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• What is Secondary Research? | Definition, Types, & Examples

What is Secondary Research? | Definition, Types, & Examples

Published on January 20, 2023 by Tegan George . Revised on January 12, 2024.

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 .

Secondary research can be qualitative or quantitative in nature. It often uses data gathered from published peer-reviewed papers, meta-analyses, or government or private sector databases and datasets.

Table of contents

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

Secondary research is a very common research method, used in lieu of collecting your own primary data. It is often used in research designs or as a way to start your research process if you plan to conduct primary research later on.

Since it is often inexpensive or free to access, secondary research is a low-stakes way to determine if further primary research is needed, as gaps in secondary research are a strong indication that primary research is necessary. For this reason, while secondary research can theoretically be exploratory or explanatory in nature, it is usually explanatory: aiming to explain the causes and consequences of a well-defined problem.

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

Statistical analysis

Literature reviews, case studies, content analysis.

There is ample data available online from a variety of sources, often in the form of datasets. These datasets are often open-source or downloadable at a low cost, and are ideal for conducting statistical analyses such as hypothesis testing or regression analysis .

Credible sources for existing data include:

• The government
• Government agencies
• Non-governmental organizations
• Educational institutions
• Businesses or consultancies
• Libraries or archives
• Newspapers, academic journals, or magazines

A literature review is a survey of preexisting scholarly sources on your topic. It provides an overview of current knowledge, allowing you to identify relevant themes, debates, and gaps in the research you analyze. You can later apply these to your own work, or use them as a jumping-off point to conduct primary research of your own.

Structured much like a regular academic paper (with a clear introduction, body, and conclusion), a literature review is a great way to evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

A case study is a detailed study of a specific subject. It is usually qualitative in nature and can focus on  a person, group, place, event, organization, or phenomenon. A case study is a great way to utilize existing research to gain concrete, contextual, and in-depth knowledge about your real-world subject.

You can choose to focus on just one complex case, exploring a single subject in great detail, or examine multiple cases if you’d prefer to compare different aspects of your topic. Preexisting interviews , observational studies , or other sources of primary data make for great case studies.

Content analysis is a research method that studies patterns in recorded communication by utilizing existing texts. It can be either quantitative or qualitative in nature, depending on whether you choose to analyze countable or measurable patterns, or more interpretive ones. Content analysis is popular in communication studies, but it is also widely used in historical analysis, anthropology, and psychology to make more semantic qualitative inferences.

Secondary research is a broad research approach that can be pursued any way you’d like. Here are a few examples of different ways you can use secondary research to explore your research topic .

Secondary research is a very common research approach, but has distinct advantages and disadvantages.

Advantages of secondary research

Advantages include:

• Secondary data is very easy to source and readily available .
• It is also often free or accessible through your educational institution’s library or network, making it much cheaper to conduct than primary research .
• As you are relying on research that already exists, conducting secondary research is much less time consuming than primary research. Since your timeline is so much shorter, your research can be ready to publish sooner.
• Using data from others allows you to show reproducibility and replicability , bolstering prior research and situating your own work within your field.

Disadvantages of secondary research

Disadvantages include:

• Ease of access does not signify credibility . It’s important to be aware that secondary research is not always reliable , and can often be out of date. It’s critical to analyze any data you’re thinking of using prior to getting started, using a method like the CRAAP test .
• Secondary research often relies on primary research already conducted. If this original research is biased in any way, those research biases could creep into the secondary results.

Many researchers using the same secondary research to form similar conclusions can also take away from the uniqueness and reliability of your research. Many datasets become “kitchen-sink” models, where too many variables are added in an attempt to draw increasingly niche conclusions from overused data . Data cleansing may be necessary to test the quality of the research.

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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.

• Normal distribution
• 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

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

Sources in this article

We strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below.

George, T. (2024, January 12). What is Secondary Research? | Definition, Types, & Examples. Scribbr. Retrieved June 24, 2024, from https://www.scribbr.com/methodology/secondary-research/

Largan, C., & Morris, T. M. (2019). Qualitative Secondary Research: A Step-By-Step Guide (1st ed.). SAGE Publications Ltd.

Peloquin, D., DiMaio, M., Bierer, B., & Barnes, M. (2020). Disruptive and avoidable: GDPR challenges to secondary research uses of data. European Journal of Human Genetics , 28 (6), 697–705. https://doi.org/10.1038/s41431-020-0596-x

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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.

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Researcher, Academic Writer, Web developer

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Home Market Research

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.

LEARN ABOUT: Research Process Steps

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.

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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.

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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A Guide To Secondary Data Analysis

What is secondary data analysis? How do you carry it out? Find out in this post.  

Historically, the only way data analysts could obtain data was to collect it themselves. This type of data is often referred to as primary data and is still a vital resource for data analysts.   

However, technological advances over the last few decades mean that much past data is now readily available online for data analysts and researchers to access and utilize. This type of data—known as secondary data—is driving a revolution in data analytics and data science.

Primary and secondary data share many characteristics. However, there are some fundamental differences in how you prepare and analyze secondary data. This post explores the unique aspects of secondary data analysis. We’ll briefly review what secondary data is before outlining how to source, collect and validate them. We’ll cover:

• What is secondary data analysis?
• How to carry out secondary data analysis (5 steps)
• Summary and further reading

Ready for a crash course in secondary data analysis? Let’s go!

1. What is secondary data analysis?

Secondary data analysis uses data collected by somebody else. This contrasts with primary data analysis, which involves a researcher collecting predefined data to answer a specific question. Secondary data analysis has numerous benefits, not least that it is a time and cost-effective way of obtaining data without doing the research yourself.

It’s worth noting here that secondary data may be primary data for the original researcher. It only becomes secondary data when it’s repurposed for a new task. As a result, a dataset can simultaneously be a primary data source for one researcher and a secondary data source for another. So don’t panic if you get confused! We explain exactly what secondary data is in this guide . 

In reality, the statistical techniques used to carry out secondary data analysis are no different from those used to analyze other kinds of data. The main differences lie in collection and preparation. Once the data have been reviewed and prepared, the analytics process continues more or less as it usually does. For a recap on what the data analysis process involves, read this post . 

In the following sections, we’ll focus specifically on the preparation of secondary data for analysis. Where appropriate, we’ll refer to primary data analysis for comparison. 

2. How to carry out secondary data analysis

Step 1: define a research topic.

The first step in any data analytics project is defining your goal. This is true regardless of the data you’re working with, or the type of analysis you want to carry out. In data analytics lingo, this typically involves defining:

• A statement of purpose
• Research design

Defining a statement of purpose and a research approach are both fundamental building blocks for any project. However, for secondary data analysis, the process of defining these differs slightly. Let’s find out how.

Step 2: Establish your statement of purpose

Before beginning any data analytics project, you should always have a clearly defined intent. This is called a ‘statement of purpose.’ A healthcare analyst’s statement of purpose, for example, might be: ‘Reduce admissions for mental health issues relating to Covid-19′. The more specific the statement of purpose, the easier it is to determine which data to collect, analyze, and draw insights from.

A statement of purpose is helpful for both primary and secondary data analysis. It’s especially relevant for secondary data analysis, though. This is because there are vast amounts of secondary data available. Having a clear direction will keep you focused on the task at hand, saving you from becoming overwhelmed. Being selective with your data sources is key.

Step 3: Design your research process

After defining your statement of purpose, the next step is to design the research process. For primary data, this involves determining the types of data you want to collect (e.g. quantitative, qualitative, or both ) and a methodology for gathering them.

For secondary data analysis, however, your research process will more likely be a step-by-step guide outlining the types of data you require and a list of potential sources for gathering them. It may also include (realistic) expectations of the output of the final analysis. This should be based on a preliminary review of the data sources and their quality.

Once you have both your statement of purpose and research design, you’re in a far better position to narrow down potential sources of secondary data. You can then start with the next step of the process: data collection.

Step 4: Locate and collect your secondary data

Collecting primary data involves devising and executing a complex strategy that can be very time-consuming to manage. The data you collect, though, will be highly relevant to your research problem.

Secondary data collection, meanwhile, avoids the complexity of defining a research methodology. However, it comes with additional challenges. One of these is identifying where to find the data. This is no small task because there are a great many repositories of secondary data available. Your job, then, is to narrow down potential sources. As already mentioned, it’s necessary to be selective, or else you risk becoming overloaded.  

Some popular sources of secondary data include:  

• Government statistics , e.g. demographic data, censuses, or surveys, collected by government agencies/departments (like the US Bureau of Labor Statistics).
• Technical reports summarizing completed or ongoing research from educational or public institutions (colleges or government).
• Scientific journals that outline research methodologies and data analysis by experts in fields like the sciences, medicine, etc.
• Literature reviews of research articles, books, and reports, for a given area of study (once again, carried out by experts in the field).
• Trade/industry publications , e.g. articles and data shared in trade publications, covering topics relating to specific industry sectors, such as tech or manufacturing.
• Online resources: Repositories, databases, and other reference libraries with public or paid access to secondary data sources.

Once you’ve identified appropriate sources, you can go about collecting the necessary data. This may involve contacting other researchers, paying a fee to an organization in exchange for a dataset, or simply downloading a dataset for free online .

Step 5: Evaluate your secondary data

Secondary data is usually well-structured, so you might assume that once you have your hands on a dataset, you’re ready to dive in with a detailed analysis. Unfortunately, that’s not the case! 

First, you must carry out a careful review of the data. Why? To ensure that they’re appropriate for your needs. This involves two main tasks:

Evaluating the secondary dataset’s relevance

• Assessing its broader credibility

Both these tasks require critical thinking skills. However, they aren’t heavily technical. This means anybody can learn to carry them out.

Let’s now take a look at each in a bit more detail.  

The main point of evaluating a secondary dataset is to see if it is suitable for your needs. This involves asking some probing questions about the data, including:

What was the data’s original purpose?

Understanding why the data were originally collected will tell you a lot about their suitability for your current project. For instance, was the project carried out by a government agency or a private company for marketing purposes? The answer may provide useful information about the population sample, the data demographics, and even the wording of specific survey questions. All this can help you determine if the data are right for you, or if they are biased in any way.

When and where were the data collected?

Over time, populations and demographics change. Identifying when the data were first collected can provide invaluable insights. For instance, a dataset that initially seems suited to your needs may be out of date.

On the flip side, you might want past data so you can draw a comparison with a present dataset. In this case, you’ll need to ensure the data were collected during the appropriate time frame. It’s worth mentioning that secondary data are the sole source of past data. You cannot collect historical data using primary data collection techniques.

Similarly, you should ask where the data were collected. Do they represent the geographical region you require? Does geography even have an impact on the problem you are trying to solve?

What data were collected and how?

A final report for past data analytics is great for summarizing key characteristics or findings. However, if you’re planning to use those data for a new project, you’ll need the original documentation. At the very least, this should include access to the raw data and an outline of the methodology used to gather them. This can be helpful for many reasons. For instance, you may find raw data that wasn’t relevant to the original analysis, but which might benefit your current task.

