secondary data research methodology example

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Secondary research: definition, methods, & examples.

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

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

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

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What is secondary research?

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

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

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

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

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

How to conduct secondary research

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

1.    Identify and define the research topic

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

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

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

2.    Find research and existing data sources

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

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

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

3.    Begin searching and collecting the existing data

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

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

4.    Combine the data and compare the results

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

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

5.    Analyze your data and explore further

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

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

Primary vs secondary research

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

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

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

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

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

Sources of Secondary Research

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

Internal data

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

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

External data

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

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

Three examples of secondary research methods in action

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

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

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

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

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

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

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

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

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

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

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

Advantages of secondary research

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

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

Disadvantages of secondary research

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

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

When do we conduct secondary research?

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

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

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

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

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

Questions to ask before conducting secondary research

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

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

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

• What am I trying to achieve with this research?

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

• How credible will my research be?

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

• What is the date of the secondary research?

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

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

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

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

In it, you’ll learn more about:

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

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

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Market intelligence 10 min read, marketing insights 11 min read, ethnographic research 11 min read, qualitative vs quantitative research 13 min read, qualitative research questions 11 min read, qualitative research design 12 min read, primary vs secondary research 14 min read, request demo.

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Home » Secondary Data – Types, Methods and Examples

Secondary Data – Types, Methods and Examples

Table of Contents

Secondary Data

Definition:

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

Secondary Data Types

Types of secondary data are as follows:

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

Secondary Data Collection Methods

Secondary Data Collection Methods are as follows:

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

Secondary Data Formats

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

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

Secondary Data Analysis Methods

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

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

Secondary Data Gathering Guide

Here are some steps to follow when gathering secondary data:

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

Examples of Secondary Data

Here are some examples of secondary data from different fields:

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

Purpose of Secondary Data

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

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

When to use Secondary Data

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

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

Characteristics of Secondary Data

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

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

Advantages of Secondary Data

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

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

Limitations of Secondary Data

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

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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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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.

LEARN ABOUT: Level of Analysis

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

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Secondary Research Methods with Examples

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

The following are popularly used secondary research methods and examples:

1. Data Available on The Internet

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

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

2. Government and Non-Government Agencies

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

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

3. Public Libraries

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

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

4. Educational Institutions

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

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

5. Commercial Information Sources

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

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

Key Differences between Primary Research and Secondary Research

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

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.

LEARN ABOUT: 12 Best Tools for Researchers

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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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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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 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?

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• 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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What Is Secondary Data? A Complete Guide

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

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

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

We’ll cover the following topics:  

What is secondary data?

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

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

1. What is secondary data?

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

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

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

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

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

What is primary data?

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

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

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

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

What is third-party data?

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

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

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

3. What are some examples of secondary data?

External secondary data.

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

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

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

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

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

Internal secondary data 

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

Sources of internal secondary data might include:

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

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

4. How to analyse secondary data

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

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

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

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

5. Advantages of secondary data

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

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

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

Advantages of using secondary data

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

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

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

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

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

6. Disadvantages of secondary data

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

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

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

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

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

7. Wrap-up and further reading

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

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

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

• 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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What is Secondary Research?

Secondary research, also known as a literature review , preliminary research , historical research , background research , desk research , or library research , is research that analyzes or describes prior research. Rather than generating and analyzing new data, secondary research analyzes existing research results to establish the boundaries of knowledge on a topic, to identify trends or new practices, to test mathematical models or train machine learning systems, or to verify facts and figures. Secondary research is also used to justify the need for primary research as well as to justify and support other activities. For example, secondary research may be used to support a proposal to modernize a manufacturing plant, to justify the use of newly a developed treatment for cancer, to strengthen a business proposal, or to validate points made in a speech.

Why Is Secondary Research Important?

Because secondary research is used for so many purposes in so many settings, all professionals will be required to perform it at some point in their careers. For managers and entrepreneurs, regardless of the industry or profession, secondary research is a regular part of worklife, although parts of the research, such as finding the supporting documents, are often delegated to juniors in the organization. For all these reasons, it is essential to learn how to conduct secondary research, even if you are unlikely to ever conduct primary research.

Secondary research is also essential if your main goal is primary research. Research funding is obtained only by using secondary research to show the need for the primary research you want to conduct. In fact, primary research depends on secondary research to prove that it is indeed new and original research and not just a rehash or replication of somebody else’s work.

• Next: Literature Review >>
• Last Updated: Dec 21, 2023 3:46 PM
• URL: https://guides.library.iit.edu/litreview

15 Secondary Research Examples

Secondary research is the analysis, summary or synthesis of already existing published research. Instead of collecting original data, as in primary research , secondary research involves data or the results of data analyses already collected.

