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Guidance from Cite Them Right Online

Cite Them Right Online provides a few different types of guidance that can be relevant for Referencing Market Research and Data. The most straightforward is the guidance for referencing  Market research reports from online databases . Navigate to Harvard > Research > Reports > Market research reports from online databases to find the guidance.

Market Research Reports referenced in Harvard will resemble the following:

In-text citation: (MarketLine, 2019)

Reference List:

MarketLine (2019) 'United Kingdom - Gyms, Health & Fitness Clubs'. Available at: http://advantage.marketline.com/ (Accessed: 14 August 2019).

Using RefWorks to cite and reference company information

RefWorks   is an online reference management, writing and collaboration tool designed to help researchers at all levels gather, organise, store and share all types of information and to generate citations and bibliographies.

Market research references can be added to your RefWorks library so you can quickly and easily add it to your work, but RefWorks does not have as many standard formats for doing this as Cite Them Right Online. 

• Add a reference to market research using the + button in the web version of RefWorks.  
• Select the 'Report' option for the type of source you wish to reference. This will give you a set of boxes with various details to fill in such as 'Title', 'Date of Publication'.
• Using the guidance above from Cite Them Right Online , fill out the boxes with the information you have available. 
• The author of the data will be the publisher of the database that you got it from because market research databases publish their own information. So, for example, if you used Mintel, the author will be Mintel.

You can then click on the " symbol in RefWorks to check what your reference will look like when it appears in a bibliography. Make sure you have selected 'Cite Them Right - Harvard'.

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How To Cite Using APA Style (Videos)

Citing journal/magazine articles, citing web pages, citing books.

• Citing Business Databases

Citing Newspaper Articles

• Associations

American Psychological Association, or APA, style is commonly used in the social and behavioral sciences. Check out the resources and example citations on this page.

• Basics of APA Style Tutorial
• Citing References: APA Style [PDF]
• Purdue OWL - APA 7th ed. Formatting and Style Guide

This video playlist walks you through why to use APA (below), and how to cite books , articles , webpages , and business resources . Watch whichever ones you need!

Plagiarism involves taking credit for work that is not one's own. Below are some resources that can help you avoid plagiarism.

• Avoiding Academic Misconduct (UWW Dean of Students) [Word Doc]
• Plagiarism: Cut & Paste Doesn't Cut It [Interactive Tutorial]

With DOI Assigned:

Without a DOI Assigned:

Example: 

See other article citation examples here:  http://libguides.uww.edu/apa/articles

Basic webpage: .

Corporate author: 

See other website citation examples here:  http://libguides.uww.edu/apa/web

See other book citation examples here:  http://libguides.uww.edu/apa/books

For help citing all the unusual business databases, visit this page:  http://libguides.uww.edu/apa/business, free online: .

Note: If there is no author listed, the title of the article comes first, followed by the date.

Print, or from a database with no DOI: 

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Business Citations

Market research report, swot analysis, online industry profile/report, online company profile, apa-can't find what you're looking for.

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IMPORTANT NOTE: Citing Business Resources:

Although the APA provides clear instructions on how to cite standard publication types, some business-specific sources include unique information that is not addressed in APA instructions. Because of that, some of the examples and instructions on this page represent the B.D. Owens Library's interpretation of APA rules. The American Psychological Association maintains a  Style Blog  that addresses many frequently asked questions. 

If there is no official title, create a non-italicized description in square brackets (see section 9.22, page 292). The square brackets indicate to somebody else searching the database cannot use the exact words to search for the item, but can indicate how to locate similar information. 

For citing resources that are more standardized in business databases (Business Source Premier, Nexis Uni), click here .

REFERENCE (BUSINESS SOURCE PREMIER)

IN TEXT   

    ("Executive summary," 2009).

  MarketLine. (2019, November 29). NIKE Inc [SWOT analysis].  Business Source Premier .

      ( MarketLine, 2019). 

• Business Source Premier

REFERENCE  

  MarketLine. (2019, May). Industry profile: Mobile phones in the United States. Business Source Premier .

NOTE: Include the database name if content  only  appears in a particular database .  Include the retrieval date if content changes over time and versions of the page are not archived.  Multiple citations to different works from the one author from the same year are distinguished by assigning a, b, c, to the citations in text and also in the reference list. This is entered after the date.

MarketLine. (2020a, September). Marketline industry profile: Airlines in North America.  MarketLine.

MarketLine. (2020b, September). MarketLine industry profile: Airlines in the United States. MarketLine .

    (MarketLine, 2020a).

    (MarketLine, 2020b).

(see p. 296 section 9.30 and p. 319 examples 13 and 14 of the 7th edition)

NOTE: Include the database name if content only appears in a particular database . 

REFERENCE    

    MarketLine. (2019, October 25). Cerner Corporation [Company profile] .   Business Source Premier .

IN TEXT 

    (MarketLine, 2019).

NOTE: Include the database name if content only appears in a particular database .  Include the retrieval date if content changes over time and versions of the page are not archived.

    MarketLine. (2020, April 13). Walmart Inc [Company profile] .   MarketLine Advantage . Retrieved June 10, 2020, from https://advantage.marketline.com/Company/Profile/wal_mart_stores_inc?companyprofile

    ( MarketLine, 2020).

NOTE: Include the database name if content  only  appears in a particular database .  Include the retrieval date if content changes over time and versions of the page are not archived.

  Zoom Company Information.  (2020, January 2). Starbucks Corporation [Company profile]. Nexis Uni . Retrieved February 3, 2020, from https://advance.lexis.com/api/permalink/c876bb8e-2b26-4db3-bb27-c1317259766c/?context=1516831  

(Zoom Company Information, 2020). 

NOTE: Include the retrieval date if content changes over time and versions of the page are not archived.

REFERENCE (Lexisnexis)

Walmart Inc. (2020, October 2). Form 8-K [SEC Filings]. Nexis Uni . Retrieved October 6, 2020. 

     (Walmart Inc., 2020).

Get more APA examples :

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Citing Sources in APA Style

The purpose of citing is (1) to give credit to the original author, and (2) enable the reader to find the source. The American Psychological Association (APA) citation style is widely used in business school courses. You may find general guidelines in:

• APA Style Guide: OWL at Excelsior

The APA Style Manual doesn't address directly how to cite business-type sources from library databases, such as analyst reports, market research reports, industry profiles, etc. These sources may not have the same citation elements as books, journal articles, or open access websites:

• Reports often don't list a named individual author. In this case, the name of the publisher or organization that produced information will serve as a corporate author.
• URLs from the address bar for the content in library databases may be too long, inaccessible to readers because of a firewall, or expire after a session. If the URL is not accessible, use the name of a database.
• The APA Style Manual no longer requires the date the information is retrieved.

Suggested Format for Citing Reports in APA style:

Author, A. A., & Author, B. B. (Date of publication). Title of document . Publisher [optional]. Retrieved from [database name].

NOTE:   Use Publisher / Contributor / Organization Name:

• Only if this name is different from the database name and there is a named personal author
• As a corporate author at the beginning of the citation, if no personal author is listed

How to Build an APA Citation for a Report

You may easily create your own APA citation once you identify appropriate elements of a document for citing.

EXAMPLE 1: A report with a named author, produced by S&P Capital IQ McGraw Hill Financial and retrieved from the S&P Capital IQ NetAdvantage database

CITATION:  Holt, D. (2016, March). Industry surveys: Electronic equipment & instruments . Retrieved from S&P Capital IQ NetAdvantage.

EXAMPLE 2:  A report without a named author, produced by Euromonitor International, and retrieved from the Passport database.  The name of the publisher is used as a corporate author.

CITATION: Euromonitor International. (2016, September). Wearable electronics in the US . Retrieved from Passport database.

NOTE: Always check with your professor for specific citation guidelines.

Several libraries created examples for citing business sources in APA style:

• Citing Online Business Resources in APA Style: Bentley Library Guide
• Citing Business Databases in APA: University of North Carolina Greensboro
• Citing Business Resources APA Style: California State University Chico
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Document information as you research

Document information as you find it.

Pasting a bunch of links into a document and making sense of them later is counterproductive. It wastes  time if you have to re-scan and determine value later. Instead, highlight exactly what key information a source provides as you collect sources. Two other tips: 

• Use persistent or permalinks. Beware! Copying the URL from the browser won't always reopen the search results.
• Adopt a file-naming convention to make your documents easier to search
• Pro tip: Save your research with persistent links (PDF) Some business databases don't let you copy the URL and re-open the article later. This file shows how to access search results at a later time.
• Pro tip: Name your files smartly (PDF) Using a file-naming convention (FNC) will save time and reduce stress.

Recommended resources

• Document sources_Template (Google Sheets) Make a copy of this template into your Google Drive folder and document where you find evidence to cite later.

Choose a citation manager

Most business reports require 2 types of citations:  In-text citations  in the narrative and an alphabetized bibliography of citations  at the end.

Remember: The goal of every in-text citation is to direct your readers back to the bibliography so they can verify the information on their own. They work together.

Recommended citation generator

• ZoteroBib Helps you build a bibliography instantly from any computer or device, without creating an account or installing any software

Other help with APA style

• Doing Business Research: What information you need to cite JMU business databases Shows you how to create citations for common business databases, since citation generators often can't parse permalinks.
• Complete APA citation guide for COB 300 (PDF) Includes a sample of what a bibliography and in-text citations should look like in APA 7th.
• APA Formatting & Style Guide A thorough guide to APA style from Purdue University.
• Missing Pieces: How to Write an APA Style Reference Even Without All the Information The authors of the APA style manual answers questions about unique style problems, e.g., "How do I cite a mobile app?"
• JMU Writing Center Schedule an appointment or attend drop-in hours in the Student Success Center.
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Q. How do I cite a Market Research Report using the Harvard Style?

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Answered By: Sarah Roughley Barake Last Updated: Feb 16, 2023     Views: 18159

DISCOVER and the Library Catalogue have been replaced by Library Search . We're busy updating all of our links, but in the meantime, please use Library Search when searching for resources or managing your Library Account.

To reference market research reports in Harvard style, please see the appropriate section in Cite-Them-Right .

Please note you should always refer to any departmental/school guidelines you’ve been given.

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Home » References in Research – Types, Examples and Writing Guide

References in Research – Types, Examples and Writing Guide

Table of Contents

References in Research

Definition:

References in research are a list of sources that a researcher has consulted or cited while conducting their study. They are an essential component of any academic work, including research papers, theses, dissertations, and other scholarly publications.

Types of References

There are several types of references used in research, and the type of reference depends on the source of information being cited. The most common types of references include:

References to books typically include the author’s name, title of the book, publisher, publication date, and place of publication.