What questions were participants asked?

We’ve already touched on this, but the wording of survey questions—especially for qualitative datasets—is significant. Questions may deliberately be phrased to preclude certain answers. A question’s context may also impact the findings in a way that’s not immediately obvious. Understanding these issues will shape how you perceive the data.  

What is the form/shape/structure of the data?

Finally, to practical issues. Is the structure of the data suitable for your needs? Is it compatible with other sources or with your preferred analytics approach? This is purely a structural issue. For instance, if a dataset of people’s ages is saved as numerical rather than continuous variables, this could potentially impact your analysis. In general, reviewing a dataset’s structure helps better understand how they are categorized, allowing you to account for any discrepancies. You may also need to tidy the data to ensure they are consistent with any other sources you’re using.  

This is just a sample of the types of questions you need to consider when reviewing a secondary data source. The answers will have a clear impact on whether the dataset—no matter how well presented or structured it seems—is suitable for your needs.

Assessing secondary data’s credibility

After identifying a potentially suitable dataset, you must double-check the credibility of the data. Namely, are the data accurate and unbiased? To figure this out, here are some key questions you might want to include:

What are the credentials of those who carried out the original research?

Do you have access to the details of the original researchers? What are their credentials? Where did they study? Are they an expert in the field or a newcomer? Data collection by an undergraduate student, for example, may not be as rigorous as that of a seasoned professor.  

And did the original researcher work for a reputable organization? What other affiliations do they have? For instance, if a researcher who works for a tobacco company gathers data on the effects of vaping, this represents an obvious conflict of interest! Questions like this help determine how thorough or qualified the researchers are and if they have any potential biases.

Do you have access to the full methodology?

Does the dataset include a clear methodology, explaining in detail how the data were collected? This should be more than a simple overview; it must be a clear breakdown of the process, including justifications for the approach taken. This allows you to determine if the methodology was sound. If you find flaws (or no methodology at all) it throws the quality of the data into question.  

How consistent are the data with other sources?

Do the secondary data match with any similar findings? If not, that doesn’t necessarily mean the data are wrong, but it does warrant closer inspection. Perhaps the collection methodology differed between sources, or maybe the data were analyzed using different statistical techniques. Or perhaps unaccounted-for outliers are skewing the analysis. Identifying all these potential problems is essential. A flawed or biased dataset can still be useful but only if you know where its shortcomings lie.

Have the data been published in any credible research journals?

Finally, have the data been used in well-known studies or published in any journals? If so, how reputable are the journals? In general, you can judge a dataset’s quality based on where it has been published. If in doubt, check out the publication in question on the Directory of Open Access Journals . The directory has a rigorous vetting process, only permitting journals of the highest quality. Meanwhile, if you found the data via a blurry image on social media without cited sources, then you can justifiably question its quality!  

Again, these are just a few of the questions you might ask when determining the quality of a secondary dataset. Consider them as scaffolding for cultivating a critical thinking mindset; a necessary trait for any data analyst!

Presuming your secondary data holds up to scrutiny, you should be ready to carry out your detailed statistical analysis. As we explained at the beginning of this post, the analytical techniques used for secondary data analysis are no different than those for any other kind of data. Rather than go into detail here, check out the different types of data analysis in this post.

3. Secondary data analysis: Key takeaways

In this post, we’ve looked at the nuances of secondary data analysis, including how to source, collect and review secondary data. As discussed, much of the process is the same as it is for primary data analysis. The main difference lies in how secondary data are prepared.

Carrying out a meaningful secondary data analysis involves spending time and effort exploring, collecting, and reviewing the original data. This will help you determine whether the data are suitable for your needs and if they are of good quality.

Why not get to know more about what data analytics involves with this free, five-day introductory data analytics short course ? And, for more data insights, check out these posts:

• Discrete vs continuous data variables: What’s the difference?
• What are the four levels of measurement? Nominal, ordinal, interval, and ratio data explained
• What are the best tools for data mining?

What is secondary research?

Last updated

7 February 2023

Reviewed by

Cathy Heath

In this guide, we explain in detail what secondary research is, including the difference between this research method and primary research, the different sources for secondary research, and how you can benefit from this research method.

Analyze your secondary research

Bring your secondary research together inside Dovetail, tag PDFs, and uncover actionable insights

• Overview of secondary research

Secondary research is a method by which the researcher finds existing data, filters it to meet the context of their research question, analyzes it, and then summarizes it to come up with valid research conclusions.

This research method involves searching for information, often via the internet, using keywords or search terms relevant to the research question. The goal is to find data from internal and external sources that are up-to-date and authoritative, and that fully answer the question.

Secondary research reviews existing research and looks for patterns, trends, and insights, which helps determine what further research, if any, is needed.

• Secondary research methods

Secondary research is more economical than primary research, mainly because the methods for this type of research use existing data and do not require the data to be collected first-hand or by a third party that you have to pay.

Secondary research is referred to as ‘desk research’ or ‘desktop research,’ since the data can be retrieved from behind a desk instead of having to host a focus group and create the research from scratch.

Finding existing research is relatively easy since there are numerous accessible sources organizations can use to obtain the information they need. These  include:

The internet:  This data is either free or behind a paywall. Yet, while there are plenty of sites on the internet with information that can be used, businesses need to be careful to collect information from trusted and authentic websites to ensure the data is accurate.

Government agencies: Government agencies are typically known to provide valuable, trustworthy information that companies can use for their research.

The public library: This establishment holds paper-based and online sources of reliable information, including business databases, magazines, newspapers, and government publications. Be mindful of any copyright restrictions that may apply when using these sources.

Commercial information: This source provides first-hand information on politics, demographics, and economic developments through information aggregators, newspapers, magazines, radio, blogs, podcasts, and journals. This information may be free or behind a paywall.

Educational and scientific facilities: Universities, colleges, and specialized research facilities carry out significant amounts of research. As a result, they have data that may be available to the public and businesses for use.

• Key differences between primary research and secondary research

Both primary and secondary research methods provide researchers with vital, complementary information, despite some major differences between the two approaches.

Primary research involves gathering first-hand information by directly working with the target market, users, and interviewees. Researchers ask questions directly using surveys , interviews, and focus groups.

Through the primary research method, researchers obtain targeted responses and accurate results directly related to their overall research goals.

Secondary research uses existing data, such as published reports, that have already been completed through earlier primary and secondary research. Researchers can use this existing data to support their research goals and preliminary research findings.

Other notable differences between primary and secondary research  include:

Relevance: Primary research uses raw data relevant to the investigation's goals. Secondary research may contain irrelevant data or may not neatly fit the parameters of the researcher's goals.

Time: Primary research takes a lot of time. Secondary research can be done relatively quickly.

Researcher bias: Primary research can be subject to researcher bias.

Cost: Primary research can be expensive. Secondary research can be more affordable because the data is often free. However, valuable data is often behind a paywall. The piece of secondary research you want may not exist or be very expensive, so you may have to turn to primary research to fill the information gap.

• When to conduct secondary research

Both primary and secondary research have roles to play in providing a holistic and accurate understanding of a topic. Generally, secondary research is done at the beginning of the research phase, especially if the topic is new.

Secondary research can provide context and critical background information to understand the issue at hand and identify any gaps, that could then be filled by primary research.

• How to conduct secondary research

Researchers usually follow several steps for secondary research.

1. Identify and define the research topic

Before starting either of these research methods, you first need to determine the following:

Topic to be researched

Purpose of this research

For instance, you may want to explore a question, determine why something happened, or confirm whether an issue is true.

At this stage, you also need to consider what search terms or keywords might be the most effective for this topic. You could do this by looking at what synonyms exist for your topic, the use of industry terms and acronyms, as well as the balance between statistical or quantitative data and contextual data to support your research topic.

It’s also essential to define what you don’t want to cover in your secondary research process. This might be choosing only to use recent information or only focusing on research based on a particular country or type of consumer. From there, once you know what you want to know and why you can decide whether you need to use both primary and secondary research to answer your questions.

2. Find research and existing data sources

Once you have determined your research topic , select the information sources that will provide you with the most appropriate and relevant data for your research. If you need secondary research, you want to determine where this information can likely be found, for example:

Trade associations

Government sources

Create a list of the relevant data sources , and other organizations or people that can help you find what you need.

3. Begin searching and collecting the existing data

Once you have narrowed down your sources, you will start gathering this information and putting it into an organized system. This often involves:

Checking the credibility of the source

Setting up meetings with research teams

Signing up for accounts to access certain websites or journals

One search result on the internet often leads to other pieces of helpful information, known as ‘pearl gathering’ or ‘pearl harvesting.’ This is usually a serendipitous activity, which can lead to valuable nuggets of information you may not have been aware of or considered.

4. Combine the data and compare the results

Once you have gathered all the data, start going through it by carefully examining all the information and comparing it to ensure the data is usable and that it isn’t duplicated or corrupted. Contradictory information is useful—just make sure you note the contradiction and the context. Be mindful of copyright and plagiarism when using secondary research and always cite your sources.

Once you have assessed everything, you will begin to look at what this information tells you by checking out the trends and comparing the different datasets. You will also investigate what this information means for your research, whether it helps your overall goal, and any gaps or deficiencies.

5. Analyze your data and explore further

In the final stage of conducting secondary research, you will analyze the data you have gathered and determine if it answers the questions you had before you started researching. Check that you understand the information, whether it fills in all your gaps, and whether it provides you with other insights or actions you should take next.

If you still need further data, repeat these steps to find additional information that can help you explore your topic more deeply. You may also need to supplement what you find with primary research to ensure that your data is complete, accurate, transparent, and credible.

• The advantages of secondary research

There are numerous advantages to performing secondary research. Some key benefits are:

Quicker than primary research: Because the data is already available, you can usually find the information you need fairly quickly. Not only will secondary research help you research faster, but you will also start optimizing the data more quickly.

Plenty of available data: There are countless sources for you to choose from, making research more accessible. This data may be already compiled and arranged, such as statistical information,  so you can quickly make use of it.

Lower costs:  Since you will not have to carry out the research from scratch, secondary research tends to be much more affordable than primary research.

Opens doors to further research:  Existing research usually identifies whether more research needs to be done. This could mean follow-up surveys or telephone interviews with subject matter experts (SME) to add value to your own research.

• The disadvantages of secondary research

While there are plenty of benefits to secondary research are plenty, there are some issues you should be aware of. These include:

Credibility issues: It is important to verify the sources used. Some information may be biased and not reflect or hide, relevant issues or challenges. It could also be inaccurate.

No recent information:  Even if data may seem accurate, it may not be up to date, so the information you gather may no longer be correct. Outdated research can distort your overall findings.

Poor quality: Because secondary research tends to make conclusions from primary research data, the success of secondary research will depend on the quality and context of the research that has already been completed. If the research you are using is of poor quality, this will bring down the quality of your own findings.