It is generally published in books, handbooks, textbooks, articles, encyclopedias, websites, magazines, literature reviews and meta-analyses. These are usually referred to as secondary sources .

Secondary research is a good place to start when wanting to acquire a broad view of a research area. It is usually easier to understand and may not require advanced training in research design and statistics.

Secondary Research Examples

1. literature review.

A literature review summarizes, reviews, and critiques the existing published literature on a topic.

Literature reviews are considered secondary research because it is a collection and analysis of the existing literature rather than generating new data for the study.

They hold value for academic studies because they enable us to take stock of the existing knowledge in a field, evaluate it, and identify flaws or gaps in the existing literature. As a result, they’re almost universally used by academics prior to conducting primary research.

Example 1: Workplace stress in nursing: a literature review

Citation: McVicar, A. (2003). Workplace stress in nursing: a literature review.  Journal of advanced nursing ,  44 (6), 633-642. Source: https://doi.org/10.1046/j.0309-2402.2003.02853.x

Summary: This study conducted a systematic analysis of literature on the causes of stress for nurses in the workplace. The study explored the literature published between 2000 and 2014. The authors found that the literature identifies several main causes of stress for nurses: professional relationships with doctors and staff, communication difficulties with patients and their families, the stress of emergency cases, overwork, lack of staff, and lack of support from the institutions. They conclude that understanding these stress factors can help improve the healthcare system and make it better for both nurses and patients.

Example 2: The impact of shiftwork on health: a literature review

Citation: Matheson, A., O’Brien, L., & Reid, J. A. (2014). The impact of shiftwork on health: a literature review.  Journal of Clinical Nursing ,  23 (23-24), 3309-3320. Source: https://doi.org/10.1111/jocn.12524

In this literature review, 118 studies were analyzed to examine the impact of shift work on nurses’ health. The findings were organized into three main themes: physical health, psychosocial health, and sleep. The majority of shift work research has primarily focused on these themes, but there is a lack of studies that explore the personal experiences of shift workers and how they navigate the effects of shift work on their daily lives. Consequently, it remains challenging to determine how individuals manage their shift work schedules. They found that, while shift work is an inevitable aspect of the nursing profession, there is limited research specifically targeting nurses and the implications for their self-care.

Example 3: Social media and entrepreneurship research: A literature review

Citation: Olanrewaju, A. S. T., Hossain, M. A., Whiteside, N., & Mercieca, P. (2020). Social media and entrepreneurship research: A literature review.  International Journal of Information Management ,  50 , 90-110. Source: https://doi.org/10.1016/j.ijinfomgt.2019.05.011

In this literature review, 118 studies were analyzed to examine the impact of shift work on nurses’ health. The findings were organized into three main themes: physical health, social health , and sleep. The majority of shift work research has primarily focused on these themes, but there is a lack of studies that explore the personal experiences of shift workers and how they navigate the effects of shift work on their daily lives. Consequently, it remains challenging to determine how individuals manage their shift work schedules. They found that, while shift work is an inevitable aspect of the nursing profession, there is limited research specifically targeting nurses and the implications for their self-care.

Example 4: Adoption of electric vehicle: A literature review and prospects for sustainability

Citation: Kumar, R. R., & Alok, K. (2020). Adoption of electric vehicle: A literature review and prospects for sustainability.  Journal of Cleaner Production ,  253 , 119911. Source: https://doi.org/10.1016/j.jclepro.2019.119911

This study is a literature review that aims to synthesize and integrate findings from existing research on electric vehicles. By reviewing 239 articles from top journals, the study identifies key factors that influence electric vehicle adoption. Themes identified included: availability of charging infrastructure and total cost of ownership. The authors propose that this analysis can provide valuable insights for future improvements in electric mobility.

Example 5: Towards an understanding of social media use in the classroom: a literature review

Citation: Van Den Beemt, A., Thurlings, M., & Willems, M. (2020). Towards an understanding of social media use in the classroom: a literature review.  Technology, Pedagogy and Education ,  29 (1), 35-55. Source: https://doi.org/10.1080/1475939X.2019.1695657

This study examines how social media can be used in education and the challenges teachers face in balancing its potential benefits with potential distractions. The review analyzes 271 research papers. They find that ambiguous results and poor study quality plague the literature. However, they identify several factors affecting the success of social media in the classroom, including: school culture, attitudes towards social media, and learning goals. The study’s value is that it organizes findings from a large corpus of existing research to help understand the topic more comprehensively.