Example: Smith, J. (2018). The Art of Writing. Penguin Books.

Journal Articles

References to journal articles usually include the author’s name, title of the article, name of the journal, volume and issue number, page numbers, and publication date.

Example: Johnson, T. (2021). The Impact of Social Media on Mental Health. Journal of Psychology, 32(4), 87-94.

Web sources

References to web sources should include the author or organization responsible for the content, the title of the page, the URL, and the date accessed.

Example: World Health Organization. (2020). Coronavirus disease (COVID-19) advice for the public. Retrieved from https://www.who.int/emergencies/disease/novel-coronavirus-2019/advice-for-public

Conference Proceedings

References to conference proceedings should include the author’s name, title of the paper, name of the conference, location of the conference, date of the conference, and page numbers.

Example: Chen, S., & Li, J. (2019). The Future of AI in Education. Proceedings of the International Conference on Educational Technology, Beijing, China, July 15-17, pp. 67-78.

References to reports typically include the author or organization responsible for the report, title of the report, publication date, and publisher.

Example: United Nations. (2020). The Sustainable Development Goals Report. United Nations.

Formats of References

Some common Formates of References with their examples are as follows:

APA (American Psychological Association) Style

The APA (American Psychological Association) Style has specific guidelines for formatting references used in academic papers, articles, and books. Here are the different reference formats in APA style with examples:

Author, A. A. (Year of publication). Title of book. Publisher.

Example : Smith, J. K. (2005). The psychology of social interaction. Wiley-Blackwell.

Journal Article

Author, A. A., Author, B. B., & Author, C. C. (Year of publication). Title of article. Title of Journal, volume number(issue number), page numbers.

Example : Brown, L. M., Keating, J. G., & Jones, S. M. (2012). The role of social support in coping with stress among African American adolescents. Journal of Research on Adolescence, 22(1), 218-233.

Author, A. A. (Year of publication or last update). Title of page. Website name. URL.

Example : Centers for Disease Control and Prevention. (2020, December 11). COVID-19: How to protect yourself and others. https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/prevention.html

Magazine article

Author, A. A. (Year, Month Day of publication). Title of article. Title of Magazine, volume number(issue number), page numbers.

Example : Smith, M. (2019, March 11). The power of positive thinking. Psychology Today, 52(3), 60-65.

Newspaper article:

Author, A. A. (Year, Month Day of publication). Title of article. Title of Newspaper, page numbers.

Example: Johnson, B. (2021, February 15). New study shows benefits of exercise on mental health. The New York Times, A8.

Edited book

Editor, E. E. (Ed.). (Year of publication). Title of book. Publisher.

Example : Thompson, J. P. (Ed.). (2014). Social work in the 21st century. Sage Publications.

Chapter in an edited book:

Author, A. A. (Year of publication). Title of chapter. In E. E. Editor (Ed.), Title of book (pp. page numbers). Publisher.

Example : Johnson, K. S. (2018). The future of social work: Challenges and opportunities. In J. P. Thompson (Ed.), Social work in the 21st century (pp. 105-118). Sage Publications.

MLA (Modern Language Association) Style

The MLA (Modern Language Association) Style is a widely used style for writing academic papers and essays in the humanities. Here are the different reference formats in MLA style:

Author’s Last name, First name. Title of Book. Publisher, Publication year.

Example : Smith, John. The Psychology of Social Interaction. Wiley-Blackwell, 2005.

Journal article

Author’s Last name, First name. “Title of Article.” Title of Journal, volume number, issue number, Publication year, page numbers.

Example : Brown, Laura M., et al. “The Role of Social Support in Coping with Stress among African American Adolescents.” Journal of Research on Adolescence, vol. 22, no. 1, 2012, pp. 218-233.

Author’s Last name, First name. “Title of Webpage.” Website Name, Publication date, URL.

Example : Centers for Disease Control and Prevention. “COVID-19: How to Protect Yourself and Others.” CDC, 11 Dec. 2020, https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/prevention.html.

Author’s Last name, First name. “Title of Article.” Title of Magazine, Publication date, page numbers.

Example : Smith, Mary. “The Power of Positive Thinking.” Psychology Today, Mar. 2019, pp. 60-65.

Newspaper article

Author’s Last name, First name. “Title of Article.” Title of Newspaper, Publication date, page numbers.

Example : Johnson, Bob. “New Study Shows Benefits of Exercise on Mental Health.” The New York Times, 15 Feb. 2021, p. A8.

Editor’s Last name, First name, editor. Title of Book. Publisher, Publication year.

Example : Thompson, John P., editor. Social Work in the 21st Century. Sage Publications, 2014.

Chapter in an edited book

Author’s Last name, First name. “Title of Chapter.” Title of Book, edited by Editor’s First Name Last name, Publisher, Publication year, page numbers.

Example : Johnson, Karen S. “The Future of Social Work: Challenges and Opportunities.” Social Work in the 21st Century, edited by John P. Thompson, Sage Publications, 2014, pp. 105-118.

Chicago Manual of Style

The Chicago Manual of Style is a widely used style for writing academic papers, dissertations, and books in the humanities and social sciences. Here are the different reference formats in Chicago style:

Example : Smith, John K. The Psychology of Social Interaction. Wiley-Blackwell, 2005.

Author’s Last name, First name. “Title of Article.” Title of Journal volume number, no. issue number (Publication year): page numbers.

Example : Brown, Laura M., John G. Keating, and Sarah M. Jones. “The Role of Social Support in Coping with Stress among African American Adolescents.” Journal of Research on Adolescence 22, no. 1 (2012): 218-233.

Author’s Last name, First name. “Title of Webpage.” Website Name. Publication date. URL.

Example : Centers for Disease Control and Prevention. “COVID-19: How to Protect Yourself and Others.” CDC. December 11, 2020. https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/prevention.html.

Author’s Last name, First name. “Title of Article.” Title of Magazine, Publication date.

Example : Smith, Mary. “The Power of Positive Thinking.” Psychology Today, March 2019.

Author’s Last name, First name. “Title of Article.” Title of Newspaper, Publication date.

Example : Johnson, Bob. “New Study Shows Benefits of Exercise on Mental Health.” The New York Times, February 15, 2021.

Example : Thompson, John P., ed. Social Work in the 21st Century. Sage Publications, 2014.

Author’s Last name, First name. “Title of Chapter.” In Title of Book, edited by Editor’s First Name Last Name, page numbers. Publisher, Publication year.

Example : Johnson, Karen S. “The Future of Social Work: Challenges and Opportunities.” In Social Work in the 21st Century, edited by John P. Thompson, 105-118. Sage Publications, 2014.

Harvard Style

The Harvard Style, also known as the Author-Date System, is a widely used style for writing academic papers and essays in the social sciences. Here are the different reference formats in Harvard Style:

Author’s Last name, First name. Year of publication. Title of Book. Place of publication: Publisher.

Example : Smith, John. 2005. The Psychology of Social Interaction. Oxford: Wiley-Blackwell.

Author’s Last name, First name. Year of publication. “Title of Article.” Title of Journal volume number (issue number): page numbers.

Example: Brown, Laura M., John G. Keating, and Sarah M. Jones. 2012. “The Role of Social Support in Coping with Stress among African American Adolescents.” Journal of Research on Adolescence 22 (1): 218-233.

Author’s Last name, First name. Year of publication. “Title of Webpage.” Website Name. URL. Accessed date.

Example : Centers for Disease Control and Prevention. 2020. “COVID-19: How to Protect Yourself and Others.” CDC. https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/prevention.html. Accessed April 1, 2023.

Author’s Last name, First name. Year of publication. “Title of Article.” Title of Magazine, month and date of publication.

Example : Smith, Mary. 2019. “The Power of Positive Thinking.” Psychology Today, March 2019.

Author’s Last name, First name. Year of publication. “Title of Article.” Title of Newspaper, month and date of publication.

Example : Johnson, Bob. 2021. “New Study Shows Benefits of Exercise on Mental Health.” The New York Times, February 15, 2021.

Editor’s Last name, First name, ed. Year of publication. Title of Book. Place of publication: Publisher.

Example : Thompson, John P., ed. 2014. Social Work in the 21st Century. Thousand Oaks, CA: Sage Publications.

Author’s Last name, First name. Year of publication. “Title of Chapter.” In Title of Book, edited by Editor’s First Name Last Name, page numbers. Place of publication: Publisher.

Example : Johnson, Karen S. 2014. “The Future of Social Work: Challenges and Opportunities.” In Social Work in the 21st Century, edited by John P. Thompson, 105-118. Thousand Oaks, CA: Sage Publications.

Vancouver Style

The Vancouver Style, also known as the Uniform Requirements for Manuscripts Submitted to Biomedical Journals, is a widely used style for writing academic papers in the biomedical sciences. Here are the different reference formats in Vancouver Style:

Author’s Last name, First name. Title of Book. Edition number. Place of publication: Publisher; Year of publication.

Example : Smith, John K. The Psychology of Social Interaction. 2nd ed. Oxford: Wiley-Blackwell; 2005.

Author’s Last name, First name. Title of Article. Abbreviated Journal Title. Year of publication; volume number(issue number):page numbers.

Example : Brown LM, Keating JG, Jones SM. The Role of Social Support in Coping with Stress among African American Adolescents. J Res Adolesc. 2012;22(1):218-233.

Author’s Last name, First name. Title of Webpage. Website Name [Internet]. Publication date. [cited date]. Available from: URL.

Example : Centers for Disease Control and Prevention. COVID-19: How to Protect Yourself and Others [Internet]. 2020 Dec 11. [cited 2023 Apr 1]. Available from: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/prevention.html.

Author’s Last name, First name. Title of Article. Title of Magazine. Year of publication; month and day of publication:page numbers.

Example : Smith M. The Power of Positive Thinking. Psychology Today. 2019 Mar 1:32-35.

Author’s Last name, First name. Title of Article. Title of Newspaper. Year of publication; month and day of publication:page numbers.

Example : Johnson B. New Study Shows Benefits of Exercise on Mental Health. The New York Times. 2021 Feb 15:A4.

Editor’s Last name, First name, editor. Title of Book. Edition number. Place of publication: Publisher; Year of publication.

Example: Thompson JP, editor. Social Work in the 21st Century. 1st ed. Thousand Oaks, CA: Sage Publications; 2014.

Author’s Last name, First name. Title of Chapter. In: Editor’s Last name, First name, editor. Title of Book. Edition number. Place of publication: Publisher; Year of publication. page numbers.

Example : Johnson KS. The Future of Social Work: Challenges and Opportunities. In: Thompson JP, editor. Social Work in the 21st Century. 1st ed. Thousand Oaks, CA: Sage Publications; 2014. p. 105-118.