Research doesn’t exist or is not easily accessible, or is expensive: Sometimes the information you need is confidential or proprietary, such as sales or earnings figures. Many information-based businesses attach value to the information they hold or publish, so the costs to access this information can be prohibitive.

Should you complete secondary research or primary research first?

Due to the costs and time involved in primary research, it may be more beneficial to conduct secondary market research first. This will save you time and provide a picture of what issues you may come across in your research. This allows you to focus on using more expensive primary research to get the specific answers you want.

What should you ask yourself before using secondary research data?

Check the date of the research to make sure it is still relevant. Also, determine the data source so you can assess how credible and trustworthy it is likely to be. For example, data from known brands, professional organizations, and even government agencies are usually excellent sources to use in your secondary research, as it tends to be trustworthy.

Be careful when using some websites and personal blogs as they may be based on opinions rather than facts. However, these sources can be useful for determining sentiment about a product or service, and help direct any primary research.

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• What is Secondary Data? + [Examples, Sources, & Analysis]

• Data Collection

Aside from consulting the primary origin or source, data can also be collected through a third party, a process common with secondary data. It takes advantage of the data collected from previous research and uses it to carry out new research.

Secondary data is one of the two main types of data, where the second type is the primary data. These 2 data types are very useful in research and statistics, but for the sake of this article, we will be restricting our scope to secondary data.

We will study secondary data, its examples, sources, and methods of analysis.

What is Secondary Data?  

Secondary data is the data that has already been collected through primary sources and made readily available for researchers to use for their own research. It is a type of data that has already been collected in the past.

A researcher may have collected the data for a particular project, then made it available to be used by another researcher. The data may also have been collected for general use with no specific research purpose like in the case of the national census.

Data classified as secondary for particular research may be said to be primary for another research. This is the case when data is being reused, making it primary data for the first research and secondary data for the second research it is being used for.

Sources of Secondary Data

Sources of secondary data include books, personal sources, journals, newspapers, websitess, government records etc. Secondary data are known to be readily available compared to that of primary data. It requires very little research and needs for manpower to use these sources.

With the advent of electronic media and the internet, secondary data sources have become more easily accessible. Some of these sources are highlighted below.

Books are one of the most traditional ways of collecting data. Today, there are books available for all topics you can think of.  When carrying out research, all you have to do is look for a book on the topic being researched, then select from the available repository of books in that area. Books, when carefully chosen are an authentic source of authentic data and can be useful in preparing a literature review.

• Published Sources

There are a variety of published sources available for different research topics. The authenticity of the data generated from these sources depends majorly on the writer and publishing company. 

Published sources may be printed or electronic as the case may be. They may be paid or free depending on the writer and publishing company’s decision.

• Unpublished Personal Sources

This may not be readily available and easily accessible compared to the published sources. They only become accessible if the researcher shares with another researcher who is not allowed to share it with a third party.

For example, the product management team of an organization may need data on customer feedback to assess what customers think about their product and improvement suggestions. They will need to collect the data from the customer service department, which primarily collected the data to improve customer service.

Journals are gradually becoming more important than books these days when data collection is concerned. This is because journals are updated regularly with new publications on a periodic basis, therefore giving to date information.

Also, journals are usually more specific when it comes to research. For example, we can have a journal on, “Secondary data collection for quantitative data ” while a book will simply be titled, “Secondary data collection”.

In most cases, the information passed through a newspaper is usually very reliable. Hence, making it one of the most authentic sources of collecting secondary data.

The kind of data commonly shared in newspapers is usually more political, economic, and educational than scientific. Therefore, newspapers may not be the best source for scientific data collection.

The information shared on websites is mostly not regulated and as such may not be trusted compared to other sources. However, there are some regulated websites that only share authentic data and can be trusted by researchers.

Most of these websites are usually government websites or private organizations that are paid, data collectors.

Blogs are one of the most common online sources for data and may even be less authentic than websites. These days, practically everyone owns a blog, and a lot of people use these blogs to drive traffic to their website or make money through paid ads.

Therefore, they cannot always be trusted. For example, a blogger may write good things about a product because he or she was paid to do so by the manufacturer even though these things are not true.

They are personal records and as such rarely used for data collection by researchers. Also, diaries are usually personal, except for these days when people now share public diaries containing specific events in their life.

A common example of this is Anne Frank’s diary which contained an accurate record of the Nazi wars.

• Government Records

Government records are a very important and authentic source of secondary data. They contain information useful in marketing, management, humanities, and social science research.

Some of these records include; census data, health records, education institute records, etc. They are usually collected to aid proper planning, allocation of funds, and prioritizing of projects.

Podcasts are gradually becoming very common these days, and a lot of people listen to them as an alternative to radio. They are more or less like online radio stations and are generating increasing popularity.

Information is usually shared during podcasts, and listeners can use it as a source of data collection. 

Some other sources of data collection include:

• Radio stations
• Public sector records.

What are the Secondary Data Collection Tools?

Popular tools used to collect secondary data include; bots, devices, libraries, etc. In order to ease the data collection process from the sources of secondary data highlighted above, researchers use these important tools which are explained below.

There are a lot of data online and it may be difficult for researchers to browse through all these data and find what they are actually looking for. In order to ease this process of data collection, programmers have created bots to do an automatic web scraping for relevant data.

These bots are “ software robots ” programmed to perform some task for the researcher. It is common for businesses to use bots to pull data from forums and social media for sentiment and competitive analysis.

• Internet-Enabled Devices

This could be a mobile phone, PC, or tablet that has access to an internet connection. They are used to access journals, books, blogs, etc. to collect secondary data.

This is a traditional secondary data collection tool for researchers. The library contains relevant materials for virtually all the research areas you can think of, and it is accessible to everyone.

A researcher might decide to sit in the library for some time to collect secondary data or borrow the materials for some time and return when done collecting the required data.

Radio stations are one of the secondary sources of data collection, and one needs radio to access them. The advent of technology has even made it possible to listen to the radio on mobile phones, deeming it unnecessary to get a radio.

Secondary Data Analysis  

Secondary data analysis is the process of analyzing data collected from another researcher who primarily collected this data for another purpose. Researchers leverage secondary data to save time and resources that would have been spent on primary data collection.

The secondary data analysis process can be carried out 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, while the qualitative method uses words to provide in-depth information about data.

How to Analyse Secondary 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 for analysis, you need to know your statement of purpose. That is, a clear understanding of why you are collecting the data—the ultimate aim of the research work and how this data will help achieve it.

This will help direct your path towards collecting the right data, and choosing the best data source and method of analysis.

• Research Design

This is a written-down plan on how the research activities will be carried out. It describes the kind of data to be collected, the sources of data collection, method of data collection, tools, and even method of analysis.

A research design may also contain a timestamp of when each of these activities will be carried out. Therefore, serving as a guide for the secondary data analysis.

After identifying the purpose of the research, the researcher should design a research process that will guide the data analysis process.

• Developing the Research Questions

It is not enough to just know the research purpose, you need to develop research questions that will help in better identifying Secondary data. This is because they are usually a pool of data to choose from, and asking the right questions will assist in collecting authentic data.

For example, a researcher trying to collect data about the best fish feeds to enable fast growth in fishes will have to ask questions like, What kind of fish is considered? Is the data meant to be quantitative or qualitative? What is the content of the fish feed? The growth rate in fishes after feeding on it, and so on.

• Identifying Secondary Data

After developing the research questions, researchers use them as a guide to identifying relevant data from the data repository. For example, if the kind of data to be collected is qualitative, a researcher can filter out qualitative data.

The suitable secondary data will be the one that correctly answers the questions highlighted above. When looking for the solutions to a linear programming problem, for instance, the solutions will be numbers that satisfy both the objective and the constraints.

Any answer that doesn’t satisfy both, is not a solution.

• Evaluating Secondary Data

This stage is what many classify as the real data analysis stage because it is the point where analysis is actually performed. However, the stages highlighted above are a part of the data analysis process, because they influence how the analysis is performed.

Once a dataset that appears viable in addressing the initial requirements discussed above is located, the next step in the process is the evaluation of the dataset to ensure the appropriateness for the research topic. The data is evaluated to ensure that it really addresses the statement of the problem and answers the research questions.

After which it will now be analyzed either using the quantitative method or the qualitative method depending on the type of data it is.

Advantages of Secondary Data

• Ease of Access

Most of the sources of secondary data are easily accessible to researchers. Most of these sources can be accessed online through a mobile device.  People who do not have access to the internet can also access them through print.

They are usually available in libraries, book stores, and can even be borrowed from other people.

• Inexpensive

Secondary data mostly require little to no cost for people to acquire them. Many books, journals, and magazines can be downloaded for free online.  Books can also be borrowed for free from public libraries by people who do not have access to the internet.

Researchers do not have to spend money on investigations, and very little is spent on acquiring books if any.

• Time-Saving

The time spent on collecting secondary data is usually very little compared to that of primary data. The only investigation necessary for secondary data collection is the process of sourcing for necessary data sources.

Therefore, cutting the time that would normally be spent on the investigation. This will save a significant amount of time for the researcher 

• Longitudinal and Comparative Studies

Secondary data makes it easy to carry out longitudinal studies without having to wait for a couple of years to draw conclusions. For example, you may want to compare the country’s population according to census 5 years ago, and now.

Rather than waiting for 5 years, the comparison can easily be made by collecting the census 5 years ago and now.

• Generating new insights

When re-evaluating data, especially through another person’s lens or point of view, new things are uncovered. There might be a thing that wasn’t discovered in the past by the primary data collector, that secondary data collection may reveal.

For example, when customers complain about difficulty using an app to the customer service team, they may decide to create a user guide teaching customers how to use it. However, when a product developer has access to this data, it may be uncovered that the issue came from and UI/UX design that needs to be worked on.

Disadvantages of Secondary Data  

• Data Quality:

The data collected through secondary sources may not be as authentic as when collected directly from the source. This is a very common disadvantage with online sources due to a lack of regulatory bodies to monitor the kind of content that is being shared.

Therefore, working with this kind of data may have negative effects on the research being carried out.

• Irrelevant Data:

Researchers spend so much time surfing through a pool of irrelevant data before finally getting the one they need. This is because the data was not collected mainly for the researcher.

In some cases, a researcher may not even find the exact data he or she needs, but have to settle for the next best alternative. 

• Exaggerated Data

Some data sources are known to exaggerate the information that is being shared. This bias may be some to maintain a good public image or due to a paid advert.

This is very common with many online blogs that even go a bead to share false information just to gain web traffic. For example, a FinTech startup may exaggerate the amount of money it has processed just to attract more customers.

A researcher gathering this data to investigate the total amount of money processed by FinTech startups in the US for the quarter may have to use this exaggerated data.

• Outdated Information

Some of the data sources are outdated and there are no new available data to replace the old ones. For example, the national census is not usually updated yearly.