2. Meta-Analyses

Meta-analyses are similar to literature reviews, but are at a larger scale and tend to involve the quantitative synthesis of data from multiple studies to identify trends and derive estimates of overall effect sizes.

For example, while a literature review might be a qualitative assessment of trends in the literature, a meta analysis would be a quantitative assessment, using statistical methods, of studies that meet specific inclusion criteria that can be directly compared and contrasted.

Often, meta-analysis aim to identify whether the existing data can provide an authoritative account for a hypothesis and whether it’s confirmed across the body of literature.

Example 6: Cholesterol and Alzheimer’s Disease Risk: A Meta-Meta-Analysis

Citation: Sáiz-Vazquez, O., Puente-Martínez, A., Ubillos-Landa, S., Pacheco-Bonrostro, J., & Santabárbara, J. (2020). Cholesterol and Alzheimer’s disease risk: a meta-meta-analysis.  Brain sciences ,  10 (6), 386. Source: https://doi.org/10.3390/brainsci10060386

This study examines the relationship between cholesterol and Alzheimer’s disease (AD). Researchers conducted a systematic search of meta-analyses and reviewed several databases, collecting 100 primary studies and five meta-analyses to analyze the connection between cholesterol and Alzheimer’s disease. They find that the literature compellingly demonstrates that low-density lipoprotein cholesterol (LDL-C) levels significantly influence the development of Alzheimer’s disease, but high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG) levels do not show significant effects. This is an example of secondary research because it compiles and analyzes data from multiple existing studies and meta-analyses rather than collecting new, original data.

Example 7: The power of feedback revisited: A meta-analysis of educational feedback research

Citation: Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research.  Frontiers in Psychology ,  10 , 3087. Source: https://doi.org/10.3389/fpsyg.2019.03087

This meta-analysis examines 435 empirical studies research on the effects of feedback on student learning. They use a random-effects model to ascertain whether there is a clear effect size across the literature. The authors find that feedback tends to impact cognitive and motor skill outcomes but has less of an effect on motivational and behavioral outcomes. A key (albeit somewhat obvious) finding was that the manner in which the feedback is provided is a key factor in whether the feedback is effective.

Example 8: How Much Does Education Improve Intelligence? A Meta-Analysis

Citation: Ritchie, S. J., & Tucker-Drob, E. M. (2018). How much does education improve intelligence? A meta-analysis.  Psychological science ,  29 (8), 1358-1369. Source: https://doi.org/10.1177/0956797618774253

This study investigates the relationship between years of education and intelligence test scores. The researchers analyzed three types of quasiexperimental studies involving over 600,000 participants to understand if longer education increases intelligence or if more intelligent students simply complete more education. They found that an additional year of education consistently increased cognitive abilities by 1 to 5 IQ points across all broad categories of cognitive ability. The effects persisted throughout the participants’ lives, suggesting that education is an effective way to raise intelligence. This study is an example of secondary research because it compiles and analyzes data from multiple existing studies rather than gathering new, original data.

Example 9: A meta-analysis of factors related to recycling

Citation: Geiger, J. L., Steg, L., Van Der Werff, E., & Ünal, A. B. (2019). A meta-analysis of factors related to recycling.  Journal of environmental psychology ,  64 , 78-97. Source: https://doi.org/10.1016/j.jenvp.2019.05.004

This study aims to identify key factors influencing recycling behavior across different studies. The researchers conducted a random-effects meta-analysis on 91 studies focusing on individual and household recycling. They found that both individual factors (such as recycling self-identity and personal norms) and contextual factors (like having a bin at home and owning a house) impacted recycling behavior. The analysis also revealed that individual and contextual factors better predicted the intention to recycle rather than the actual recycling behavior. The study offers theoretical and practical implications and suggests that future research should examine the effects of contextual factors and the interplay between individual and contextual factors.

Example 10: Stress management interventions for police officers and recruits

Citation: Patterson, G. T., Chung, I. W., & Swan, P. W. (2014). Stress management interventions for police officers and recruits: A meta-analysis.  Journal of experimental criminology ,  10 , 487-513. Source: https://doi.org/10.1007/s11292-014-9214-7

The meta-analysis systematically reviews randomized controlled trials and quasi-experimental studies that explore the effects of stress management interventions on outcomes among police officers. It looked at 12 primary studies published between 1984 and 2008. Across the studies, there were a total of 906 participants. Interestingly, it found that the interventions were not effective. Here, we can see how secondary research is valuable sometimes for showing there is no clear trend or consensus in existing literature. The conclusions suggest a need for further research to develop and implement more effective interventions addressing specific stressors and using randomized controlled trials.