Turabian Style

Turabian style is a variation of the Chicago style used in academic writing, particularly in the fields of history and humanities. Here are the different reference formats in Turabian style:

Author’s Last name, First name. Title of Book. Place of publication: Publisher, Year of publication.

Example : Smith, John K. The Psychology of Social Interaction. Oxford: Wiley-Blackwell, 2005.

Author’s Last name, First name. “Title of Article.” Title of Journal volume number, no. issue number (Year of publication): page numbers.

Example : Brown, LM, Keating, JG, Jones, SM. “The Role of Social Support in Coping with Stress among African American Adolescents.” J Res Adolesc 22, no. 1 (2012): 218-233.

Author’s Last name, First name. “Title of Webpage.” Name of Website. Publication date. Accessed date. URL.

Example : Centers for Disease Control and Prevention. “COVID-19: How to Protect Yourself and Others.” CDC. December 11, 2020. Accessed April 1, 2023. https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/prevention.html.

Author’s Last name, First name. “Title of Article.” Title of Magazine, Month Day, Year of publication, page numbers.

Example : Smith, M. “The Power of Positive Thinking.” Psychology Today, March 1, 2019, 32-35.

Author’s Last name, First name. “Title of Article.” Title of Newspaper, Month Day, Year of publication.

Example : Johnson, B. “New Study Shows Benefits of Exercise on Mental Health.” The New York Times, February 15, 2021.

Editor’s Last name, First name, ed. Title of Book. Place of publication: Publisher, Year of publication.

Example : Thompson, JP, ed. Social Work in the 21st Century. Thousand Oaks, CA: Sage Publications, 2014.

Author’s Last name, First name. “Title of Chapter.” In Title of Book, edited by Editor’s Last name, First name, page numbers. Place of publication: Publisher, Year of publication.

Example : Johnson, KS. “The Future of Social Work: Challenges and Opportunities.” In Social Work in the 21st Century, edited by Thompson, JP, 105-118. Thousand Oaks, CA: Sage Publications, 2014.

IEEE (Institute of Electrical and Electronics Engineers) Style

IEEE (Institute of Electrical and Electronics Engineers) style is commonly used in engineering, computer science, and other technical fields. Here are the different reference formats in IEEE style:

Author’s Last name, First name. Book Title. Place of Publication: Publisher, Year of publication.

Example : Oppenheim, A. V., & Schafer, R. W. Discrete-Time Signal Processing. Upper Saddle River, NJ: Prentice Hall, 2010.

Author’s Last name, First name. “Title of Article.” Abbreviated Journal Title, vol. number, no. issue number, pp. page numbers, Month year of publication.

Example: Shannon, C. E. “A Mathematical Theory of Communication.” Bell System Technical Journal, vol. 27, no. 3, pp. 379-423, July 1948.

Conference paper

Author’s Last name, First name. “Title of Paper.” In Title of Conference Proceedings, Place of Conference, Date of Conference, pp. page numbers, Year of publication.

Example: Gupta, S., & Kumar, P. “An Improved System of Linear Discriminant Analysis for Face Recognition.” In Proceedings of the 2011 International Conference on Computer Science and Network Technology, Harbin, China, Dec. 2011, pp. 144-147.

Author’s Last name, First name. “Title of Webpage.” Name of Website. Date of publication or last update. Accessed date. URL.

Example : National Aeronautics and Space Administration. “Apollo 11.” NASA. July 20, 1969. Accessed April 1, 2023. https://www.nasa.gov/mission_pages/apollo/apollo11.html.

Technical report

Author’s Last name, First name. “Title of Report.” Name of Institution or Organization, Report number, Year of publication.

Example : Smith, J. R. “Development of a New Solar Panel Technology.” National Renewable Energy Laboratory, NREL/TP-6A20-51645, 2011.

Author’s Last name, First name. “Title of Patent.” Patent number, Issue date.

Example : Suzuki, H. “Method of Producing Carbon Nanotubes.” US Patent 7,151,019, December 19, 2006.

Standard Title. Standard number, Publication date.

Example : IEEE Standard for Floating-Point Arithmetic. IEEE Std 754-2008, August 29, 2008

ACS (American Chemical Society) Style

ACS (American Chemical Society) style is commonly used in chemistry and related fields. Here are the different reference formats in ACS style:

Author’s Last name, First name; Author’s Last name, First name. Title of Article. Abbreviated Journal Title Year, Volume, Page Numbers.

Example : Wang, Y.; Zhao, X.; Cui, Y.; Ma, Y. Facile Preparation of Fe3O4/graphene Composites Using a Hydrothermal Method for High-Performance Lithium Ion Batteries. ACS Appl. Mater. Interfaces 2012, 4, 2715-2721.

Author’s Last name, First name. Book Title; Publisher: Place of Publication, Year of Publication.

Example : Carey, F. A. Organic Chemistry; McGraw-Hill: New York, 2008.

Author’s Last name, First name. Chapter Title. In Book Title; Editor’s Last name, First name, Ed.; Publisher: Place of Publication, Year of Publication; Volume number, Chapter number, Page Numbers.

Example : Grossman, R. B. Analytical Chemistry of Aerosols. In Aerosol Measurement: Principles, Techniques, and Applications; Baron, P. A.; Willeke, K., Eds.; Wiley-Interscience: New York, 2001; Chapter 10, pp 395-424.

Author’s Last name, First name. Title of Webpage. Website Name, URL (accessed date).

Example : National Institute of Standards and Technology. Atomic Spectra Database. https://www.nist.gov/pml/atomic-spectra-database (accessed April 1, 2023).

Author’s Last name, First name. Patent Number. Patent Date.

Example : Liu, Y.; Huang, H.; Chen, H.; Zhang, W. US Patent 9,999,999, December 31, 2022.

Author’s Last name, First name; Author’s Last name, First name. Title of Article. In Title of Conference Proceedings, Publisher: Place of Publication, Year of Publication; Volume Number, Page Numbers.

Example : Jia, H.; Xu, S.; Wu, Y.; Wu, Z.; Tang, Y.; Huang, X. Fast Adsorption of Organic Pollutants by Graphene Oxide. In Proceedings of the 15th International Conference on Environmental Science and Technology, American Chemical Society: Washington, DC, 2017; Volume 1, pp 223-228.

AMA (American Medical Association) Style

AMA (American Medical Association) style is commonly used in medical and scientific fields. Here are the different reference formats in AMA style:

Author’s Last name, First name. Article Title. Journal Abbreviation. Year; Volume(Issue):Page Numbers.

Example : Jones, R. A.; Smith, B. C. The Role of Vitamin D in Maintaining Bone Health. JAMA. 2019;321(17):1765-1773.

Author’s Last name, First name. Book Title. Edition number. Place of Publication: Publisher; Year.

Example : Guyton, A. C.; Hall, J. E. Textbook of Medical Physiology. 13th ed. Philadelphia, PA: Saunders; 2015.

Author’s Last name, First name. Chapter Title. In: Editor’s Last name, First name, ed. Book Title. Edition number. Place of Publication: Publisher; Year: Page Numbers.

Example: Rajakumar, K. Vitamin D and Bone Health. In: Holick, M. F., ed. Vitamin D: Physiology, Molecular Biology, and Clinical Applications. 2nd ed. New York, NY: Springer; 2010:211-222.

Author’s Last name, First name. Webpage Title. Website Name. URL. Published date. Updated date. Accessed date.

Example : National Cancer Institute. Breast Cancer Prevention (PDQ®)–Patient Version. National Cancer Institute. https://www.cancer.gov/types/breast/patient/breast-prevention-pdq. Published October 11, 2022. Accessed April 1, 2023.

Author’s Last name, First name. Conference presentation title. In: Conference Title; Conference Date; Place of Conference.

Example : Smith, J. R. Vitamin D and Bone Health: A Meta-Analysis. In: Proceedings of the Annual Meeting of the American Society for Bone and Mineral Research; September 20-23, 2022; San Diego, CA.

Thesis or dissertation

Author’s Last name, First name. Title of Thesis or Dissertation. Degree level [Doctoral dissertation or Master’s thesis]. University Name; Year.

Example : Wilson, S. A. The Effects of Vitamin D Supplementation on Bone Health in Postmenopausal Women [Doctoral dissertation]. University of California, Los Angeles; 2018.

ASCE (American Society of Civil Engineers) Style

The ASCE (American Society of Civil Engineers) style is commonly used in civil engineering fields. Here are the different reference formats in ASCE style:

Author’s Last name, First name. “Article Title.” Journal Title, volume number, issue number (year): page numbers. DOI or URL (if available).

Example : Smith, J. R. “Evaluation of the Effectiveness of Sustainable Drainage Systems in Urban Areas.” Journal of Environmental Engineering, vol. 146, no. 3 (2020): 04020010. https://doi.org/10.1061/(ASCE)EE.1943-7870.0001668.

Example : McCuen, R. H. Hydrologic Analysis and Design. 4th ed. Upper Saddle River, NJ: Pearson Education; 2013.

Author’s Last name, First name. “Chapter Title.” In: Editor’s Last name, First name, ed. Book Title. Edition number. Place of Publication: Publisher; Year: page numbers.

Example : Maidment, D. R. “Floodplain Management in the United States.” In: Shroder, J. F., ed. Treatise on Geomorphology. San Diego, CA: Academic Press; 2013: 447-460.

Author’s Last name, First name. “Paper Title.” In: Conference Title; Conference Date; Location. Place of Publication: Publisher; Year: page numbers.

Example: Smith, J. R. “Sustainable Drainage Systems for Urban Areas.” In: Proceedings of the ASCE International Conference on Sustainable Infrastructure; November 6-9, 2019; Los Angeles, CA. Reston, VA: American Society of Civil Engineers; 2019: 156-163.

Author’s Last name, First name. “Report Title.” Report number. Place of Publication: Publisher; Year.

Example : U.S. Army Corps of Engineers. “Hurricane Sandy Coastal Risk Reduction Program, New York and New Jersey.” Report No. P-15-001. Washington, DC: U.S. Army Corps of Engineers; 2015.

CSE (Council of Science Editors) Style

The CSE (Council of Science Editors) style is commonly used in the scientific and medical fields. Here are the different reference formats in CSE style:

Author’s Last name, First Initial. Middle Initial. “Article Title.” Journal Title. Year;Volume(Issue):Page numbers.

Example : Smith, J.R. “Evaluation of the Effectiveness of Sustainable Drainage Systems in Urban Areas.” Journal of Environmental Engineering. 2020;146(3):04020010.

Author’s Last name, First Initial. Middle Initial. Book Title. Edition number. Place of Publication: Publisher; Year.