Therefore, there have been changes in the country’s population since the last census. However, someone working with the country’s population will have to settle for the previously recorded figure even though it is outdated.

Secondary data has various uses in research, business, and statistics. Researchers choose secondary data for different reasons, with some of it being due to price, availability, or even needs of the research.

Although old, secondary data may be the only source of data in some cases. This may be due to the huge cost of performing research or due to its delegation to a particular body (e.g. national census). 

In short, secondary data has its shortcomings, which may affect the outcome of the research negatively and also some advantages over primary data. It all depends on the situation, the researcher in question, and the kind of research being carried out.

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Secondary Research Guide: Definition, Methods, Examples

Apr 3, 2024

8 min. read

The internet has vastly expanded our access to information, allowing us to learn almost anything about everything. But not all market research is created equal , and this secondary research guide explains why.

There are two key ways to do research. One is to test your own ideas, make your own observations, and collect your own data to derive conclusions. The other is to use secondary research — where someone else has done most of the heavy lifting for you. 

Here’s an overview of secondary research and the value it brings to data-driven businesses.

Secondary Research Definition: What Is Secondary Research?

Primary vs Secondary Market Research

What Are Secondary Research Methods?

Advantages of secondary research, disadvantages of secondary research, best practices for secondary research, how to conduct secondary research with meltwater.

Secondary research definition: The process of collecting information from existing sources and data that have already been analyzed by others.

Secondary research (aka desk research or complementary research ) provides a foundation to help you understand a topic, with the goal of building on existing knowledge. They often cover the same information as primary sources, but they add a layer of analysis and explanation to them.

Users can choose from several secondary research types and sources, including:

• Journal articles
• Research papers

With secondary sources, users can draw insights, detect trends , and validate findings to jumpstart their research efforts.

Primary vs. Secondary Market Research

We’ve touched a little on primary research , but it’s essential to understand exactly how primary and secondary research are unique.

Think of primary research as the “thing” itself, and secondary research as the analysis of the “thing,” like these primary and secondary research examples:

• An expert gives an interview (primary research) and a marketer uses that interview to write an article (secondary research).
• A company conducts a consumer satisfaction survey (primary research) and a business analyst uses the survey data to write a market trend report (secondary research).
• A marketing team launches a new advertising campaign across various platforms (primary research) and a marketing research firm, like Meltwater for market research , compiles the campaign performance data to benchmark against industry standards (secondary research).

In other words, primary sources make original contributions to a topic or issue, while secondary sources analyze, synthesize, or interpret primary sources.

Both are necessary when optimizing a business, gaining a competitive edge , improving marketing, or understanding consumer trends that may impact your business.

Secondary research methods focus on analyzing existing data rather than collecting primary data . Common examples of secondary research methods include:

• Literature review . Researchers analyze and synthesize existing literature (e.g., white papers, research papers, articles) to find knowledge gaps and build on current findings.
• Content analysis . Researchers review media sources and published content to find meaningful patterns and trends.
• AI-powered secondary research . Platforms like Meltwater for market research analyze vast amounts of complex data and use AI technologies like natural language processing and machine learning to turn data into contextual insights.

Researchers today have access to more secondary research companies and market research tools and technology than ever before, allowing them to streamline their efforts and improve their findings.

Want to see how Meltwater can complement your secondary market research efforts? Simply fill out the form at the bottom of this post, and we'll be in touch.

Conducting secondary research offers benefits in every job function and use case, from marketing to the C-suite. Here are a few advantages you can expect.

Cost and time efficiency

Using existing research saves you time and money compared to conducting primary research. Secondary data is readily available and easily accessible via libraries, free publications, or the Internet. This is particularly advantageous when you face time constraints or when a project requires a large amount of data and research.

Access to large datasets

Secondary data gives you access to larger data sets and sample sizes compared to what primary methods may produce. Larger sample sizes can improve the statistical power of the study and add more credibility to your findings.

Ability to analyze trends and patterns

Using larger sample sizes, researchers have more opportunities to find and analyze trends and patterns. The more data that supports a trend or pattern, the more trustworthy the trend becomes and the more useful for making decisions. 

Historical context

Using a combination of older and recent data allows researchers to gain historical context about patterns and trends. Learning what’s happened before can help decision-makers gain a better current understanding and improve how they approach a problem or project.

Basis for further research

Ideally, you’ll use secondary research to further other efforts . Secondary sources help to identify knowledge gaps, highlight areas for improvement, or conduct deeper investigations.

Tip: Learn how to use Meltwater as a research tool and how Meltwater uses AI.

Secondary research comes with a few drawbacks, though these aren’t necessarily deal breakers when deciding to use secondary sources.

Reliability concerns

Researchers don’t always know where the data comes from or how it’s collected, which can lead to reliability concerns. They don’t control the initial process, nor do they always know the original purpose for collecting the data, both of which can lead to skewed results.

Potential bias

The original data collectors may have a specific agenda when doing their primary research, which may lead to biased findings. Evaluating the credibility and integrity of secondary data sources can prove difficult.

Outdated information

Secondary sources may contain outdated information, especially when dealing with rapidly evolving trends or fields. Using outdated information can lead to inaccurate conclusions and widen knowledge gaps.

Limitations in customization

Relying on secondary data means being at the mercy of what’s already published. It doesn’t consider your specific use cases, which limits you as to how you can customize and use the data.

A lack of relevance

Secondary research rarely holds all the answers you need, at least from a single source. You typically need multiple secondary sources to piece together a narrative, and even then you might not find the specific information you need.

To make secondary market research your new best friend, you’ll need to think critically about its strengths and find ways to overcome its weaknesses. Let’s review some best practices to use secondary research to its fullest potential.

Identify credible sources for secondary research

To overcome the challenges of bias, accuracy, and reliability, choose secondary sources that have a demonstrated history of excellence . For example, an article published in a medical journal naturally has more credibility than a blog post on a little-known website.

Assess credibility based on peer reviews, author expertise, sampling techniques, publication reputation, and data collection methodologies. Cross-reference the data with other sources to gain a general consensus of truth.

The more credibility “factors” a source has, the more confidently you can rely on it. 

Evaluate the quality and relevance of secondary data

You can gauge the quality of the data by asking simple questions:

• How complete is the data? 
• How old is the data? 
• Is this data relevant to my needs?
• Does the data come from a known, trustworthy source?

It’s best to focus on data that aligns with your research objectives. Knowing the questions you want to answer and the outcomes you want to achieve ahead of time helps you focus only on data that offers meaningful insights.

Document your sources 

If you’re sharing secondary data with others, it’s essential to document your sources to gain others’ trust. They don’t have the benefit of being “in the trenches” with you during your research, and sharing your sources can add credibility to your findings and gain instant buy-in.

Secondary market research offers an efficient, cost-effective way to learn more about a topic or trend, providing a comprehensive understanding of the customer journey . Compared to primary research, users can gain broader insights, analyze trends and patterns, and gain a solid foundation for further exploration by using secondary sources.

Meltwater for market research speeds up the time to value in using secondary research with AI-powered insights, enhancing your understanding of the customer journey. Using natural language processing, machine learning, and trusted data science processes, Meltwater helps you find relevant data and automatically surfaces insights to help you understand its significance. Our solution identifies hidden connections between data points you might not know to look for and spells out what the data means, allowing you to make better decisions based on accurate conclusions. Learn more about Meltwater's power as a secondary research solution when you request a demo by filling out the form below:

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Finding Social Science Data for Research

What is secondary data.

• Getting Started
• Frequently Used Data
• Crime & Justice
• Economic & Finance
• International
• Labor/Employment
• Multi-Topic
• Qualitative Data
• Accessing Restricted Data
• Citing Data

Secondary data is data that a researcher has not collected or created themselves.  Secondary data can encompass an enormous range of highly original and extensive studies, including some of the largest and most careful collections of data.

Secondary data are usually easily accessible to researchers and individuals because they are mostly shared publicly. This, however, means that the data are usually general and not tailored specifically to meet the researcher's needs as primary data does.

 This guide is a very quick introduction to locating secondary data sources.

When would you reuse data?

There are many reasons why you may want to use existing data. Below are some examples of common reasons to reuse data: 

• You need data collected by another agency, such as the U.S. Census Bureau or the United Nations Statistics Division
• You want to supplement your own collected data with historical data on the same topic
• You are hoping to replicate the results of a scientific study by re-analyzing their open data
• You want to blend data from several sources to produce a holistic analysis of a topic

We are incredibly lucky to live during a time when the amount of available digital data is skyrocketing! Using existing data for research projects can help save time and money, and supports innovation within the scholarly community. For more information on the benefits of reusing data, please visit this resource: 

Open Knowledge Foundation

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• Last Updated: Jun 12, 2024 5:01 PM
• URL: https://libguides.utk.edu/find_data

What is Secondary Research? Types, Methods, Examples

Appinio Research · 20.09.2023 · 13min read

Have you ever wondered how researchers gather valuable insights without conducting new experiments or surveys? That's where secondary research steps in—a powerful approach that allows us to explore existing data and information others collect.

Whether you're a student, a professional, or someone seeking to make informed decisions, understanding the art of secondary research opens doors to a wealth of knowledge.

What is Secondary Research?

Secondary Research refers to the process of gathering and analyzing existing data, information, and knowledge that has been previously collected and compiled by others. This approach allows researchers to leverage available sources, such as articles, reports, and databases, to gain insights, validate hypotheses, and make informed decisions without collecting new data.

Benefits of Secondary Research

Secondary research offers a range of advantages that can significantly enhance your research process and the quality of your findings.

• Time and Cost Efficiency: Secondary research saves time and resources by utilizing existing data sources, eliminating the need for data collection from scratch.
• Wide Range of Data: Secondary research provides access to vast information from various sources, allowing for comprehensive analysis.
• Historical Perspective: Examining past research helps identify trends, changes, and long-term patterns that might not be immediately apparent.
• Reduced Bias: As data is collected by others, there's often less inherent bias than in conducting primary research, where biases might affect data collection.
• Support for Primary Research: Secondary research can lay the foundation for primary research by providing context and insights into gaps in existing knowledge.
• Comparative Analysis : By integrating data from multiple sources, you can conduct robust comparative analyses for more accurate conclusions.
• Benchmarking and Validation: Secondary research aids in benchmarking performance against industry standards and validating hypotheses.

Primary Research vs. Secondary Research

When it comes to research methodologies, primary and secondary research each have their distinct characteristics and advantages. Here's a brief comparison to help you understand the differences.

Primary Research

• Data Source: Involves collecting new data directly from original sources.
• Data Collection: Researchers design and conduct surveys, interviews, experiments, or observations.
• Time and Resources: Typically requires more time, effort, and resources due to data collection.
• Fresh Insights: Provides firsthand, up-to-date information tailored to specific research questions.
• Control: Researchers control the data collection process and can shape methodologies.