3. Textbooks

Academic textbooks tend not to present new research. Rather, they present key academic information in ways that are accessible to university students and academics.

As a result, we can consider textbooks to be secondary rather than primary research. They’re collections of information and research produced by other people, then re-packaged for a specific audience.

Textbooks tend to be written by experts in a topic. However, unlike literature reviews and meta-analyses, they are not necessarily systematic in nature and are not designed to progress current knowledge through identifying gaps, weaknesses, and strengths in the existing literature.

Example 11: Psychology for the Third Millennium: Integrating Cultural and Neuroscience Perspectives

This textbook aims to bridge the gap between two distinct domains in psychology: Qualitative and Cultural Psychology , which focuses on managing meaning and norms, and Neuropsychology and Neuroscience, which studies brain processes. The authors believe that by combining these areas, a more comprehensive general psychology can be achieved, which unites the biological and cultural aspects of human life. This textbook is considered a secondary source because it synthesizes and integrates information from various primary research studies, theories, and perspectives in the field of psychology.

Example 12: Cultural Sociology: An Introduction

Citation: Bennett, A., Back, L., Edles, L. D., Gibson, M., Inglis, D., Jacobs, R., & Woodward, I. (2012).  Cultural sociology: an introduction . New York: John Wiley & Sons.

This student textbook introduces cultural sociology and proposes that it is a valid model for sociological thinking and research. It gathers together existing knowledge within the field to prevent an overview of major sociological themes and empirical approaches utilized within cultural sociological research. It does not present new research, but rather packages existing knowledge in sociology and makes it understandable for undergraduate students.

Example 13: A Textbook of Community Nursing

Citation: Chilton, S., & Bain, H. (Eds.). (2017).  A textbook of community nursing . New York: Routledge.

This textbook presents an evidence-based introduction to professional topics in nursing. In other words, it gathers evidence from other research and presents it to students. It covers areas such as care approaches, public health, eHealth, therapeutic relationships, and mental health. Like many textbooks, it brings together its own secondary research with user-friendly elements like exercises, activities, and hypothetical case studies in each chapter.

4. White Papers

White papers are typically produced within businesses and government departments rather than academic research environments.

Generally, a white paper will focus on a specific topic of concern to the institution in order to present a state of the current situation as well as opportunities that could be pursued for change, improvement, or profit generation in the future.

Unlike a literature review, a white paper generally doesn’t follow standards of academic rigor and may be presented with a bias toward, or focus on, a company or institution’s mission and values.

Example 14: Future of Mobility White Paper

Citation: Shaheen, S., Totte, H., & Stocker, A. (2018). Future of Mobility White Paper.  UC Berkeley: Institute of Transportation Studies at UC Berkeley Source: https://doi.org/10.7922/G2WH2N5D

This white paper explores the how transportation is changing due to concerns over climate change, equity of access to transit, and rapid technological advances (such as shared mobility and automation). The authors aggregate current information and research on key trends, emerging technologies/services, impacts on California’s transportation ecosystem, and future growth projections by reviewing state agency publications, peer-reviewed articles, and forecast reports from various sources. This white paper is an example of secondary research because it synthesizes and integrates information from multiple primary research sources, expert interviews, and input from an advisory committee of local and state transportation agencies.

Example 15: White Paper Concerning Philosophy of Education and Environment

Citation: Humphreys, C., Blenkinsop, S. White Paper Concerning Philosophy of Education and Environment.  Stud Philos Educ   36 (1): 243–264. Source: https://doi.org/10.1007/s11217-017-9567-2

This white paper acknowledges the increasing significance of climate change, environmental degradation, and our relationship with nature, and the need for philosophers of education and global citizens to respond. The paper examines five key journals in the philosophy of education to identify the scope and content of current environmental discussions. By organizing and summarizing the located articles, it assesses the possibilities and limitations of these discussions within the philosophy of education community. This white paper is an example of secondary research because it synthesizes and integrates information from multiple primary research sources, specifically articles from the key journals in the field, to analyze the current state of environmental discussions.

5. Academic Essays

Students’ academic essays tend to present secondary rather than primary research. The student is expected to study current literature on a topic and use it to present a thesis statement.

Academic essays tend to require rigorous standards of analysis, critique, and evaluation, but do not require systematic investigation of a topic like you would expect in a literature review.