Author’s Last name, First Initial. Middle Initial. “Chapter Title.” In: Editor’s Last name, First Initial. Middle Initial., ed. Book Title. Edition number. Place of Publication: Publisher; Year:Page numbers.

Author’s Last name, First Initial. Middle Initial. “Paper Title.” In: Conference Title; Conference Date; Location. Place of Publication: Publisher; Year.

Example : Smith, J.R. “Sustainable Drainage Systems for Urban Areas.” In: Proceedings of the ASCE International Conference on Sustainable Infrastructure; November 6-9, 2019; Los Angeles, CA. Reston, VA: American Society of Civil Engineers; 2019.

Author’s Last name, First Initial. Middle Initial. “Report Title.” Report number. Place of Publication: Publisher; Year.

Bluebook Style

The Bluebook style is commonly used in the legal field for citing legal documents and sources. Here are the different reference formats in Bluebook style:

Case citation

Case name, volume source page (Court year).

Example : Brown v. Board of Education, 347 U.S. 483 (1954).

Statute citation

Name of Act, volume source § section number (year).

Example : Clean Air Act, 42 U.S.C. § 7401 (1963).

Regulation citation

Name of regulation, volume source § section number (year).

Example: Clean Air Act, 40 C.F.R. § 52.01 (2019).

Book citation

Author’s Last name, First Initial. Middle Initial. Book Title. Edition number (if applicable). Place of Publication: Publisher; Year.

Example: Smith, J.R. Legal Writing and Analysis. 3rd ed. New York, NY: Aspen Publishers; 2015.

Journal article citation

Author’s Last name, First Initial. Middle Initial. “Article Title.” Journal Title. Volume number (year): first page-last page.

Example: Garcia, C. “The Right to Counsel: An International Comparison.” International Journal of Legal Information. 43 (2015): 63-94.

Website citation

Author’s Last name, First Initial. Middle Initial. “Page Title.” Website Title. URL (accessed month day, year).

Example : United Nations. “Universal Declaration of Human Rights.” United Nations. https://www.un.org/en/universal-declaration-human-rights/ (accessed January 3, 2023).

Oxford Style

The Oxford style, also known as the Oxford referencing system or the documentary-note citation system, is commonly used in the humanities, including literature, history, and philosophy. Here are the different reference formats in Oxford style:

Author’s Last name, First name. Book Title. Place of Publication: Publisher, Year of Publication.

Example : Smith, John. The Art of Writing. New York: Penguin, 2020.

Author’s Last name, First name. “Article Title.” Journal Title volume, no. issue (year): page range.

Example: Garcia, Carlos. “The Role of Ethics in Philosophy.” Philosophy Today 67, no. 3 (2019): 53-68.

Chapter in an edited book citation

Author’s Last name, First name. “Chapter Title.” In Book Title, edited by Editor’s Name, page range. Place of Publication: Publisher, Year of Publication.

Example : Lee, Mary. “Feminism in the 21st Century.” In The Oxford Handbook of Feminism, edited by Jane Smith, 51-69. Oxford: Oxford University Press, 2018.

Author’s Last name, First name. “Page Title.” Website Title. URL (accessed day month year).

Example : Jones, David. “The Importance of Learning Languages.” Oxford Language Center. https://www.oxfordlanguagecenter.com/importance-of-learning-languages/ (accessed 3 January 2023).

Dissertation or thesis citation

Author’s Last name, First name. “Title of Dissertation/Thesis.” PhD diss., University Name, Year of Publication.

Example : Brown, Susan. “The Art of Storytelling in American Literature.” PhD diss., University of Oxford, 2020.

Newspaper article citation

Author’s Last name, First name. “Article Title.” Newspaper Title, Month Day, Year.

Example : Robinson, Andrew. “New Developments in Climate Change Research.” The Guardian, September 15, 2022.

AAA (American Anthropological Association) Style

The American Anthropological Association (AAA) style is commonly used in anthropology research papers and journals. Here are the different reference formats in AAA style:

Author’s Last name, First name. Year of Publication. Book Title. Place of Publication: Publisher.

Example : Smith, John. 2019. The Anthropology of Food. New York: Routledge.

Author’s Last name, First name. Year of Publication. “Article Title.” Journal Title volume, no. issue: page range.

Example : Garcia, Carlos. 2021. “The Role of Ethics in Anthropology.” American Anthropologist 123, no. 2: 237-251.

Author’s Last name, First name. Year of Publication. “Chapter Title.” In Book Title, edited by Editor’s Name, page range. Place of Publication: Publisher.

Example: Lee, Mary. 2018. “Feminism in Anthropology.” In The Oxford Handbook of Feminism, edited by Jane Smith, 51-69. Oxford: Oxford University Press.

Author’s Last name, First name. Year of Publication. “Page Title.” Website Title. URL (accessed day month year).

Example : Jones, David. 2020. “The Importance of Learning Languages.” Oxford Language Center. https://www.oxfordlanguagecenter.com/importance-of-learning-languages/ (accessed January 3, 2023).

Author’s Last name, First name. Year of Publication. “Title of Dissertation/Thesis.” PhD diss., University Name.

Example : Brown, Susan. 2022. “The Art of Storytelling in Anthropology.” PhD diss., University of California, Berkeley.

Author’s Last name, First name. Year of Publication. “Article Title.” Newspaper Title, Month Day.

Example : Robinson, Andrew. 2021. “New Developments in Anthropology Research.” The Guardian, September 15.

AIP (American Institute of Physics) Style

The American Institute of Physics (AIP) style is commonly used in physics research papers and journals. Here are the different reference formats in AIP style:

Example : Johnson, S. D. 2021. “Quantum Computing and Information.” Journal of Applied Physics 129, no. 4: 043102.

Example : Feynman, Richard. 2018. The Feynman Lectures on Physics. New York: Basic Books.

Example : Jones, David. 2020. “The Future of Quantum Computing.” In The Handbook of Physics, edited by John Smith, 125-136. Oxford: Oxford University Press.

Conference proceedings citation

Author’s Last name, First name. Year of Publication. “Title of Paper.” Proceedings of Conference Name, date and location: page range. Place of Publication: Publisher.

Example : Chen, Wei. 2019. “The Applications of Nanotechnology in Solar Cells.” Proceedings of the 8th International Conference on Nanotechnology, July 15-17, Tokyo, Japan: 224-229. New York: AIP Publishing.

Example : American Institute of Physics. 2022. “About AIP Publishing.” AIP Publishing. https://publishing.aip.org/about-aip-publishing/ (accessed January 3, 2023).

Patent citation

Author’s Last name, First name. Year of Publication. Patent Number.

Example : Smith, John. 2018. US Patent 9,873,644.

References Writing Guide

Here are some general guidelines for writing references:

• Follow the citation style guidelines: Different disciplines and journals may require different citation styles (e.g., APA, MLA, Chicago). It is important to follow the specific guidelines for the citation style required.
• Include all necessary information : Each citation should include enough information for readers to locate the source. For example, a journal article citation should include the author(s), title of the article, journal title, volume number, issue number, page numbers, and publication year.
• Use proper formatting: Citation styles typically have specific formatting requirements for different types of sources. Make sure to follow the proper formatting for each citation.
• Order citations alphabetically: If listing multiple sources, they should be listed alphabetically by the author’s last name.
• Be consistent: Use the same citation style throughout the entire paper or project.
• Check for accuracy: Double-check all citations to ensure accuracy, including correct spelling of author names and publication information.
• Use reputable sources: When selecting sources to cite, choose reputable and authoritative sources. Avoid sources that are biased or unreliable.
• Include all sources: Make sure to include all sources used in the research, including those that were not directly quoted but still informed the work.
• Use online tools : There are online tools available (e.g., citation generators) that can help with formatting and organizing references.

Purpose of References in Research

References in research serve several purposes:

• To give credit to the original authors or sources of information used in the research. It is important to acknowledge the work of others and avoid plagiarism.
• To provide evidence for the claims made in the research. References can support the arguments, hypotheses, or conclusions presented in the research by citing relevant studies, data, or theories.
• To allow readers to find and verify the sources used in the research. References provide the necessary information for readers to locate and access the sources cited in the research, which allows them to evaluate the quality and reliability of the information presented.
• To situate the research within the broader context of the field. References can show how the research builds on or contributes to the existing body of knowledge, and can help readers to identify gaps in the literature that the research seeks to address.

Importance of References in Research

References play an important role in research for several reasons:

• Credibility : By citing authoritative sources, references lend credibility to the research and its claims. They provide evidence that the research is based on a sound foundation of knowledge and has been carefully researched.
• Avoidance of Plagiarism : References help researchers avoid plagiarism by giving credit to the original authors or sources of information. This is important for ethical reasons and also to avoid legal repercussions.
• Reproducibility : References allow others to reproduce the research by providing detailed information on the sources used. This is important for verification of the research and for others to build on the work.
• Context : References provide context for the research by situating it within the broader body of knowledge in the field. They help researchers to understand where their work fits in and how it builds on or contributes to existing knowledge.
• Evaluation : References provide a means for others to evaluate the research by allowing them to assess the quality and reliability of the sources used.

Advantages of References in Research

There are several advantages of including references in research:

• Acknowledgment of Sources: Including references gives credit to the authors or sources of information used in the research. This is important to acknowledge the original work and avoid plagiarism.
• Evidence and Support : References can provide evidence to support the arguments, hypotheses, or conclusions presented in the research. This can add credibility and strength to the research.
• Reproducibility : References provide the necessary information for others to reproduce the research. This is important for the verification of the research and for others to build on the work.
• Context : References can help to situate the research within the broader body of knowledge in the field. This helps researchers to understand where their work fits in and how it builds on or contributes to existing knowledge.
• Evaluation : Including references allows others to evaluate the research by providing a means to assess the quality and reliability of the sources used.
• Ongoing Conversation: References allow researchers to engage in ongoing conversations and debates within their fields. They can show how the research builds on or contributes to the existing body of knowledge.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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How to Do Market Research: The Complete Guide

Learn how to do market research with this step-by-step guide, complete with templates, tools and real-world examples.

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What are your customers’ needs? How does your product compare to the competition? What are the emerging trends and opportunities in your industry? If these questions keep you up at night, it’s time to conduct market research.

Market research plays a pivotal role in your ability to stay competitive and relevant, helping you anticipate shifts in consumer behavior and industry dynamics. It involves gathering these insights using a wide range of techniques, from surveys and interviews to data analysis and observational studies.

In this guide, we’ll explore why market research is crucial, the various types of market research, the methods used in data collection, and how to effectively conduct market research to drive informed decision-making and success.

What is market research?

Market research is the systematic process of gathering, analyzing and interpreting information about a specific market or industry. The purpose of market research is to offer valuable insight into the preferences and behaviors of your target audience, and anticipate shifts in market trends and the competitive landscape. This information helps you make data-driven decisions, develop effective strategies for your business, and maximize your chances of long-term growth.