Secondary Research

• Data Source: Involves utilizing existing data and information collected by others.
• Data Collection: Researchers search, select, and analyze data from published sources, reports, and databases.
• Time and Resources: Generally more time-efficient and cost-effective as data is already available.
• Existing Knowledge: Utilizes data that has been previously compiled, often providing broader context.
• Less Control: Researchers have limited control over how data was collected originally, if any.

Choosing between primary and secondary research depends on your research objectives, available resources, and the depth of insights you require.

Types of Secondary Research

Secondary research encompasses various types of existing data sources that can provide valuable insights for your research endeavors. Understanding these types can help you choose the most relevant sources for your objectives.

Here are the primary types of secondary research:

Internal Sources

Internal sources consist of data generated within your organization or entity. These sources provide valuable insights into your own operations and performance.

• Company Records and Data: Internal reports, documents, and databases that house information about sales, operations, and customer interactions.
• Sales Reports and Customer Data: Analysis of past sales trends, customer demographics, and purchasing behavior.
• Financial Statements and Annual Reports: Financial data, such as balance sheets and income statements, offer insights into the organization's financial health.

External Sources

External sources encompass data collected and published by entities outside your organization.

These sources offer a broader perspective on various subjects.

• Published Literature and Journals: Scholarly articles, research papers, and academic studies available in journals or online databases.
• Market Research Reports: Reports from market research firms that provide insights into industry trends, consumer behavior, and market forecasts.
• Government and NGO Databases: Data collected and maintained by government agencies and non-governmental organizations, offering demographic, economic, and social information.
• Online Media and News Articles: News outlets and online publications that cover current events, trends, and societal developments.

Each type of secondary research source holds its value and relevance, depending on the nature of your research objectives. Combining these sources lets you understand the subject matter and make informed decisions.

How to Conduct Secondary Research?

Effective secondary research involves a thoughtful and systematic approach that enables you to extract valuable insights from existing data sources. Here's a step-by-step guide on how to navigate the process:

1. Define Your Research Objectives

Before delving into secondary research, clearly define what you aim to achieve. Identify the specific questions you want to answer, the insights you're seeking, and the scope of your research.

2. Identify Relevant Sources

Begin by identifying the most appropriate sources for your research. Consider the nature of your research objectives and the data type you require. Seek out sources such as academic journals, market research reports, official government databases, and reputable news outlets.

3. Evaluate Source Credibility

Ensuring the credibility of your sources is crucial. Evaluate the reliability of each source by assessing factors such as the author's expertise, the publication's reputation, and the objectivity of the information provided. Choose sources that align with your research goals and are free from bias.

4. Extract and Analyze Information

Once you've gathered your sources, carefully extract the relevant information. Take thorough notes, capturing key data points, insights, and any supporting evidence. As you accumulate information, start identifying patterns, trends, and connections across different sources.

5. Synthesize Findings

As you analyze the data, synthesize your findings to draw meaningful conclusions. Compare and contrast information from various sources to identify common themes and discrepancies. This synthesis process allows you to construct a coherent narrative that addresses your research objectives.

6. Address Limitations and Gaps

Acknowledge the limitations and potential gaps in your secondary research. Recognize that secondary data might have inherent biases or be outdated. Where necessary, address these limitations by cross-referencing information or finding additional sources to fill in gaps.

7. Contextualize Your Findings

Contextualization is crucial in deriving actionable insights from your secondary research. Consider the broader context within which the data was collected. How does the information relate to current trends, societal changes, or industry shifts? This contextual understanding enhances the relevance and applicability of your findings.

8. Cite Your Sources

Maintain academic integrity by properly citing the sources you've used for your secondary research. Accurate citations not only give credit to the original authors but also provide a clear trail for readers to access the information themselves.

9. Integrate Secondary and Primary Research (If Applicable)

In some cases, combining secondary and primary research can yield more robust insights. If you've also conducted primary research, consider integrating your secondary findings with your primary data to provide a well-rounded perspective on your research topic.

You can use a market research platform like Appinio to conduct primary research with real-time insights in minutes!

10. Communicate Your Findings

Finally, communicate your findings effectively. Whether it's in an academic paper, a business report, or any other format, present your insights clearly and concisely. Provide context for your conclusions and use visual aids like charts and graphs to enhance understanding.

Remember that conducting secondary research is not just about gathering information—it's about critically analyzing, interpreting, and deriving valuable insights from existing data. By following these steps, you'll navigate the process successfully and contribute to the body of knowledge in your field.

Secondary Research Examples

To better understand how secondary research is applied in various contexts, let's explore a few real-world examples that showcase its versatility and value.

Market Analysis and Trend Forecasting

Imagine you're a marketing strategist tasked with launching a new product in the smartphone industry. By conducting secondary research, you can:

• Access Market Reports: Utilize market research reports to understand consumer preferences, competitive landscape, and growth projections.
• Analyze Trends: Examine past sales data and industry reports to identify trends in smartphone features, design, and user preferences.
• Benchmark Competitors: Compare market share, customer satisfaction, and pricing strategies of key competitors to develop a strategic advantage.
• Forecast Demand: Use historical sales data and market growth predictions to estimate demand for your new product.

Academic Research and Literature Reviews

Suppose you're a student researching climate change's effects on marine ecosystems. Secondary research aids your academic endeavors by:

• Reviewing Existing Studies: Analyze peer-reviewed articles and scientific papers to understand the current state of knowledge on the topic.
• Identifying Knowledge Gaps: Identify areas where further research is needed based on what existing studies still need to cover.
• Comparing Methodologies: Compare research methodologies used by different studies to assess the strengths and limitations of their approaches.
• Synthesizing Insights: Synthesize findings from various studies to form a comprehensive overview of the topic's implications on marine life.

Competitive Landscape Assessment for Business Strategy

Consider you're a business owner looking to expand your restaurant chain to a new location. Secondary research aids your strategic decision-making by:

• Analyzing Demographics: Utilize demographic data from government databases to understand the local population's age, income, and preferences.
• Studying Local Trends: Examine restaurant industry reports to identify the types of cuisines and dining experiences currently popular in the area.
• Understanding Consumer Behavior: Analyze online reviews and social media discussions to gauge customer sentiment towards existing restaurants in the vicinity.
• Assessing Economic Conditions: Access economic reports to evaluate the local economy's stability and potential purchasing power.

These examples illustrate the practical applications of secondary research across various fields to provide a foundation for informed decision-making, deeper understanding, and innovation.

Secondary Research Limitations

While secondary research offers many benefits, it's essential to be aware of its limitations to ensure the validity and reliability of your findings.

• Data Quality and Validity: The accuracy and reliability of secondary data can vary, affecting the credibility of your research.
• Limited Contextual Information: Secondary sources might lack detailed contextual information, making it important to interpret findings within the appropriate context.
• Data Suitability: Existing data might not align perfectly with your research objectives, leading to compromises or incomplete insights.
• Outdated Information: Some sources might provide obsolete information that doesn't accurately reflect current trends or situations.
• Potential Bias: While secondary data is often less biased, biases might still exist in the original data sources, influencing your findings.
• Incompatibility of Data: Combining data from different sources might pose challenges due to variations in definitions, methodologies, or units of measurement.
• Lack of Control: Unlike primary research, you have no control over how data was collected or its quality, potentially affecting your analysis. Understanding these limitations will help you navigate secondary research effectively and make informed decisions based on a well-rounded understanding of its strengths and weaknesses.

Secondary research is a valuable tool that businesses can use to their advantage. By tapping into existing data and insights, companies can save time, resources, and effort that would otherwise be spent on primary research. This approach equips decision-makers with a broader understanding of market trends, consumer behaviors, and competitive landscapes. Additionally, benchmarking against industry standards and validating hypotheses empowers businesses to make informed choices that lead to growth and success.

As you navigate the world of secondary research, remember that it's not just about data retrieval—it's about strategic utilization. With a clear grasp of how to access, analyze, and interpret existing information, businesses can stay ahead of the curve, adapt to changing landscapes, and make decisions that are grounded in reliable knowledge.

How to Conduct Secondary Research in Minutes?

In the world of decision-making, having access to real-time consumer insights is no longer a luxury—it's a necessity. That's where Appinio comes in, revolutionizing how businesses gather valuable data for better decision-making. As a real-time market research platform, Appinio empowers companies to tap into the pulse of consumer opinions swiftly and seamlessly.

• Fast Insights: Say goodbye to lengthy research processes. With Appinio, you can transform questions into actionable insights in minutes.
• Data-Driven Decisions: Harness the power of real-time consumer insights to drive your business strategies, allowing you to make informed choices on the fly.
• Seamless Integration: Appinio handles the research and technical complexities, freeing you to focus on what truly matters: making rapid data-driven decisions that propel your business forward.

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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.

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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Understanding the value of secondary research data June 28, 2023

“Reduce, reuse, recycle” isn’t just a good motto for preserving the environment, it’s also a smart scientific principle, thanks to the value of secondary research.

Secondary research uses existing data or specimens initially collected for purposes other than the planned (or primary) research. For example, the same specimens originally collected for a clinical trial could also be used in secondary genomic research. Secondary research maximizes the usefulness of data and unique specimens while minimizing risk to study volunteers since no new procedures are needed.

Through previous blogs, NIA provided updates and tips on the NIH Data Management and Sharing (DMS) Policy . That same policy also emphasizes the importance of sharing data gleaned from secondary research. It requires investigators, including those conducting secondary research, to describe the type of scientific data they plan to generate, and encourages good data sharing practices when performing secondary research. NIA is actively supporting secondary research through our recent Notice of Special Interest on the topic .

Advantages and challenges

Secondary research has several benefits:

• Enables use of large-scale data sets or large samples of human or model organism specimens
• Can be less expensive and time-consuming than primary data collection
• May be simpler (and expedited) if an Institutional Review Board waives the need for informed consent for a secondary research project

Potential downsides to consider might include:

• Original data may not be a perfect fit for your current research question or study design
• Details on previous data collection procedures may be scarce
• Data may potentially lack depth
• Often requires special techniques for statistical data analysis

Know the rules of the road

As you consider secondary research, be sure to get familiar with related regulations and rules. There may be requirements to access and use secondary data or specimens as stipulated by NIH-supported scientific data repositories or other sources of information. Generally, data repositories with controlled access , such as the NIA Genetics of Alzheimer’s Disease Data Storage Site ( NIAGADS ) or the Database of Genotypes and Phenotypes , require investigators to sign a Data Use Certification Agreement (PDF, 775K) to ensure protection of sensitive data.

Additional potential requirements can include:

• IRB approval to meet human subject protections (per regulation 45 CFR 46 )
• NIH Institutional Certification (for large-scale genomic data generation)
• Data Distribution Agreement (for NIAGADS) (PDF, 673K)
• Attestation of Alzheimer’s Disease Genomics Sharing Plan (for Alzheimer’s and related dementias genomic research)
• Cloud Use Statement and Cloud Server Provider Information (as applicable)
• Possible participant consent

Reach out with questions!