In an essay, a student may identify the most relevant or important data from a field of research in order to demonstrate their knowledge of a field of study. They may also, after demonstrating sufficient knowledge and understanding, present a thesis statement about the issue.

Secondary research involves data that has already been collected. The published research might be reviewed, included in a meta-analysis, or subjected to a re-analysis.

These findings might be published in a peer-reviewed journal or handbook, become the foundation of a book for public consumption, or presented in a more narrative form for a popular website or magazine.

Sources for secondary research can range from scientific journals to government databases and archived data accumulated by research institutes.

University students might engage in secondary research to become familiar with an area of research. That might help spark an intriguing hypothesis for a research project of master’s thesis.

Secondary research can yield new insights into human behavior , or confirm existing conceptualizations of psychological constructs.

Dave Cornell (PhD)

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Positive Punishment Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Dissociation Examples (Psychology)
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 15 Zone of Proximal Development Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ Perception Checking: 15 Examples and Definition

Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

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• Chris Drew (PhD) #molongui-disabled-link 25 Dissociation Examples (Psychology)
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Library Guides

Dissertations 4: methodology: methods.

• Introduction & Philosophy
• Methodology

Primary & Secondary Sources, Primary & Secondary Data

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

Definitions  

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

Secondary sources 

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

Primary sources 

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

Primary data 

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

Secondary data 

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

Comparison between primary and secondary data   

Use  

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

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

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

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

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

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

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

Quantitative, Qualitative & Mixed Methods

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

Quantitative research 

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

Qualitative research  

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

Mixed methods 

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

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

Ultimately, your methodology chapter should state: 

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

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

Why you rejected other methods. 

How well the method served your research. 

The problems or limitations you encountered. 

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

LinkedIn Learning Video on Academic Research Foundations: Quantitative

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

Link to quantitative research video

Some Types of Methods

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

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

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

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

ethical considerations (see also tab...)  

safety considerations  

validity  

feasibility  

recording  

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

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

Experiments 

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

For more information on Scientific Method, click here . 

Observations 

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

Questionnaires and surveys 

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

Interviews  

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

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

Focus groups   

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

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

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

Case study 

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

Content analysis 

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

Extra links and resources:  

Research Methods  

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

Doing your dissertation during the COVID-19 pandemic  

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

• Virtual Focus Groups Guidance on managing virtual focus groups

5 Minute Methods Videos

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

Case Study Research

Research Ethics

Quantitative Content Analysis 

Sequential Analysis 

Qualitative Content Analysis 

Thematic Analysis 

Social Media Research 

Mixed Method Research 

Procedural Method

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

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

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

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

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

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

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

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

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

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

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

Bibliography

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

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

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

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

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• Last Updated: Sep 14, 2022 12:58 PM
• URL: https://libguides.westminster.ac.uk/methodology-for-dissertations

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• → The 6-Step Guide to Market Research P...

The 6-Step Guide to Market Research Processes

Looking for a step-by-step guide to market research processes? Learn more about the marketing research process and methods to gather data—and make the most of it.

Latest posts on Tips

Typeform    |    05.2024

Typeform    |    04.2024

Say what you will about McDonald’s, but one of the things most respected about their brand is the international menu concept.

From maple and bacon poutine in Canada and gazpacho in Spain to India’s McPaneer Royale, McDonald’s knows how to give the people what they want.

And how do they inject local appeal in a global brand? By gaining a deep understanding of the consumers in every target market they plan to enter.

If you’re thinking about doing consumer insights research, you should be familiar with market research processes. Let’s start with the basics. What is market research, and how is it different from marketing research?

What is market research?

People often confuse market research and marketing research. Aren’t they just different words for the same thing?

ESOMAR, the global research and data association, and the American Marketing Association would disagree. Here’s the gist:

Market research emphasizes the process of collecting consumer data , while marketing research refers to the product of that information and/or a function within an organization.

Essentially, you might be looking for a marketing researcher to conduct market research. Market research will help you answer questions about your customers, your competitors, or current and potential markets.

The 6-step marketing research process

Market research can seem like a mystery.

However, market research processes are quite systematic—well, in theory. In practice, the steps involve exploration, creativity, and abstraction.

Here are a few steps you can follow to make it a bit easier.

1. Identify the problem

Researchers are curious people. That’s why every research project starts with a question.

What is the part of your business you want to know more about? Identifying the problem is the most important step in market research processes. It’s going to determine every step you take in the future—of market research, anyway.

Not sure where to start? Here are a few tips:

Look for marketing challenges or opportunities. Maybe your brand awareness could use a boost. You've noticed declining customer loyalty, or you’re considering opportunities in emerging markets.