Why is market research important? 

By understanding the significance of market research, you can make sure you’re asking the right questions and using the process to your advantage. Some of the benefits of market research include:

• Informed decision-making: Market research provides you with the data and insights you need to make smart decisions for your business. It helps you identify opportunities, assess risks and tailor your strategies to meet the demands of the market. Without market research, decisions are often based on assumptions or guesswork, leading to costly mistakes.
• Customer-centric approach: A cornerstone of market research involves developing a deep understanding of customer needs and preferences. This gives you valuable insights into your target audience, helping you develop products, services and marketing campaigns that resonate with your customers.
• Competitive advantage: By conducting market research, you’ll gain a competitive edge. You’ll be able to identify gaps in the market, analyze competitor strengths and weaknesses, and position your business strategically. This enables you to create unique value propositions, differentiate yourself from competitors, and seize opportunities that others may overlook.
• Risk mitigation: Market research helps you anticipate market shifts and potential challenges. By identifying threats early, you can proactively adjust their strategies to mitigate risks and respond effectively to changing circumstances. This proactive approach is particularly valuable in volatile industries.
• Resource optimization: Conducting market research allows organizations to allocate their time, money and resources more efficiently. It ensures that investments are made in areas with the highest potential return on investment, reducing wasted resources and improving overall business performance.
• Adaptation to market trends: Markets evolve rapidly, driven by technological advancements, cultural shifts and changing consumer attitudes. Market research ensures that you stay ahead of these trends and adapt your offerings accordingly so you can avoid becoming obsolete. 

As you can see, market research empowers businesses to make data-driven decisions, cater to customer needs, outperform competitors, mitigate risks, optimize resources and stay agile in a dynamic marketplace. These benefits make it a huge industry; the global market research services market is expected to grow from $76.37 billion in 2021 to $108.57 billion in 2026 . Now, let’s dig into the different types of market research that can help you achieve these benefits.

Types of market research 

• Qualitative research
• Quantitative research
• Exploratory research
• Descriptive research
• Causal research
• Cross-sectional research
• Longitudinal research

Despite its advantages, 23% of organizations don’t have a clear market research strategy. Part of developing a strategy involves choosing the right type of market research for your business goals. The most commonly used approaches include:

1. Qualitative research

Qualitative research focuses on understanding the underlying motivations, attitudes and perceptions of individuals or groups. It is typically conducted through techniques like in-depth interviews, focus groups and content analysis — methods we’ll discuss further in the sections below. Qualitative research provides rich, nuanced insights that can inform product development, marketing strategies and brand positioning.

2. Quantitative research

Quantitative research, in contrast to qualitative research, involves the collection and analysis of numerical data, often through surveys, experiments and structured questionnaires. This approach allows for statistical analysis and the measurement of trends, making it suitable for large-scale market studies and hypothesis testing. While it’s worthwhile using a mix of qualitative and quantitative research, most businesses prioritize the latter because it is scientific, measurable and easily replicated across different experiments.

3. Exploratory research

Whether you’re conducting qualitative or quantitative research or a mix of both, exploratory research is often the first step. Its primary goal is to help you understand a market or problem so you can gain insights and identify potential issues or opportunities. This type of market research is less structured and is typically conducted through open-ended interviews, focus groups or secondary data analysis. Exploratory research is valuable when entering new markets or exploring new product ideas.

4. Descriptive research

As its name implies, descriptive research seeks to describe a market, population or phenomenon in detail. It involves collecting and summarizing data to answer questions about audience demographics and behaviors, market size, and current trends. Surveys, observational studies and content analysis are common methods used in descriptive research. 

5. Causal research

Causal research aims to establish cause-and-effect relationships between variables. It investigates whether changes in one variable result in changes in another. Experimental designs, A/B testing and regression analysis are common causal research methods. This sheds light on how specific marketing strategies or product changes impact consumer behavior.

6. Cross-sectional research

Cross-sectional market research involves collecting data from a sample of the population at a single point in time. It is used to analyze differences, relationships or trends among various groups within a population. Cross-sectional studies are helpful for market segmentation, identifying target audiences and assessing market trends at a specific moment.

7. Longitudinal research

Longitudinal research, in contrast to cross-sectional research, collects data from the same subjects over an extended period. This allows for the analysis of trends, changes and developments over time. Longitudinal studies are useful for tracking long-term developments in consumer preferences, brand loyalty and market dynamics.

Each type of market research has its strengths and weaknesses, and the method you choose depends on your specific research goals and the depth of understanding you’re aiming to achieve. In the following sections, we’ll delve into primary and secondary research approaches and specific research methods.

Primary vs. secondary market research

Market research of all types can be broadly categorized into two main approaches: primary research and secondary research. By understanding the differences between these approaches, you can better determine the most appropriate research method for your specific goals.

Primary market research 

Primary research involves the collection of original data straight from the source. Typically, this involves communicating directly with your target audience — through surveys, interviews, focus groups and more — to gather information. Here are some key attributes of primary market research:

• Customized data: Primary research provides data that is tailored to your research needs. You design a custom research study and gather information specific to your goals.
• Up-to-date insights: Because primary research involves communicating with customers, the data you collect reflects the most current market conditions and consumer behaviors.
• Time-consuming and resource-intensive: Despite its advantages, primary research can be labor-intensive and costly, especially when dealing with large sample sizes or complex study designs. Whether you hire a market research consultant, agency or use an in-house team, primary research studies consume a large amount of resources and time.

Secondary market research 

Secondary research, on the other hand, involves analyzing data that has already been compiled by third-party sources, such as online research tools, databases, news sites, industry reports and academic studies.

Here are the main characteristics of secondary market research:

• Cost-effective: Secondary research is generally more cost-effective than primary research since it doesn’t require building a research plan from scratch. You and your team can look at databases, websites and publications on an ongoing basis, without needing to design a custom experiment or hire a consultant. 
• Leverages multiple sources: Data tools and software extract data from multiple places across the web, and then consolidate that information within a single platform. This means you’ll get a greater amount of data and a wider scope from secondary research.
• Quick to access: You can access a wide range of information rapidly — often in seconds — if you’re using online research tools and databases. Because of this, you can act on insights sooner, rather than taking the time to develop an experiment. 

So, when should you use primary vs. secondary research? In practice, many market research projects incorporate both primary and secondary research to take advantage of the strengths of each approach.

One rule of thumb is to focus on secondary research to obtain background information, market trends or industry benchmarks. It is especially valuable for conducting preliminary research, competitor analysis, or when time and budget constraints are tight. Then, if you still have knowledge gaps or need to answer specific questions unique to your business model, use primary research to create a custom experiment. 

Market research methods

• Surveys and questionnaires
• Focus groups
• Observational research
• Online research tools
• Experiments
• Content analysis
• Ethnographic research

How do primary and secondary research approaches translate into specific research methods? Let’s take a look at the different ways you can gather data: 

1. Surveys and questionnaires

Surveys and questionnaires are popular methods for collecting structured data from a large number of respondents. They involve a set of predetermined questions that participants answer. Surveys can be conducted through various channels, including online tools, telephone interviews and in-person or online questionnaires. They are useful for gathering quantitative data and assessing customer demographics, opinions, preferences and needs. On average, customer surveys have a 33% response rate , so keep that in mind as you consider your sample size.

2. Interviews

Interviews are in-depth conversations with individuals or groups to gather qualitative insights. They can be structured (with predefined questions) or unstructured (with open-ended discussions). Interviews are valuable for exploring complex topics, uncovering motivations and obtaining detailed feedback. 

3. Focus groups

The most common primary research methods are in-depth webcam interviews and focus groups. Focus groups are a small gathering of participants who discuss a specific topic or product under the guidance of a moderator. These discussions are valuable for primary market research because they reveal insights into consumer attitudes, perceptions and emotions. Focus groups are especially useful for idea generation, concept testing and understanding group dynamics within your target audience.

4. Observational research

Observational research involves observing and recording participant behavior in a natural setting. This method is particularly valuable when studying consumer behavior in physical spaces, such as retail stores or public places. In some types of observational research, participants are aware you’re watching them; in other cases, you discreetly watch consumers without their knowledge, as they use your product. Either way, observational research provides firsthand insights into how people interact with products or environments.

5. Online research tools

You and your team can do your own secondary market research using online tools. These tools include data prospecting platforms and databases, as well as online surveys, social media listening, web analytics and sentiment analysis platforms. They help you gather data from online sources, monitor industry trends, track competitors, understand consumer preferences and keep tabs on online behavior. We’ll talk more about choosing the right market research tools in the sections that follow.

6. Experiments

Market research experiments are controlled tests of variables to determine causal relationships. While experiments are often associated with scientific research, they are also used in market research to assess the impact of specific marketing strategies, product features, or pricing and packaging changes.

7. Content analysis

Content analysis involves the systematic examination of textual, visual or audio content to identify patterns, themes and trends. It’s commonly applied to customer reviews, social media posts and other forms of online content to analyze consumer opinions and sentiments.

8. Ethnographic research

Ethnographic research immerses researchers into the daily lives of consumers to understand their behavior and culture. This method is particularly valuable when studying niche markets or exploring the cultural context of consumer choices.

How to do market research

• Set clear objectives
• Identify your target audience
• Choose your research methods
• Use the right market research tools
• Collect data
• Analyze data 
• Interpret your findings
• Identify opportunities and challenges
• Make informed business decisions
• Monitor and adapt

Now that you have gained insights into the various market research methods at your disposal, let’s delve into the practical aspects of how to conduct market research effectively. Here’s a quick step-by-step overview, from defining objectives to monitoring market shifts.

1. Set clear objectives

When you set clear and specific goals, you’re essentially creating a compass to guide your research questions and methodology. Start by precisely defining what you want to achieve. Are you launching a new product and want to understand its viability in the market? Are you evaluating customer satisfaction with a product redesign? 

Start by creating SMART goals — objectives that are specific, measurable, achievable, relevant and time-bound. Not only will this clarify your research focus from the outset, but it will also help you track progress and benchmark your success throughout the process. 

You should also consult with key stakeholders and team members to ensure alignment on your research objectives before diving into data collecting. This will help you gain diverse perspectives and insights that will shape your research approach.

2. Identify your target audience

Next, you’ll need to pinpoint your target audience to determine who should be included in your research. Begin by creating detailed buyer personas or stakeholder profiles. Consider demographic factors like age, gender, income and location, but also delve into psychographics, such as interests, values and pain points.

The more specific your target audience, the more accurate and actionable your research will be. Additionally, segment your audience if your research objectives involve studying different groups, such as current customers and potential leads.