With these guidelines in mind, secondary research can be quite valuable to your studies. If you have questions, please refer to the FAQs About Secondary Research or leave a comment below. For specific questions related to preparing a DMS plan for the generation of secondary data for your research, contact your NIA Program Officer .

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Secondary Research for Your Dissertation: A Research Guide

Introduction     

Understanding Secondary Research    

How Secondary Research Can Influence Primary Research     

Organizing and Documenting Your Research Activities  

Apply Research Skills    

Developing and Using Search Strategies    

Applying Advanced Search Operators    

Identifying and Using Credible Sources    

Conclusion    

Additional Resources   

Introduction

Secondary research plays a crucial role in dissertation writing, providing a foundation for your primary research. By leveraging existing data, you can gain valuable insights, identify research gaps, and enhance the credibility of your study. Unlike primary research, which involves collecting original data directly through experiments, surveys, or interviews, secondary research relies on analyzing information previously gathered by others from sources such as academic journals, books, and reputable websites.

Starting with secondary research is efficient, allowing you to quickly access a wealth of information and save time and resources that would otherwise be spent on data collection. Additionally, secondary research provides a broader context for your study, helping you frame your research questions and hypotheses more effectively.

This article provides a comprehensive step-by-step guide for conducting effective secondary research for your dissertation. It covers essential topics such as developing research skills, identifying and using credible sources, employing search strategies, and utilizing advanced search operators. Additionally, it discusses integrating secondary research with primary research, ensuring your dissertation is well-rounded and robust. By following this guide, you will be equipped with the tools and techniques needed to navigate the vast landscape of existing research and enhance the quality of your dissertation.

Understanding Secondary Research

Definition and scope of secondary research.

Secondary research involves analyzing and interpreting existing data collected by others. This data can come from various sources, including academic journals, books, government reports, and online databases. The scope of secondary research is broad, encompassing a wide range of information that can provide background context, support theoretical frameworks, and help identify trends and patterns relevant to your study.

Differences Between Secondary and Primary Research

Primary research involves collecting new data directly through experiments, surveys, interviews, or observations, tailored specifically to the researcher's study objectives. Secondary research, in contrast, uses data previously gathered for other purposes. While primary research is more time-consuming and costly, it allows for precise data collection tailored to specific research questions. Secondary research, on the other hand, is more accessible and cost-effective, providing a broader context and supporting evidence for the study.

Advantages and Limitations of Secondary Research

Advantages:

Time and Cost Efficiency: Accessing existing data is quicker and less expensive than collecting new data.

Broad Scope: Provides a wide array of information and a broader context for the research.

Foundation for Primary Research: Helps formulate research questions and hypotheses by identifying existing gaps and trends.

Limitations:

Relevance and Currency: Existing data may not be entirely relevant to the specific research question or may be outdated.

Lack of Control: Researchers have no control over how the original data was collected or the quality of the data.

Potential Bias: The original data collection methods and purposes may introduce biases not aligned with the new research objectives.

How Secondary Research Can Influence Primary Research

Secondary research significantly influences primary research by providing a foundation of existing knowledge, which helps in identifying gaps and refining research questions. It informs the design of primary research, suggesting appropriate methodologies and data collection techniques.

Techniques for Integrating Secondary Data with Primary Data

Integrating secondary and primary data involves several techniques:

Literature Review: Conducting a comprehensive review of existing literature to contextualize primary findings.

Comparative Analysis: Comparing secondary data trends with primary data results to validate findings.

Triangulation: Using multiple data sources to cross-verify and strengthen the research conclusions.

Examples of Dissertations Combining Secondary and Primary Research

An effective combination of secondary and primary research can be seen in dissertations that:

Contextualize Experimental Data: Using literature reviews to frame and interpret experimental results.

Validate Survey Results: Comparing survey findings with existing statistical data from government or industry reports.

Support Qualitative Insights: Enhancing interview or focus group data with relevant case studies or historical data.

By effectively integrating secondary and primary research, dissertations can achieve a more comprehensive and nuanced understanding of the research topic, ultimately leading to more robust and credible conclusions.

Organizing and Documenting Your Research Activities

Effective organization and documentation of your research activities are crucial for maintaining the integrity and clarity of your dissertation. Here are some best practices and tips to ensure your research process is thorough and well-documented.

Best Practices for Notetaking

Taking systematic and detailed notes is essential for keeping track of your research. There are several methods you can use:

Digital Notetaking: Tools like Microsoft OneNote, Evernote, and Notion allow you to organize notes, attach files, and sync across devices. These platforms often include search functionalities, making it easier to find specific information.

Index Cards: A traditional method where each card holds a single note or idea. This can be useful for organizing thoughts and data points, allowing for easy reorganization as your research progresses.

Annotated Bibliographies: Creating annotated bibliographies helps you summarize and evaluate each source, providing a quick reference to the key points and relevance of each work.

Tips for Documenting Sources, Referencing, and Avoiding Plagiarism

Proper documentation of sources is vital to avoid plagiarism and give credit to original authors. Here are some tips:

Consistent Referencing: Use a consistent citation style (APA, MLA, Chicago, etc.) throughout your dissertation. Tools like Zotero, EndNote, and Mendeley can help manage and format citations automatically.

Detailed Records: Keep detailed records of all sources, including full citations and page numbers for specific quotes or data points. This can be done using citation management tools or a simple spreadsheet.

Quotations and Paraphrasing: Clearly distinguish between direct quotes and paraphrased ideas in your notes. Use quotation marks for direct quotes and always cite the source.

Plagiarism Checkers: Utilize plagiarism detection software (such as Turnitin or Grammarly) to ensure originality and proper citation of all referenced material.

Creating a Research Log or Journal

A research log or journal is an effective way to track your sources and notes systematically:

Log Structure: Create a structured format for your log, including sections for date, source, notes, and reflections. This can be done in a digital document or a physical notebook.

Source Tracking: Record full citation details for each source as soon as you find it. Include a brief summary of the content and its relevance to your research.

Progress Tracking: Regularly update your log with new insights, reflections, and any changes in your research direction. This helps in keeping a clear record of your thought process and development over time.

Integration with Notetaking Tools: Many digital notetaking tools allow you to integrate your research log, making it easier to link notes to specific sources and track your research progress comprehensively.

By following these practices, you can ensure that your research activities are well-organized and documented, ultimately leading to a more coherent and credible dissertation.

Apply Research Skills

Importance of strong research skills in conducting secondary research.

Strong research skills are critical for conducting effective secondary research. They enable you to efficiently locate, evaluate, and synthesize information from various sources, providing a solid foundation for your dissertation. These skills help you discern the quality and relevance of sources, ensuring that your research is built on credible and accurate data. Moreover, adept research skills enhance your ability to identify research gaps, frame your research questions, and develop a comprehensive literature review that contextualizes your study within the existing body of knowledge.

Time Management and Organization Tips for Efficient Research

Efficient research requires effective time management and organization. Here are some tips:

Set Clear Goals: Define specific research goals and break them down into manageable tasks. This helps in maintaining focus and tracking progress.

Create a Schedule: Allocate dedicated time slots for research activities and stick to a consistent schedule. Use tools like calendars and project management apps to plan your research timeline.

Use Reference Management Tools: Tools like EndNote, Zotero, and Mendeley help organize your sources, making it easier to manage citations and bibliographies.

Maintain a Research Log: Keep a detailed log of your research activities, sources consulted, and notes taken. This log helps track your progress and ensures that you do not overlook important information.

Developing and Using Search Strategies

Importance of having a clear search strategy.

A clear search strategy is essential for efficient and effective research. It ensures that you systematically explore relevant sources, avoid missing crucial information, and stay focused on your research objectives. A well-defined search strategy saves time and effort by streamlining the search process and enhancing the quality of your findings.

Steps to Develop an Effective Search Strategy

Define Research Questions: Start with clear and concise research questions that guide your search . This helps in narrowing down the focus and identifying relevant keywords.

Identify Keywords: Extract key terms and phrases from your research questions. Consider synonyms and related terms to broaden your search scope.

Use Boolean Operators: Incorporate Boolean operators (AND, OR, NOT) to refine your search . For example, use "AND" to combine terms, "OR" to include synonyms, and "NOT" to exclude irrelevant terms.

Apply Filters: Use filters to narrow down search results based on criteria such as publication date, source type, and subject area.

Iterate and Refine: Continuously refine your search strategy based on the results you obtain. Adjust keywords, Boolean operators, and filters as needed to improve the relevance of your findings.

How to Broaden or Narrow Down Search Results Based on Research Needs

Broadening Search Results: Use general keywords, include synonyms, and apply the OR operator to capture a wider range of results. Avoid using too many filters initially.

Narrowing Search Results: Use specific keywords, add more terms using the AND operator, and apply filters such as publication date, subject area, and document type. Exclude irrelevant terms using the NOT operator.

Applying Advanced Search Operators

Introduction to advanced search operators.

Advanced search operators are special characters and commands that enhance search precision. Common operators include Boolean operators (AND, OR, NOT), wildcards (*), and quotation marks ("").

How to Use Advanced Search Operators in Various Databases and Search Engines

Boolean Operators: Use AND to combine search terms (e.g., "climate change AND policy"), OR to include either term (e.g., "adolescents OR teenagers"), and NOT to exclude terms (e.g., "genetics NOT epigenetics").

Wildcards: Use the asterisk ( ) to replace multiple characters (e.g., "educat " retrieves "education," "educator," "educational").

Quotation Marks: Enclose phrases in quotation marks to search for exact phrases (e.g., "renewable energy sources").

Examples of Effective Search Queries Using Advanced Search Operators

Combining Terms: "renewable energy AND policy AND (solar OR wind)"

Excluding Terms: "artificial intelligence NOT robotics"

Wildcard Use: "neuro* development" to capture "neurological development," "neurodevelopment," etc.

Exact Phrases: "climate change mitigation strategies"

By mastering advanced search operators, you can conduct more precise and efficient searches, ultimately enhancing the quality of your secondary research. These skills and techniques will ensure that your dissertation is built on a solid foundation of comprehensive and credible information.

Identifying and Using Credible Sources

Criteria for evaluating the credibility of sources.

Evaluating the credibility of sources is essential to ensure the reliability and validity of your research. Key criteria include:

Author Expertise: Assess the author's qualifications, affiliations, and expertise in the subject matter. Look for authors with advanced degrees, professional experience, or a history of publications in the field.

Publication Quality: Consider the reputation of the journal, book, or website where the information is published. Peer-reviewed academic journals are generally reliable, as they undergo rigorous scrutiny by experts.

Citation Frequency: High citation frequency can indicate the importance and influence of the work within the academic community. Use databases like Google Scholar to check citation counts.

Date of Publication: Ensure the source is current and relevant. Outdated information may not reflect the latest research and developments in the field.