Frame it as a question. Why is customer loyalty decreasing? How can we enter the market for luxury hotels? What does our customer’s typical path to purchase look like?

Determine what type of problem you have. In market research, a problem can be ambiguous, clearly defined, or somewhere in the middle. Do you know the variables and factors influencing what you want to measure? This is important as it'll influence your overall research design, which is up next.

2. Design the research

There are three types of research designs. The design you choose will be informed by how well-defined your problem is.

If you don’t know much about the problem, you need:

Exploratory research: If you don’t know the major variables or factors at play, your research is ambiguous. Exploratory research can help you develop a hypothesis or ask a more precise question. If you have a vague idea about what’s important to solve the problem, you need:

Descriptive research: Descriptive research does what it says on the box— it describes a certain phenomenon or the characteristics of a population. It can build on exploratory research but doesn’t give insight into the how, when, or why. Descriptive research is useful for parsing out market segments and measuring performance. Consequently, you need a pretty good idea of what you’re measuring and how it'll be measured. If you want to know how cause and effect are linked, you need:

Causal research: Market researchers conduct causal research when they want to understand the relationships between two or more variables. Simply put, causal research helps you understand cause and effect.

3. Choose your sample and market research methods

Data is the essence of market research. At the end of these market research processes, data is analyzed, interpreted, and turned into information and actionable insights.

Data can be qualitative or quantitative . Qualitative data can take many forms, from descriptions to audio and video. Quantitative data is typically presented in values and figures.

When choosing your sample, you must select the population you want to study. A population is a group with some shared characteristics that you’re interested in gathering data from. It can be broad (Canadians) or narrow (independent gym owners in Chicago).

No matter how small or large your population, you’ll unlikely be able to work with everyone.

The key to choosing a good sample is that it is representative. That means the people you select to participate (the sample) should reflect the larger group you’re studying.

4. Get the data

There are two forms of data you can collect: primary and secondary data.

Primary data is gathered specifically for your project. Secondary data has already been collected, either internally or externally through government agencies, consulting or market research firms, websites, social networks, and so on.

Depending on your research design, you may want to check internally for secondary data. For example, let’s say you’re trying to understand the annual purchase cycle for your business. You'd gather sales and reports and company records—that's secondary data.

But of course, secondary data still needs to be prepared for analysis

There are two ways to collect primary data: directly or indirectly. Direct data collection is just that—you are speaking to your participants directly. That can be through surveys, interviews, focus groups, and so on. Indirect data collection typically means observation. Think in-store observation, shelf experiments, or website heatmaps.

5. Analyze the data

Data analysis is a process of looking for patterns in data and trying to understand why those patterns exist. Data can be analyzed quantitatively or qualitatively.

Quantitative data analysis is a process more complicated than can be described here. Unless you’re a math whiz, you’ll probably just use a data analysis software like SPSS or StatCrunch.

Qualitative data analysis typically involves coding—but not the computer programming kind, don’t you worry. This type of coding can be done by hand or using software such as NVivo. It involves looking for themes, concepts, and words that are repeated throughout the data.

6. Interpret and present the insights

Interpretation involves answering the question: What does the data tell me about what I wanted to know?

That’s where themes and patterns come in. You can describe trends and present them using figures or descriptions drawn from your participants.

Part of interpretation is using what you know about customers, businesses, or markets to provide recommendations for how to move forward. These data-driven suggestions should offer a solution to the initial problem. The results of the research can also bring to light a problem you weren’t even aware you had.

Overview of market research methods

Market researchers are able to draw on a large toolbox of market research methods. Typically, they fall into the qualitative or quantitative category because of the type of data they produce.

Focus groups

Best for: Exploratory research

Type of method: Qualitative

A market research technique that involves a group discussion about certain topics led by a moderator to uncover the thoughts and opinions of participants.

In-depth interviews

Best for: Descriptive research

An interview that's conducted with an individual aimed at getting deeper insights about attitudes, motivations, or experiences.

Ethnography

Best for: Descriptive research 

Also known as participant observation, it involves spending time with participants in their natural environment (as opposed to a lab setting). 

Observational

Carefully watch people to understand what they’re doing. It allows you to learn about consumer or employee behavior but not the motivation behind it.

Discourse analysis

Best for: Exploratory or descriptive research

This is a fancy way of saying “analyzing what people say.” Social listening is a form of discourse analysis. Examining customer reviews, help transcripts, social media comments, and more are all forms of discourse analysis.