If you already have existing customers, you can also hold conversations with them to better understand your target market. From there, you can refine your buyer personas and tailor your research methods accordingly.

3. Choose your research methods

Selecting the right research methods is crucial for gathering high-quality data. Start by considering the nature of your research objectives. If you’re exploring consumer preferences, surveys and interviews can provide valuable insights. For in-depth understanding, focus groups or observational research might be suitable. Consider using a mix of quantitative and qualitative methods to gain a well-rounded perspective. 

You’ll also need to consider your budget. Think about what you can realistically achieve using the time and resources available to you. If you have a fairly generous budget, you may want to try a mix of primary and secondary research approaches. If you’re doing market research for a startup , on the other hand, chances are your budget is somewhat limited. If that’s the case, try addressing your goals with secondary research tools before investing time and effort in a primary research study. 

4. Use the right market research tools

Whether you’re conducting primary or secondary research, you’ll need to choose the right tools. These can help you do anything from sending surveys to customers to monitoring trends and analyzing data. Here are some examples of popular market research tools:

• Market research software: Crunchbase is a platform that provides best-in-class company data, making it valuable for market research on growing companies and industries. You can use Crunchbase to access trusted, first-party funding data, revenue data, news and firmographics, enabling you to monitor industry trends and understand customer needs.

• Survey and questionnaire tools: SurveyMonkey is a widely used online survey platform that allows you to create, distribute and analyze surveys. Google Forms is a free tool that lets you create surveys and collect responses through Google Drive.
• Data analysis software: Microsoft Excel and Google Sheets are useful for conducting statistical analyses. SPSS is a powerful statistical analysis software used for data processing, analysis and reporting.
• Social listening tools: Brandwatch is a social listening and analytics platform that helps you monitor social media conversations, track sentiment and analyze trends. Mention is a media monitoring tool that allows you to track mentions of your brand, competitors and keywords across various online sources.
• Data visualization platforms: Tableau is a data visualization tool that helps you create interactive and shareable dashboards and reports. Power BI by Microsoft is a business analytics tool for creating interactive visualizations and reports.

5. Collect data

There’s an infinite amount of data you could be collecting using these tools, so you’ll need to be intentional about going after the data that aligns with your research goals. Implement your chosen research methods, whether it’s distributing surveys, conducting interviews or pulling from secondary research platforms. Pay close attention to data quality and accuracy, and stick to a standardized process to streamline data capture and reduce errors. 

6. Analyze data

Once data is collected, you’ll need to analyze it systematically. Use statistical software or analysis tools to identify patterns, trends and correlations. For qualitative data, employ thematic analysis to extract common themes and insights. Visualize your findings with charts, graphs and tables to make complex data more understandable.

If you’re not proficient in data analysis, consider outsourcing or collaborating with a data analyst who can assist in processing and interpreting your data accurately.

7. Interpret your findings

Interpreting your market research findings involves understanding what the data means in the context of your objectives. Are there significant trends that uncover the answers to your initial research questions? Consider the implications of your findings on your business strategy. It’s essential to move beyond raw data and extract actionable insights that inform decision-making.

Hold a cross-functional meeting or workshop with relevant team members to collectively interpret the findings. Different perspectives can lead to more comprehensive insights and innovative solutions.

8. Identify opportunities and challenges

Use your research findings to identify potential growth opportunities and challenges within your market. What segments of your audience are underserved or overlooked? Are there emerging trends you can capitalize on? Conversely, what obstacles or competitors could hinder your progress?

Lay out this information in a clear and organized way by conducting a SWOT analysis, which stands for strengths, weaknesses, opportunities and threats. Jot down notes for each of these areas to provide a structured overview of gaps and hurdles in the market.

9. Make informed business decisions

Market research is only valuable if it leads to informed decisions for your company. Based on your insights, devise actionable strategies and initiatives that align with your research objectives. Whether it’s refining your product, targeting new customer segments or adjusting pricing, ensure your decisions are rooted in the data.

At this point, it’s also crucial to keep your team aligned and accountable. Create an action plan that outlines specific steps, responsibilities and timelines for implementing the recommendations derived from your research. 

10. Monitor and adapt

Market research isn’t a one-time activity; it’s an ongoing process. Continuously monitor market conditions, customer behaviors and industry trends. Set up mechanisms to collect real-time data and feedback. As you gather new information, be prepared to adapt your strategies and tactics accordingly. Regularly revisiting your research ensures your business remains agile and reflects changing market dynamics and consumer preferences.

Online market research sources

As you go through the steps above, you’ll want to turn to trusted, reputable sources to gather your data. Here’s a list to get you started:

• Crunchbase: As mentioned above, Crunchbase is an online platform with an extensive dataset, allowing you to access in-depth insights on market trends, consumer behavior and competitive analysis. You can also customize your search options to tailor your research to specific industries, geographic regions or customer personas.

• Academic databases: Academic databases, such as ProQuest and JSTOR , are treasure troves of scholarly research papers, studies and academic journals. They offer in-depth analyses of various subjects, including market trends, consumer preferences and industry-specific insights. Researchers can access a wealth of peer-reviewed publications to gain a deeper understanding of their research topics.
• Government and NGO databases: Government agencies, nongovernmental organizations and other institutions frequently maintain databases containing valuable economic, demographic and industry-related data. These sources offer credible statistics and reports on a wide range of topics, making them essential for market researchers. Examples include the U.S. Census Bureau , the Bureau of Labor Statistics and the Pew Research Center .
• Industry reports: Industry reports and market studies are comprehensive documents prepared by research firms, industry associations and consulting companies. They provide in-depth insights into specific markets, including market size, trends, competitive analysis and consumer behavior. You can find this information by looking at relevant industry association databases; examples include the American Marketing Association and the National Retail Federation .
• Social media and online communities: Social media platforms like LinkedIn or Twitter (X) , forums such as Reddit and Quora , and review platforms such as G2 can provide real-time insights into consumer sentiment, opinions and trends. 

Market research examples

At this point, you have market research tools and data sources — but how do you act on the data you gather? Let’s go over some real-world examples that illustrate the practical application of market research across various industries. These examples showcase how market research can lead to smart decision-making and successful business decisions.

Example 1: Apple’s iPhone launch

Apple ’s iconic iPhone launch in 2007 serves as a prime example of market research driving product innovation in tech. Before the iPhone’s release, Apple conducted extensive market research to understand consumer preferences, pain points and unmet needs in the mobile phone industry. This research led to the development of a touchscreen smartphone with a user-friendly interface, addressing consumer demands for a more intuitive and versatile device. The result was a revolutionary product that disrupted the market and redefined the smartphone industry.

Example 2: McDonald’s global expansion

McDonald’s successful global expansion strategy demonstrates the importance of market research when expanding into new territories. Before entering a new market, McDonald’s conducts thorough research to understand local tastes, preferences and cultural nuances. This research informs menu customization, marketing strategies and store design. For instance, in India, McDonald’s offers a menu tailored to local preferences, including vegetarian options. This market-specific approach has enabled McDonald’s to adapt and thrive in diverse global markets.

Example 3: Organic and sustainable farming

The shift toward organic and sustainable farming practices in the food industry is driven by market research that indicates increased consumer demand for healthier and environmentally friendly food options. As a result, food producers and retailers invest in sustainable sourcing and organic product lines — such as with these sustainable seafood startups — to align with this shift in consumer values. 

The bottom line? Market research has multiple use cases and is a critical practice for any industry. Whether it’s launching groundbreaking products, entering new markets or responding to changing consumer preferences, you can use market research to shape successful strategies and outcomes.

Market research templates

You finally have a strong understanding of how to do market research and apply it in the real world. Before we wrap up, here are some market research templates that you can use as a starting point for your projects:

• Smartsheet competitive analysis templates : These spreadsheets can serve as a framework for gathering information about the competitive landscape and obtaining valuable lessons to apply to your business strategy.
• SurveyMonkey product survey template : Customize the questions on this survey based on what you want to learn from your target customers.
• HubSpot templates : HubSpot offers a wide range of free templates you can use for market research, business planning and more.
• SCORE templates : SCORE is a nonprofit organization that provides templates for business plans, market analysis and financial projections.
• SBA.gov : The U.S. Small Business Administration offers templates for every aspect of your business, including market research, and is particularly valuable for new startups. 

Strengthen your business with market research

When conducted effectively, market research is like a guiding star. Equipped with the right tools and techniques, you can uncover valuable insights, stay competitive, foster innovation and navigate the complexities of your industry.

Throughout this guide, we’ve discussed the definition of market research, different research methods, and how to conduct it effectively. We’ve also explored various types of market research and shared practical insights and templates for getting started. 

Now, it’s time to start the research process. Trust in data, listen to the market and make informed decisions that guide your company toward lasting success.

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How To Cite Market Research in School Assignments

Apr 22, 2020

Blog Academic Institutions How To Cite Market Research in School Assignments

BCC’s market research is a solid reference that provides weight to whatever project or paper you’re working on. That said, there’s an aspect of it that is often overlooked; citing market research reports correctly.

To start, think of our market research as a pizza. Confused? Check out our breakdown here . Syndicated research, which includes market research reports, is the sauce of the market research pizza.

Now, like a pizza, the secret lies in the perfect sauce. There are a variety of ways to make the sauce, but once you choose a variety, you must follow the recipe exactly or else the taste will be affected.

If we put the analogies aside for a second, citing market research correctly really comes down to what your professors require. Are they asking you to cite your references in MLA, APA or Chicago style?

Chances are, you’re not completely certain about how you should be formatting the research, but you do know what style your professor requires.

That’s why we’re going to give you the recipe (yup, we’re back with the analogy) to guide you in cooking the exact sauce, er, citation that your professor requires.

Below you’ll find the breakdown for each citation style, as well as an example of how it should look like when you’re using our reports in your projects and papers.

Now, without further ado, to the citations! These are specific to the reports in the BCC Research library.

Citation for MLA: Author’s Last Name, / Author’s First Name / “Title of article in quotation marks” / Title of web page in italics / Vol. number / issue number / Date published / page number or range / Title of Website in italics / doi: or URL

Citing our research in MLA: Kumar, Aneesh. “Probiotics in Food, Beverages, Dietary Supplements and Animal Feed.”  Probiotics Market Report on Dietary Supplements & Animal Feed , BCC Research, Jan. 2020, www.bccresearch.com/market-research/food-and-beverage/probiotics-market-ingredients-supplements-foods-report.html.