Objective and Balanced: Evaluate whether the source presents information objectively and without bias. Reliable sources typically provide evidence-based analysis and avoid sensationalism.

Examples of Credible Sources

Academic Journals: Journals such as Nature , The Lancet , and Journal of Business Research provide peer-reviewed articles that are highly credible.

Books: Scholarly books published by reputable academic presses (e.g., Oxford University Press, Harvard University Press) offer in-depth and well-researched information.

Reputable Websites: Websites ending in .edu, .gov, and .org, such as those belonging to universities, government agencies, and reputable non-profit organizations, are generally reliable. Examples include the National Institutes of Health (nih.gov) and the World Health Organization (who.int).

How to Cross-Check Information for Reliability and Accuracy

Cross-checking information involves comparing data and findings across multiple credible sources to verify accuracy. Here’s how to do it:

Use Multiple Sources: Gather information from several reputable sources to confirm facts and identify discrepancies.

Compare Findings: Look for consistency in data, results, and conclusions across different studies and publications. Consistent findings enhance the credibility of the information.

Check References: Review the references and citations within a source to trace the origin of the information. Reliable sources cite reputable and original research.

Consult Experts: When possible, consult experts or seek peer feedback to validate the information.

By diligently evaluating and cross-checking sources, you can ensure that your research is built on a solid foundation of credible and accurate information, enhancing the overall quality and reliability of your dissertation.

Secondary research is a vital component of dissertation writing, providing a comprehensive foundation that supports and enhances primary research. By effectively utilizing secondary data, you can gain valuable insights, identify existing gaps in the literature, and develop a robust context for your study. This guide has outlined the key steps and best practices for conducting secondary research, from understanding its scope and differences from primary research to organizing your research activities and applying advanced search strategies.

Developing strong research skills is crucial for navigating the vast landscape of existing data. Techniques such as critical thinking, participating in workshops, and using online courses can significantly enhance your research capabilities. Efficient time management and organization are also essential, ensuring that your research process is streamlined and productive. Creating a detailed research log or journal, using digital notetaking tools, and maintaining consistent referencing practices are some of the best ways to keep your research well-documented and credible.

Having a clear search strategy is fundamental to efficient secondary research. By defining your research questions, identifying relevant keywords, and using Boolean operators, you can refine your searches and find pertinent information more effectively. Advanced search operators further enhance search precision, allowing you to conduct more targeted and comprehensive searches across various databases and search engines.

Identifying and using credible sources is critical to the reliability and validity of your dissertation. Evaluating the credibility of sources based on author expertise, publication quality, citation frequency, and objectivity ensures that your research is built on solid, trustworthy data. Cross-checking information across multiple reputable sources and consulting experts helps verify the accuracy of your findings.

Integrating secondary and primary research can lead to a more nuanced and comprehensive understanding of your research topic. Techniques such as literature reviews, comparative analysis, and triangulation enable you to combine existing knowledge with new data, resulting in more robust and credible conclusions.

By following the steps and best practices outlined in this guide, you can conduct effective secondary research that significantly enhances the quality of your dissertation. Leveraging the wealth of existing data not only provides a strong foundation for your study but also saves time and resources, allowing you to focus on generating new insights and contributions to your field.

Additional Resources

To further enhance your understanding and skills in writing a dissertation methodology, consider exploring the following resources:

Books and Guides:

"Research Design: Qualitative, Quantitative, and Mixed Methods Approaches" by John W. Creswell and J. David Creswell : A comprehensive guide on different research designs and methodologies.

"The Craft of Research" by Wayne C. Booth, Gregory G. Colomb, and Joseph M. Williams : A valuable resource for understanding the research process, including methodology.

"Succeeding with Your Master’s Dissertation" by John Biggam : Provides practical advice on the entire dissertation process, including secondary research.

Lined and Blank Notebooks: Available for purchase from Amazon, we offer a selection of lined and blank notebooks designed for students to capture all dissertation-related thoughts and research in one centralized place, ensuring that you can easily access and review your work as the project evolves.

The lined notebooks provide a structured format for detailed notetaking and organizing research questions systematically

The blank notebooks offer a free-form space ideal for sketching out ideas, diagrams, and unstructured notes.

By utilizing these resources, you can deepen your understanding of secondary research methods, enhance your research skills, and ensure your dissertation is well-supported by comprehensive and credible secondary research.

As an Amazon Associate, I may earn from qualifying purchases.

Analysing and Interpreting Data in Your Dissertation: Making Sense of Your Findings

Dissertation methodology unpacked: explaining your approach.

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Secondary Data Analysis: Ethical Issues and Challenges

Research does not always involve collection of data from the participants. There is huge amount of data that is being collected through the routine management information system and other surveys or research activities. The existing data can be analyzed to generate new hypothesis or answer critical research questions. This saves lots of time, money and other resources. Also data from large sample surveys may be of higher quality and representative of the population. It avoids repetition of research & wastage of resources by detailed exploration of existing research data and also ensures that sensitive topics or hard to reach populations are not over researched ( 1 ). However, there are certain ethical issues pertaining to secondary data analysis which should be taken care of before handling such data.

Secondary data analysis

Secondary analysis refers to the use of existing research data to find answer to a question that was different from the original work ( 2 ). Secondary data can be large scale surveys or data collected as part of personal research. Although there is general agreement about sharing the results of large scale surveys, but little agreement exists about the second. While the fundamental ethical issues related to secondary use of research data remain the same, they have become more pressing with the advent of new technologies. Data sharing, compiling and storage have become much faster and easier. At the same time, there are fresh concerns about data confidentiality and security.

Issues in Secondary data analysis

Concerns about secondary use of data mostly revolve around potential harm to individual subjects and issue of return for consent. Secondary data vary in terms of the amount of identifying information in it. If the data has no identifying information or is completely devoid of such information or is appropriately coded so that the researcher does not have access to the codes, then it does not require a full review by the ethical board. The board just needs to confirm that the data is actually anonymous. However, if the data contains identifying information on participants or information that could be linked to identify participants, a complete review of the proposal will then be made by the board. The researcher will then have to explain why is it unavoidable to have identifying information to answer the research question and must also indicate how participants’ privacy and the confidentiality of the data will be protected. If the above said concerns are satisfactorily addressed, the researcher can then request for a waiver of consent.

If the data is freely available on the Internet, books or other public forum, permission for further use and analysis is implied. However, the ownership of the original data must be acknowledged. If the research is part of another research project and the data is not freely available, except to the original research team, explicit, written permission for the use of the data must be obtained from the research team and included in the application for ethical clearance.

However, there are certain other issues pertaining to the data that is procured for secondary analysis. The data obtained should be adequate, relevant but not excessive. In secondary data analysis, the original data was not collected to answer the present research question. Thus the data should be evaluated for certain criteria such as the methodology of data collection, accuracy, period of data collection, purpose for which it was collected and the content of the data. It shall be kept for no longer than is necessary for that purpose. It must be kept safe from unauthorized access, accidental loss or destruction. Data in the form of hardcopies should be kept in safe locked cabinets whereas softcopies should be kept as encrypted files in computers. It is the responsibility of the researcher conducting the secondary analysis to ensure that further analysis of the data conducted is appropriate. In some cases there is provision for analysis of secondary data in the original consent form with the condition that the secondary study is approved by the ethics review committee. According to the British Sociological Association’s Statement of Ethical Practice (2004) the researchers must inform participants regarding the use of data and obtain consent for the future use of the material as well. However it also says that consent is not a once-and-for-all event, but is subject to renegotiation over time ( 3 ). It appears that there are no guidelines about the specific conditions that require further consent.

Issues in Secondary analysis of Qualitative data

In qualitative research, the culture of data archiving is absent ( 4 ). Also, there is a concern that data archiving exposes subject’s personal views. However, the best practice is to plan anonymisation at the time of initial transcription. Use of pseudonyms or replacements can protect subject’s identity. A log of all replacements, aggregations or removals should be made and stored separately from the anonymised data files. But because of the circumstances, under which qualitative data is produced, their reinterpretation at some later date can be challenging and raises further ethical concerns.

There is a need for formulating specific guidelines regarding re-use of data, data protection and anonymisation and issues of consent in secondary data analysis.

Acknowledgements

The authors declare that there is no conflict of interest.

• Fielding NG, Fielding JL (2003). Resistance and adaptation to criminal identity: Using secondary analysis to evaluate classic studies of crime and deviance . Sociology , 34 ( 4 ): 671–689. [ Google Scholar ]
• Szabo V, Strang VR (1997). Secondary analysis of qualitative data . Advances in Nursing Science , 20 ( 2 ): 66–74. [ PubMed ] [ Google Scholar ]
• Statement of Ethical Practice for the British Sociological Association (2004). The British Sociological Association, Durham . Available at: http://www.york.ac.uk/media/abouttheuniversity/governanceandmanagement/governance/ethicscommittee/hssec/documents/BSA%20statement%20of%20ethical%20practice.pdf (Last accessed 24November2013)
• Archiving Qualitative Data: Prospects and Challenges of Data Preservation and Sharing among Australian Qualitative Researchers. Institute for Social Science Research, The University of Queensland, 2009 . Available at: http://www.assda.edu.au/forms/AQuAQualitativeArchiving_DiscussionPaper_FinalNov09.pdf (Last accessed 05September2013)

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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.
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• Packaged Facts : Reports based on market research on consumer goods and services industries.
• Dun & Bradstreet : Company directory with business information.

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10 Secondary Data Sources

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Secondary data refers to any research data that is not collected for the purpose of your own study, but is repurposed and reanalyzed within your study.

In Dissertation Research Methods: A Step-by-Step Guide , Philip Adu and Anthony Miles (2023) provide a succinct scholarly definition:

Secondary data is defined as data collected for a purpose other than the problem at hand, and secondary analysis is usually undertaken by researchers who did not conduct the primary data collection .

The most common times when we would use secondary data is in literature reviews and meta-analyses, where we collect, collate, compare, analyze, and synthesize other people’s data to identify research trends, allowing us to understand the landscape of research on a topic. This can help researchers to identify research gaps. ( See more times we would conduct secondary research here ).

Below is a list of common sources of secondary data.

Secondary Data Sources

1. academic journal articles.

Academic journal articles are scholarly papers published in academic journals. They usually report on original research, review existing literature, or present theoretical analyses in various academic fields.

When researchers use academic journal articles, they are accessing the data, analyses, or findings of other researchers. The original data collected and analyzed by the authors of these articles becomes secondary data when it is reused or reanalyzed by other researchers.

Typically, researchers will use academic journal articles as secondary data sources when they are used in literature reviews and meta-analyses.

In these situations, researchers will synthesize and analyze the findings of multiple studies to draw broader conclusions, identify trends, or discover research gaps in a specific field. This process allows them to build upon existing knowledge without conducting original data collection.

2. Government Publications

Government publications are a treasure trove of secondary data. These can include documents such as reports, policy papers, statistics, and research findings issued by government bodies or agencies.