Type of method: Quantitative

Surveys are the crux of market research. They involve collecting facts, figures, and opinions using a questionnaire. Surveys can also yield qualitative data if participants write out answers. Surveys may seem simple, but there are a lot of factors that can turn good intentions into bad data—be sure to read our tips on the right question types to ask . 

Structured observation

Observation research can also be quantitative if you are observing participants without direct involvement and assigning values to certain behaviors.

A/B testing

Also called split testing, this is a way to compare responses to a variation of a single variable to see which performs better. For example, presenting users with two versions of an ad to see which gets more clicks.

Best for: Causal research

Marketing experimentation typically involves manipulating a variable to see how it influences behavior. It can be conducted in a lab or in the field. 

Examples of market research

Time to put this into practice. Let’s look at market research examples of various types of research designs. 

Exploratory market research

Mobile phone company HTC wanted to understand how they could improve the user experience of their phones. This problem required exploratory research because there wasn’t a specific feature they wanted to test. They simply wanted to learn more from their customers.

With market research, they observed how participants interacted with their phones. They looked for challenges people had with everyday usage. After analyzing these pain points, they added new functions to their next model that made the phones easier to use.

Descriptive market research

Company ABC wants to understand how large the market for vegan cheese is in Canada. They have a somewhat defined research problem: What is the potential market share for vegan cheese?

In order to provide an answer, market researchers will have to describe various characteristics: who the customers are, why they buy vegan cheese, competitor market penetration, and potential opportunities.

This requires mixed-method research. The researchers might collect secondary data on the number of vegans in Canada or how much vegan cheese is sold in the country and through which companies. They may also conduct focus groups to understand what motivates people to buy vegan cheese.

Once complete, they'll be able to present statistics on vegans in Canada and estimate Company ABC’s potential market share.

Causal market research

Causal research requires keeping variables and conditions the same, save for the one you are testing. German marketing and sensory research company iSi is a company that runs both field and lab experiments.

They worked with a chocolate bar company to design an experiment that tested 12 different chocolate bar recipes.

The consumers sequentially tested the recipes and provided ratings (quantitative data) and descriptions (qualitative data) of each one. The result was that consumers were most satiated by “a firm, tough texture and a higher amount of caramel and peanuts.”

Discovering market research processes

One thing to remember is that market research is an iterative process. You can keep using what you learn to conduct better studies and evaluate the changing market conditions and the whims of consumers. 

Ready to tackle the market research process? Build a market research survey with Typeform—choose from one of our customizable templates to gather beautifully designed data.

About the author

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Too Sensitive or Not Sensitive Enough? Sensitivity to Context and Justice-involved Youths' Response to Violence Exposure

This article discusses sensory processing sensitivity in youth and its contribution to violence and aggressive behavior, laying out the authors’ research methodology, sample population, procedure and measures, missing data, and study results.

Building on research that explored the likelihood of youth development of mental health problems and externalizing behaviors after exposure to adverse contexts, the authors address the question of the role of sensitivity in the cycle of violence. This paper presents the authors’ research methodology and findings from a research study that explored how sensitivity to context moderated the association between exposure to violence and subsequent violence and aggressive behavior in a justice-involved sample of youth. The population sample included 1,216 male youth from the Crossroads Study, aged 13 to 17 years at their first arrest, from three sites: Orange County, California; Philadelphia, Pennsylvania; and Jefferson Parish, Louisiana. The paper provides details about the research methodology, including study procedures which were approved by the Institutional Review Board of all three sites, and measures which comprised of the following: participants’ recent exposure to violence; sensitivity to context, according to the 12-item Highly Sensitive Child (HSC) scale; violent/aggressive behavior, according to the Self-Report of Offending (SRO) scale; and covariates such as demographics, prior violent/aggressive behavior, lifetime exposure to violence, sensation seeking, and impulse control. The authors’ analytic plan included bivariate correlation calculation among all key study variables, among other actions. Study results indicate that exposure to violence (ETV) is a risk factor for future violent and aggressive behavior, and lower levels of sensitivity to context may further compound the risk. An extensive discussion of study outcomes is included as well as implications for practice.

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• Social–emotional Functioning Among Bias-based Bullies, Victims, and Bully-victims
• Finding an answer in time: Assessing change in needs scores on time to recidivism among justice-involved youth
• Effects of Cross-Age Peer Mentoring Program Within a Randomized Control Trial

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FTC Announces Rule Banning Noncompetes

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Today, the Federal Trade Commission issued a final rule to promote competition by banning noncompetes nationwide, protecting the fundamental freedom of workers to change jobs, increasing innovation, and fostering new business formation.

