness, (2) data quality, and (3) limited knowledge of data collection procedure. ... Due to the advantages of secondary data analysis particularly given COVID-19 restrictions supported by our ambition to obtain narratives from different parts of the world, publicly ...
Advantages of Secondary Research
Advantages of Secondary Research. The key advantage of secondary research is that data is readily available in most cases, especially from internet sources. Secondary research sources such as online libraries, academic databases, journals, e-books, online articles, and government repositories can be accessed to collect data on any given topic.
Conducting secondary analysis of qualitative data: Should we, can we
SDA involves investigations where data collected for a previous study is analyzed - either by the same researcher(s) or different researcher(s) - to explore new questions or use different analysis strategies that were not a part of the primary analysis (Szabo and Strang, 1997).For research involving quantitative data, SDA, and the process of sharing data for the purpose of SDA, has become ...
Secondary Data Analysis
Secondary data analysis is the process of analyzing data collected by others. This process is important because it saves time and prevents unnecessary duplication of research. However, since the ...
Secondary Research
Secondary research. Secondary research uses research and data that has already been carried out. It is sometimes referred to as desk research. It is a good starting point for any type of research as it enables you to analyse what research has already been undertaken and identify any gaps. You may only need to carry out secondary research for ...
The Market Researcher's Toolbox: Primary vs Secondary Research
Primary research may have a narrow focus and limited generalizability compared to secondary research. Advantages and Disadvantages of Secondary Research. On the other hand, secondary research offers its own set of advantages: It is typically more cost-effective than primary research, as data is readily available from existing sources.
12 Pros and Cons of Secondary Research
Pros Of Secondary Research. 1. Accessibility. A few years ago when you needed to collect some data then going to libraries or particular organizations was a must. And it was even impossible to gather such data by the public. The Internet has played a great role in accessing the data so easily in a single click.
Dissertations 4: Methodology: Methods
Advantages: •Data collected is first hand and accurate. •Data collected can be controlled. No dilution of data. •Research method can be customized to suit personal requirements and needs of the research. Advantages: •Information is readily available •Less expensive and less time-consuming •Quicker to conduct . Disadvantages:
Primary Research
Primary research is any research that you conduct yourself. It can be as simple as a 2-question survey, or as in-depth as a years-long longitudinal study. The only key is that data must be collected firsthand by you. Primary research is often used to supplement or strengthen existing secondary research.
Secondary Research: Meaning, Sources, Advantages, Disadvantages
Advantages of secondary research . Advantages of secondary research are: Easy, cheap, and fast. You don't have to be involved in developing complicated data collection methods. You also don't have to run surveys or interviews to collect data. You just sit at the table and look it up on the internet. More varied. You can collect data from a ...

Secondary Data: Advantages, Disadvantages, Sources, Types

What is secondary data? Definition and meaning.

Advantages And Disadvantages Of Secondary Data

Types Of Secondary Data

Examples And Sources Of Secondary Data

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Secondary Research Advantages, Limitations, and Sources

Advantages of Secondary Research

Limitations of Secondary Research

Lack of relevance

Lack of Accuracy

Criteria for Evaluating Secondary Research Data

Secondary Research Data Sources

Published Materials

External Databases

Syndicated Services

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Secondary Data: sources, advantages and disadvantages.

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Purpose of Secondary Data

When to use Secondary Data

Characteristics of Secondary Data

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2. What’s the difference between primary, secondary, and third-party data?

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3. What are some examples of secondary data?

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