These publications often contain data collected by government agencies for purposes such as policy development, monitoring, and administrative functions.

When this data is used by researchers for a different purpose than its original intent, it becomes secondary data.

For example, researchers might utilize government publications to gain insights into policy impacts, demographic trends, and socio-economic conditions.

Researchers rely on the credibility and the comprehensive nature of government data to support their findings or to compare with data from other sources, but should still always check the methodological rigor of those studies.

3. Industry Reports

Industry reports are research reports produced by market research firms, industry analysts, or trade associations. They tend to provide detailed analysis on industry trends, market size, competitive landscapes, and consumer behaviors.

These reports compile data gathered from various sources like surveys, market analysis, and business operations. This compiled data can be used as secondary data for researchers who did not participate in the original data collection process, but can leverage that data for their own studies.

Industry reports save researchers time and resources as they provide consolidated and analyzed data relevant to a specific industry.

4. Census Data

Census data refers to the information collected during national or regional censuses, which are typically conducted by governments at regular intervals (often every five or ten years).

This data generally includes demographic information such as age, gender, ethnicity, employment status, and housing conditions of the population.

While government use this data to inform public spending distributions and infrastructure planning, it’s analyzed by researchers for a range of other purposes, given the fact this is detailed and authoritative cross-sectional data on populations. This allows researchers to identify trends, make comparisons across regions and time periods, and support policy development and academic studies.

5. Historical Records

Historical records encompass a wide range of documents and materials that provide information about past events, people, and societies. These can include government records and curated artifacts.

When researchers use historical records, they are accessing data that was originally created or collected for purposes other than their current research inquiry. These records serve as secondary data because they are being repurposed to extract information and insights about the past.

Researchers in fields such as history, anthropology, and sociology use historical records to understand the context and events of the past.

These records are vital for reconstructing historical narratives, understanding cultural and societal changes, and analyzing historical events and trends.

Researchers rely on the authenticity and preservation of these records to conduct accurate and insightful historical analysis.

6. Public Opinion Polls

Public opinion polls are surveys conducted to gauge the public’s views, attitudes, or perceptions on various topics, ranging from politics and social issues to consumer products and services.

Public opinion polls become secondary data when researchers use the collected survey data for purposes other than the original intent of the poll. The initial purpose of these polls is to understand the current views of a specific population at a specific time.

Researchers use data from public opinion polls to analyze trends in public attitudes, understand societal changes, or validate hypotheses in social science research. This data is especially useful in fields like political science, marketing, and sociology.

7. Health Records

Health records consist of detailed information about an individual’s medical history, diagnoses, treatments, and health outcomes. These records are typically maintained by healthcare providers, hospitals, and clinics.

These records are considered secondary data when researchers use them for studies or analyses beyond their initial purpose of individual patient care and treatment. The data in these records was primarily collected for clinical purposes and patient management.

Researchers use health records to conduct epidemiological studies, public health research, and to analyze healthcare outcomes. These records provide invaluable data for understanding disease patterns, treatment effectiveness, and healthcare disparities. By analyzing this data, researchers can identify risk factors for diseases, assess the impact of healthcare interventions, and contribute to the development of evidence-based medical practices and policies.

However, accessing health records comes with a range of ethical issues , which are tightly regulated, which makes accessing this data difficult.

8. Trade and Economic Indexes

Trade and economic indexes are statistical measures that track economic performance, market trends, and trade activities. Examples include the Consumer Price Index (CPI), Gross Domestic Product (GDP), and various stock market indices.

While the data is not collected by academic reseasrchers, and not intended for them, researchers often use these indexes to study economic trends, evaluate policy impacts, and understand market behaviors.

In economics, finance, and business studies, these indexes are crucial for analyzing economic health, forecasting market trends, and making investment decisions.

By examining changes in these indexes, researchers can infer about inflation, economic growth, and consumer behavior, thus enabling informed decision-making in various economic and business contexts.

9. Policy Documents

Policy documents are formal records that outline the principles, plans, and objectives of specific policies implemented by governments, organizations, or institutions. These documents can include legislation, regulatory guidelines, strategic plans, and governmental directives.

Policy documents are considered secondary data when researchers use them to analyze or evaluate the impact and effectiveness of certain policies, analyze their ideological leanings via discourse analysis, and so on. Whenever the research is relied upon and used for purposes rather than for their original purpose of policy implementation and guidance, we consider them to be secondary data soureces.

By analyzing these documents, researchers can understand the rationale behind policies, their intended objectives, and their real-world impacts.

This analysis can inform future policy development, offer critiques of current policies, and contribute to the academic discourse on governance and policy-making.

10. Market Research Data

Market research data includes information gathered about consumers, market trends, competitors, and industry dynamics. This data is collected through methods like surveys, focus groups, sales analysis, and consumer feedback.

Market research data becomes secondary when researchers use it for purposes other than its initial marketing or business objectives. The primary purpose of collecting this data is to inform business strategies, product development, and marketing tactics.

Nevertheless, researchers utilize market research data to understand consumer behavior, analyze market trends, and study economic patterns.

By analyzing this secondary data, researchers can identify market opportunities, forecast consumer trends, and evaluate the effectiveness of marketing strategies.

This secondary use of market research data is crucial for businesses and policymakers to make informed decisions that align with consumer needs and market conditions.

Primary vs Secondary Data

Primary data is collected firsthand for specific research objectives , offering highly relevant and controlled information, but it can be time-consuming and expensive to gather.

Secondary data, on the other hand, is pre-existing data collected for other purposes, which is less costly and quicker to access but may not be as precisely tailored to the specific research needs and can vary in accuracy and relevance (Cameron & Price, 2009).

Here is a table comparing primary data to secondary data:

Benefits and Limitations of Secondary Data

Secondary data can be attractive to research students because it helps them to skip the process of original data gathering (complete with complications like passing ethical review boards), allowing them to focus on data analysis and evaluation processes.

However, ideally, that’s not why you’d lean toward secondary data. Instead, a stronger reason to conduct a secondary research project is to help progress knowledge in a topic area by identifying trends in the area, and revealing previously unidentified insights that are burried in datasets (Rodriguez, Crossman & Bordia, 2021).

Below is a table comparing other possible benefits and limitations:

Adu, P., & Miles, D. A. (2023). Dissertation Research Methods: A Step-by-Step Guide to Writing Up Your Research in the Social Sciences . London: Taylor & Francis.

Cameron, S., & Price, D. (2009).  Business Research Methods: A Practical Approach . Kogan Page.

Kenett, R. S., & Shmueli, G. (2016).  Information Quality: The Potential of Data and Analytics to Generate Knowledge.  Wiley.

Kumar, R. (2010).  Research Methodology: A Step-by-Step Guide for Beginners . SAGE Publications.

Rodriguez, L., Crossman, J., & Bordia, S. (2021). An interdisciplinary approach to secondary qualitative data analysis: what why and how. In  Handbook of qualitative research methodologies in workplace contexts  (pp. 133-156). Edward Elgar Publishing.

Wilson, J. (2021).  Understanding Research for Business Students: A Complete Student’s Guide . SAGE Publications.

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Secondary research: definition, methods, & examples.

18 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.

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, organisational 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, analyse 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 organisations 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 organised 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.    Analyse 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 summarise 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.

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 organisation. External data refers to data published outside of and not owned by the researcher’s organisation.

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 organisation wants to consider entering. For instance, by viewing the U.S Census Bureau demographic data for that area, you can see what your target audience’s demographic segmentations 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, synthesising 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 analyse 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 organisation 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 organisation 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 favour 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.

Download our free guide for a clearer view on market research for your business

Related resources

Market intelligence tools 10 min read, qualitative research questions 11 min read, primary vs secondary research 14 min read, business research methods 12 min read, ethnographic research 11 min read, business research 10 min read, qualitative research design 12 min read, request demo.

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The development of high-throughput RNA structure profiling methods in the past decade has greatly facilitated our ability to map and characterize different aspects of RNA structures transcriptome-wide in cell populations, single cells and single molecules. The resulting high-resolution data have provided insights into the static and dynamic nature of RNA structures, revealing their complexity as they perform their respective functions in the cell. In this Review, we discuss recent technical advances in the determination of RNA structures, and the roles of RNA structures in RNA biogenesis and functions, including in transcription, processing, translation, degradation, localization and RNA structure-dependent condensates. We also discuss the current understanding of how RNA structures could guide drug design for treating genetic diseases and battling pathogenic viruses, and highlight existing challenges and future directions in RNA structure research.

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Probing the dynamic RNA structurome and its functions

Keth-seq for transcriptome-wide RNA structure mapping

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Acknowledgements

This work was supported by the UK Biotechnology and Biological Sciences Research Council (BBSRC) (BB/X01102X/1) and European Research Council (ERC) (selected by the ERC, funded by BBSRC Horizon Europe Guarantee (EP/Y009886/1)) (Y.D. and Y.Z.). Y.W. and X.C. are supported by funding from A*STAR, the National Research Foundation of Singapore, the EMBO Young Investigator Programme and a CIFAR Azrieli global scholar fellowship.

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These authors contributed equally: Xinang Cao, Yueying Zhang.

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Stem Cell and Regenerative Biology, Genome Institute of Singapore, Singapore, Singapore

Xinang Cao & Yue Wan

Department of Cell and Developmental Biology, John Innes Centre, Norwich, UK

Yueying Zhang & Yiliang Ding

Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

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Supplementary information.

An RNA structure in a riboswitch that binds to small molecules.

Refers to the use of nucleases that cleave RNA selectively at single-stranded or double-stranded regions (for example, RNase T1 and RNase V1, respectively); the resulting digestion footprints of the RNA can chart its structure.

Cytosine-rich DNAs that form quadruplex structures; also known as intercalated-motif DNAs.

Highly folded segments of (mostly bacterial) mRNAs that, when bound by environmental small molecules, induce structure changes that regulate the transcription or translation of the mRNA.

A three-stranded nucleic acid structure composed of a DNA–RNA hybrid and a displaced single strand of DNA.

A class of small non-coding RNAs (ncRNAs) that mostly reside in nucleoli, which guide chemical modifications of other RNA species such as ribosomal RNAs.

Dynamic cytoplasmic bodies formed in response to cellular stress, comprising RNA molecules and various proteins; they have a role in RNA metabolism and are associated with responses to environmental stresses.

(uORFs). Open reading frames (ORFs) located upstream of a main open reading frame, that is, within the 5′ untranslated region (UTR) of the mRNA. uORFs can encode small peptides, and can regulate the translation of the main ORF by competing for the translation machinery.

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Cao, X., Zhang, Y., Ding, Y. et al. Identification of RNA structures and their roles in RNA functions. Nat Rev Mol Cell Biol (2024). https://doi.org/10.1038/s41580-024-00748-6

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Published : 26 June 2024

DOI : https://doi.org/10.1038/s41580-024-00748-6

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