Citation for Chicago: Author’s Last Name, / Author’s First Name / “Title of Article in quotation marks” / Title of publication in italics / Date published, / URL

Citing our research in Chicago: Kumar, Aneesh. “Probiotics in Food, Beverages, Dietary Supplements and Animal Feed.” Probiotics Market Report on Dietary Supplements & Animal Feed. BCC Research, January 2020. https://www.bccresearch.com/market-research/food-and-beverage/probiotics-market-ingredients-supplements-foods-report.html.

Citation for APA: Author’s Last Name / Initials of First and Middle Name / (Date Published) / Title of Source / Location of publisher / URL

Citing our research in APA: Kumar, A. (2020, January). Probiotics in Food, Beverages, Dietary Supplements and Animal Feed. Retrieved from https://www.bccresearch.com/market-research/food-and-beverage/probiotics-market-ingredients-supplements-foods-report.html

Don’t be daunted by the initial complexity that comes with citing sources. Going back to our analogy of the pizza sauce, it’s always harder the first time you do it.

But after some practice and repetition, you won’t even have to think about it. And soon, you’ll know exactly what information to cite and how to properly list our research according to your professor’s requirements.

Looking for market research for your paper or project? Type in your topic and find related reports.

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How do I reference a market research report… in the Cranfield Author-date style?

Market research reports are heavily used in MIRC.  So how would you create a reference for a Mintel report or something similar?   Here’s our guidance on how to reference a market research or industry report using the Author-date style used at Cranfield University:

• Publishing organisation or author
• (Year of publication)
• Title or section of report
• Day/Month if available.
• Available at: URL
• (Accessed: date).

Here are some examples of what your bibliographic references might look like:

MarketLine (2015) Germany – Management & Marketing Consultancy . January. Available at: http://advantage.marketline.com. (Accessed: 03 March 2015).

Mintel (2014) Beer – UK .  December.  Available at: http://academic.mintel.com/. (Accessed: 03 March 2015).

Euromonitor International (2014) Chocolate Confectionery in the United Kingdom: Category Briefing . 25 September. Available at: http://www.portal.euromonitor.com/.  (Accessed 01 March 2015).

As always if you have any questions about referencing, pop into MIRC or contact us at [email protected].

Feature image from Pixabay. Available at: https://pixabay.com/photos/student-typing-keyboard-text-woman-849822/

Written By: Karen Stokes

A Business Librarian since 2009, Karen leads support for the Cranfield MBA courses, both full-time and Executive.

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Market research is a cornerstone of all successful, strategic businesses. It can also be daunting for entrepreneurs looking to launch a startup or start a side hustle . What is market research, anyway? And how do you…do it?

We’ll walk you through absolutely everything you need to know about the market research process so that by the end of this guide, you’ll be an expert in market research too. And what’s more important: you’ll have actionable steps you can take to start collecting your own market research.

What Is Market Research?

Market research is the organized process of gathering information about your target customers and market. Market research can help you better understand customer behavior and competitor strengths and weaknesses, as well as provide insight for the best strategies in launching new businesses and products. There are different ways to approach market research, including primary and secondary research and qualitative and quantitative research. The strongest approaches will include a combination of all four.

“Virtually every business can benefit from conducting some market research,” says Niles Koenigsberg of Real FiG Advertising + Marketing . “Market research can help you piece together your [business’s] strengths and weaknesses, along with your prospective opportunities, so that you can understand where your unique differentiators may lie.” Well-honed market research will help your brand stand out from the competition and help you see what you need to do to lead the market. It can also do so much more.

The Purposes of Market Research

Why do market research? It can help you…

• Pinpoint your target market, create buyer personas, and develop a more holistic understanding of your customer base and market.
• Understand current market conditions to evaluate risks and anticipate how your product or service will perform.
• Validate a concept prior to launch.
• Identify gaps in the market that your competitors have created or overlooked.
• Solve problems that have been left unresolved by the existing product/brand offerings.
• Identify opportunities and solutions for new products or services.
• Develop killer marketing strategies .

What Are the Benefits of Market Research?

Strong market research can help your business in many ways. It can…

• Strengthen your market position.
• Help you identify your strengths and weaknesses.
• Help you identify your competitors’ strengths and weaknesses.
• Minimize risk.
• Center your customers’ experience from the get-go.
• Help you create a dynamic strategy based on market conditions and customer needs/demands.

What Are the Basic Methods of Market Research?

The basic methods of market research include surveys, personal interviews, customer observation, and the review of secondary research. In addition to these basic methods, a forward-thinking market research approach incorporates data from the digital landscape like social media analysis, SEO research, gathering feedback via forums, and more. Throughout this guide, we will cover each of the methods commonly used in market research to give you a comprehensive overview.

Primary vs. Secondary Market Research

Primary and secondary are the two main types of market research you can do. The latter relies on research conducted by others. Primary research, on the other hand, refers to the fact-finding efforts you conduct on your own.

This approach is limited, however. It’s likely that the research objectives of these secondary data points differ from your own, and it can be difficult to confirm the veracity of their findings.

Primary Market Research

Primary research is more labor intensive, but it generally yields data that is exponentially more actionable. It can be conducted through interviews, surveys, online research, and your own data collection. Every new business should engage in primary market research prior to launch. It will help you validate that your idea has traction, and it will give you the information you need to help minimize financial risk.

You can hire an agency to conduct this research on your behalf. This brings the benefit of expertise, as you’ll likely work with a market research analyst. The downside is that hiring an agency can be expensive—too expensive for many burgeoning entrepreneurs. That brings us to the second approach. You can also do the market research yourself, which substantially reduces the financial burden of starting a new business .

Secondary Market Research

Secondary research includes resources like government databases and industry-specific data and publications. It can be beneficial to start your market research with secondary sources because it’s widely available and often free-to-access. This information will help you gain a broad overview of the market conditions for your new business.

Identify Your Goals and Your Audience

Before you begin conducting interviews or sending out surveys, you need to set your market research goals. At the end of your market research process, you want to have a clear idea of who your target market is—including demographic information like age, gender, and where they live—but you also want to start with a rough idea of who your audience might be and what you’re trying to achieve with market research.

You can pinpoint your objectives by asking yourself a series of guiding questions:

• What are you hoping to discover through your research?
• Who are you hoping to serve better because of your findings?
• What do you think your market is?
• Who are your competitors?
• Are you testing the reception of a new product category or do you want to see if your product or service solves the problem left by a current gap in the market?
• Are you just…testing the waters to get a sense of how people would react to a new brand?

Once you’ve narrowed down the “what” of your market research goals, you’re ready to move onto how you can best achieve them. Think of it like algebra. Many math problems start with “solve for x.” Once you know what you’re looking for, you can get to work trying to find it. It’s a heck of a lot easier to solve a problem when you know you’re looking for “x” than if you were to say “I’m gonna throw some numbers out there and see if I find a variable.”

How to Do Market Research

This guide outlines every component of a comprehensive market research effort. Take into consideration the goals you have established for your market research, as they will influence which of these elements you’ll want to include in your market research strategy.

Secondary Data

Secondary data allows you to utilize pre-existing data to garner a sense of market conditions and opportunities. You can rely on published market studies, white papers, and public competitive information to start your market research journey.

Secondary data, while useful, is limited and cannot substitute your own primary data. It’s best used for quantitative data that can provide background to your more specific inquiries.

Find Your Customers Online

Once you’ve identified your target market, you can use online gathering spaces and forums to gain insights and give yourself a competitive advantage. Rebecca McCusker of The Creative Content Shop recommends internet recon as a vital tool for gaining a sense of customer needs and sentiment. “Read their posts and comments on forums, YouTube video comments, Facebook group [comments], and even Amazon/Goodreads book comments to get in their heads and see what people are saying.”

If you’re interested in engaging with your target demographic online, there are some general rules you should follow. First, secure the consent of any group moderators to ensure that you are acting within the group guidelines. Failure to do so could result in your eviction from the group.

Not all comments have the same research value. “Focus on the comments and posts with the most comments and highest engagement,” says McCusker. These high-engagement posts can give you a sense of what is already connecting and gaining traction within the group.

Social media can also be a great avenue for finding interview subjects. “LinkedIn is very useful if your [target customer] has a very specific job or works in a very specific industry or sector. It’s amazing the amount of people that will be willing to help,” explains Miguel González, a marketing executive at Dealers League . “My advice here is BE BRAVE, go to LinkedIn, or even to people you know and ask them, do quick interviews and ask real people that belong to that market and segment and get your buyer persona information first hand.”

Market research interviews can provide direct feedback on your brand, product, or service and give you a better understanding of consumer pain points and interests.

When organizing your market research interviews, you want to pay special attention to the sample group you’re selecting, as it will directly impact the information you receive. According to Tanya Zhang, the co-founder of Nimble Made , you want to first determine whether you want to choose a representative sample—for example, interviewing people who match each of the buyer persona/customer profiles you’ve developed—or a random sample.

“A sampling of your usual persona styles, for example, can validate details that you’ve already established about your product, while a random sampling may [help you] discover a new way people may use your product,” Zhang says.

Market Surveys

Market surveys solicit customer inclinations regarding your potential product or service through a series of open-ended questions. This direct outreach to your target audience can provide information on your customers’ preferences, attitudes, buying potential, and more.

Every expert we asked voiced unanimous support for market surveys as a powerful tool for market research. With the advent of various survey tools with accessible pricing—or free use—it’s never been easier to assemble, disseminate, and gather market surveys. While it should also be noted that surveys shouldn’t replace customer interviews , they can be used to supplement customer interviews to give you feedback from a broader audience.

Who to Include in Market Surveys

• Current customers
• Past customers
• Your existing audience (such as social media/newsletter audiences)

Example Questions to Include in Market Surveys

While the exact questions will vary for each business, here are some common, helpful questions that you may want to consider for your market survey. Demographic Questions: the questions that help you understand, demographically, who your target customers are:

• “What is your age?”
• “Where do you live?”
• “What is your gender identity?”
• “What is your household income?”
• “What is your household size?”
• “What do you do for a living?”
• “What is your highest level of education?”

Product-Based Questions: Whether you’re seeking feedback for an existing brand or an entirely new one, these questions will help you get a sense of how people feel about your business, product, or service:

• “How well does/would our product/service meet your needs?”
• “How does our product/service compare to similar products/services that you use?”
• “How long have you been a customer?” or “What is the likelihood that you would be a customer of our brand?

Personal/Informative Questions: the deeper questions that help you understand how your audience thinks and what they care about.

• “What are your biggest challenges?”
• “What’s most important to you?”
• “What do you do for fun (hobbies, interests, activities)?”
• “Where do you seek new information when researching a new product?”
• “How do you like to make purchases?”
• “What is your preferred method for interacting with a brand?”

Survey Tools

Online survey tools make it easy to distribute surveys and collect responses. The best part is that there are many free tools available. If you’re making your own online survey, you may want to consider SurveyMonkey, Typeform, Google Forms, or Zoho Survey.