“Noncompete clauses keep wages low, suppress new ideas, and rob the American economy of dynamism, including from the more than 8,500 new startups that would be created a year once noncompetes are banned,” said FTC Chair Lina M. Khan. “The FTC’s final rule to ban noncompetes will ensure Americans have the freedom to pursue a new job, start a new business, or bring a new idea to market.”

The FTC estimates that the final rule banning noncompetes will lead to new business formation growing by 2.7% per year, resulting in more than 8,500 additional new businesses created each year. The final rule is expected to result in higher earnings for workers, with estimated earnings increasing for the average worker by an additional $524 per year, and it is expected to lower health care costs by up to $194 billion over the next decade. In addition, the final rule is expected to help drive innovation, leading to an estimated average increase of 17,000 to 29,000 more patents each year for the next 10 years under the final rule.

Noncompetes are a widespread and often exploitative practice imposing contractual conditions that prevent workers from taking a new job or starting a new business. Noncompetes often force workers to either stay in a job they want to leave or bear other significant harms and costs, such as being forced to switch to a lower-paying field, being forced to relocate, being forced to leave the workforce altogether, or being forced to defend against expensive litigation. An estimated 30 million workers—nearly one in five Americans—are subject to a noncompete.

Under the FTC’s new rule, existing noncompetes for the vast majority of workers will no longer be enforceable after the rule’s effective date. Existing noncompetes for senior executives - who represent less than 0.75% of workers - can remain in force under the FTC’s final rule, but employers are banned from entering into or attempting to enforce any new noncompetes, even if they involve senior executives. Employers will be required to provide notice to workers other than senior executives who are bound by an existing noncompete that they will not be enforcing any noncompetes against them.

In January 2023, the FTC issued a  proposed rule which was subject to a 90-day public comment period. The FTC received more than 26,000 comments on the proposed rule, with over 25,000 comments in support of the FTC’s proposed ban on noncompetes. The comments informed the FTC’s final rulemaking process, with the FTC carefully reviewing each comment and making changes to the proposed rule in response to the public’s feedback.

In the final rule, the Commission has determined that it is an unfair method of competition, and therefore a violation of Section 5 of the FTC Act, for employers to enter into noncompetes with workers and to enforce certain noncompetes.

The Commission found that noncompetes tend to negatively affect competitive conditions in labor markets by inhibiting efficient matching between workers and employers. The Commission also found that noncompetes tend to negatively affect competitive conditions in product and service markets, inhibiting new business formation and innovation. There is also evidence that noncompetes lead to increased market concentration and higher prices for consumers.

Alternatives to Noncompetes

The Commission found that employers have several alternatives to noncompetes that still enable firms to protect their investments without having to enforce a noncompete.

Trade secret laws and non-disclosure agreements (NDAs) both provide employers with well-established means to protect proprietary and other sensitive information. Researchers estimate that over 95% of workers with a noncompete already have an NDA.

The Commission also finds that instead of using noncompetes to lock in workers, employers that wish to retain employees can compete on the merits for the worker’s labor services by improving wages and working conditions.

Changes from the NPRM

Under the final rule, existing noncompetes for senior executives can remain in force. Employers, however, are prohibited from entering into or enforcing new noncompetes with senior executives. The final rule defines senior executives as workers earning more than $151,164 annually and who are in policy-making positions.

Additionally, the Commission has eliminated a provision in the proposed rule that would have required employers to legally modify existing noncompetes by formally rescinding them. That change will help to streamline compliance.

Instead, under the final rule, employers will simply have to provide notice to workers bound to an existing noncompete that the noncompete agreement will not be enforced against them in the future. To aid employers’ compliance with this requirement, the Commission has included model language in the final rule that employers can use to communicate to workers. 

The Commission vote to approve the issuance of the final rule was 3-2 with Commissioners Melissa Holyoak and Andrew N. Ferguson voting no. Commissioners Rebecca Kelly Slaughter , Alvaro Bedoya , Melissa Holyoak and Andrew N. Ferguson each issued separate statements. Chair Lina M. Khan will issue a separate statement.

The final rule will become effective 120 days after publication in the Federal Register.

Once the rule is effective, market participants can report information about a suspected violation of the rule to the Bureau of Competition by emailing  [email protected] . 

The Federal Trade Commission develops policy initiatives on issues that affect competition, consumers, and the U.S. economy. The FTC will never demand money, make threats, tell you to transfer money, or promise you a prize. Follow the  FTC on social media , read  consumer alerts  and the  business blog , and  sign up to get the latest FTC news and alerts .

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