Competitive Analysis

A competitive analysis is a breakdown of how your business stacks up against the competition. There are many different ways to conduct this analysis. One of the most popular methods is a SWOT analysis, which stands for “strengths, weaknesses, opportunities, and threats.” This type of analysis is helpful because it gives you a more robust understanding of why a customer might choose a competitor over your business. Seeing how you stack up against the competition can give you the direction you need to carve out your place as a market leader.

Social Media Analysis

Social media has fundamentally changed the market research landscape, making it easier than ever to engage with a wide swath of consumers. Follow your current or potential competitors on social media to see what they’re posting and how their audience is engaging with it. Social media can also give you a lower cost opportunity for testing different messaging and brand positioning.

SEO Analysis and Opportunities

SEO analysis can help you identify the digital competition for getting the word out about your brand, product, or service. You won’t want to overlook this valuable information. Search listening tools offer a novel approach to understanding the market and generating the content strategy that will drive business. Tools like Google Trends and Awario can streamline this process.

Ready to Kick Your Business Into High Gear?

Now that you’ve completed the guide to market research you know you’re ready to put on your researcher hat to give your business the best start. Still not sure how actually… launch the thing? Our free mini-course can run you through the essentials for starting your side hustle .

About Mary Kate Miller

Mary Kate Miller writes about small business, real estate, and finance. In addition to writing for Foundr, her work has been published by The Washington Post, Teen Vogue, Bustle, and more. She lives in Chicago.

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What Is Market Research?

• How It Works
• Primary vs. Secondary
• How to Conduct Research

The Bottom Line

• Marketing Essentials

How to Do Market Research, Types, and Example

Joules Garcia / Investopedia

Market research examines consumer behavior and trends in the economy to help a business develop and fine-tune its business idea and strategy. It helps a business understand its target market by gathering and analyzing data.

Market research is the process of evaluating the viability of a new service or product through research conducted directly with potential customers. It allows a company to define its target market and get opinions and other feedback from consumers about their interest in a product or service.

Research may be conducted in-house or by a third party that specializes in market research. It can be done through surveys and focus groups, among other ways. Test subjects are usually compensated with product samples or a small stipend for their time.

Key Takeaways

• Companies conduct market research before introducing new products to determine their appeal to potential customers.
• Tools include focus groups, telephone interviews, and questionnaires.
• The results of market research inform the final design of the product and determine how it will be positioned in the marketplace.
• Market research usually combines primary information, gathered directly from consumers, and secondary information, which is data available from external sources.

Market Research

How market research works.

Market research is used to determine the viability of a new product or service. The results may be used to revise the product design and fine-tune the strategy for introducing it to the public. This can include information gathered for the purpose of determining market segmentation . It also informs product differentiation , which is used to tailor advertising.

A business engages in various tasks to complete the market research process. It gathers information based on the market sector being targeted by the product. This information is then analyzed and relevant data points are interpreted to draw conclusions about how the product may be optimally designed and marketed to the market segment for which it is intended.

It is a critical component in the research and development (R&D) phase of a new product or service introduction. Market research can be conducted in many different ways, including surveys, product testing, interviews, and focus groups.

Market research is a critical tool that companies use to understand what consumers want, develop products that those consumers will use, and maintain a competitive advantage over other companies in their industry.

Primary Market Research vs. Secondary Market Research

Market research usually consists of a combination of:

• Primary research, gathered by the company or by an outside company that it hires
• Secondary research, which draws on external sources of data

Primary Market Research

Primary research generally falls into two categories: exploratory and specific research.

• Exploratory research is less structured and functions via open-ended questions. The questions may be posed in a focus group setting, telephone interviews, or questionnaires. It results in questions or issues that the company needs to address about a product that it has under development.
• Specific research delves more deeply into the problems or issues identified in exploratory research.

Secondary Market Research

All market research is informed by the findings of other researchers about the needs and wants of consumers. Today, much of this research can be found online.

Secondary research can include population information from government census data , trade association research reports , polling results, and research from other businesses operating in the same market sector.

History of Market Research

Formal market research began in Germany during the 1920s. In the United States, it soon took off with the advent of the Golden Age of Radio.

Companies that created advertisements for this new entertainment medium began to look at the demographics of the audiences who listened to each of the radio plays, music programs, and comedy skits that were presented.

They had once tried to reach the widest possible audience by placing their messages on billboards or in the most popular magazines. With radio programming, they had the chance to target rural or urban consumers, teenagers or families, and judge the results by the sales numbers that followed.

Types of Market Research

Face-to-face interviews.

From their earliest days, market research companies would interview people on the street about the newspapers and magazines that they read regularly and ask whether they recalled any of the ads or brands that were published in them. Data collected from these interviews were compared to the circulation of the publication to determine the effectiveness of those ads.

Market research and surveys were adapted from these early techniques.

To get a strong understanding of your market, it’s essential to understand demand, market size, economic indicators, location, market saturation, and pricing.

Focus Groups

A focus group is a small number of representative consumers chosen to try a product or watch an advertisement.

Afterward, the group is asked for feedback on their perceptions of the product, the company’s brand, or competing products. The company then takes that information and makes decisions about what to do with the product or service, whether that's releasing it, making changes, or abandoning it altogether.

Phone Research

The man-on-the-street interview technique soon gave way to the telephone interview. A telephone interviewer could collect information in a more efficient and cost-effective fashion.

Telephone research was a preferred tactic of market researchers for many years. It has become much more difficult in recent years as landline phone service dwindles and is replaced by less accessible mobile phones.

Survey Research

As an alternative to focus groups, surveys represent a cost-effective way to determine consumer attitudes without having to interview anyone in person. Consumers are sent surveys in the mail, usually with a coupon or voucher to incentivize participation. These surveys help determine how consumers feel about the product, brand, and price point.

Online Market Research

With people spending more time online, market research activities have shifted online as well. Data collection still uses a survey-style form. But instead of companies actively seeking participants by finding them on the street or cold calling them on the phone, people can choose to sign up, take surveys, and offer opinions when they have time.

This makes the process far less intrusive and less rushed, since people can participate on their own time and of their own volition.

How to Conduct Market Research

The first step to effective market research is to determine the goals of the study. Each study should seek to answer a clear, well-defined problem. For example, a company might seek to identify consumer preferences, brand recognition, or the comparative effectiveness of different types of ad campaigns.

After that, the next step is to determine who will be included in the research. Market research is an expensive process, and a company cannot waste resources collecting unnecessary data. The firm should decide in advance which types of consumers will be included in the research, and how the data will be collected. They should also account for the probability of statistical errors or sampling bias .

The next step is to collect the data and analyze the results. If the two previous steps have been completed accurately, this should be straightforward. The researchers will collect the results of their study, keeping track of the ages, gender, and other relevant data of each respondent. This is then analyzed in a marketing report that explains the results of their research.

The last step is for company executives to use their market research to make business decisions. Depending on the results of their research, they may choose to target a different group of consumers, or they may change their price point or some product features.

The results of these changes may eventually be measured in further market research, and the process will begin all over again.

Benefits of Market Research

Market research is essential for developing brand loyalty and customer satisfaction. Since it is unlikely for a product to appeal equally to every consumer, a strong market research program can help identify the key demographics and market segments that are most likely to use a given product.

Market research is also important for developing a company’s advertising efforts. For example, if a company’s market research determines that its consumers are more likely to use Facebook than X (formerly Twitter), it can then target its advertisements to one platform instead of another. Or, if they determine that their target market is value-sensitive rather than price-sensitive, they can work on improving the product rather than reducing their prices.

Market research only works when subjects are honest and open to participating.

Example of Market Research

Many companies use market research to test new products or get information from consumers about what kinds of products or services they need and don’t currently have.

For example, a company that’s considering starting a business might conduct market research to test the viability of its product or service. If the market research confirms consumer interest, the business can proceed confidently with its business plan . If not, the company can use the results of the market research to make adjustments to the product to bring it in line with customer desires.

What Are the Main Types of Market Research?

The main types of market research are primary research and secondary research. Primary research includes focus groups, polls, and surveys. Secondary research includes academic articles, infographics, and white papers.

Qualitative research gives insights into how customers feel and think. Quantitative research uses data and statistics such as website views, social media engagement, and subscriber numbers.

What Is Online Market Research?

Online market research uses the same strategies and techniques as traditional primary and secondary market research, but it is conducted on the Internet. Potential customers may be asked to participate in a survey or give feedback on a product. The responses may help the researchers create a profile of the likely customer for a new product.

What Are Paid Market Research Surveys?

Paid market research involves rewarding individuals who agree to participate in a study. They may be offered a small payment for their time or a discount coupon in return for filling out a questionnaire or participating in a focus group.

What Is a Market Study?

A market study is an analysis of consumer demand for a product or service. It looks at all of the factors that influence demand for a product or service. These include the product’s price, location, competition, and substitutes as well as general economic factors that could influence the new product’s adoption, for better or worse.

Market research is a key component of a company’s research and development (R&D) stage. It helps companies understand in advance the viability of a new product that they have in development and to see how it might perform in the real world.

Britannica Money. “ Market Research .”

U.S. Small Business Administration. “ Market Research and Competitive Analysis .”

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• APA 7th ed. citation for business sources. This extensive business citation guide was created by business librarians from across the country. Schemm, N., Dellenbach, M., Grisham, Z., Hageman, M., Tingle, N., Trowbridge, M., & Wheatley, A. (2020). APA 7th ed. citation for business sources .

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From Database:

Tesla Inc. (2021).  Form 10-K 2020 . Retrieved from Mergent Online database.

From SEC Website:

Tesla Inc. (2021).  Form 10-K 2020 . Retrieved from SEC EDGAR website http://www.sec.gov/edgar.shtml

From Company Website:

Tesla Inc. (2021).  Form 10-K 2020 . Retrieved from https://ir.tesla.com/_flysystem/s3/sec/000156459021004599/tsla-10k_20201231-gen.pdf

A.P. Moeller Maersk. (2021).  Annual report 2020 .  Retrieved from https://investor.maersk.com/static-files/97a03c29-46a2-4e84-9b7e-12d4ee451361

A.P. Moeller Maersk. (2021).  Annual report 2020 . Retrieved from Mergent Online database.

RIA. (2020). 2301 Business Incentive Credits—General Business Credit (GBC)—Form 3800. Federal tax handbook. RIA Checkpoint.  https://checkpoint.riag.com.

AICPA. (2020, March 1). Not-for-Profit Entities. AICPA Audit and Accounting Guide. RIA Checkpoint.  https://checkpoint.riag.com.

Economist Intelligence Unit. (2019, July 23). China’s social credit system and its implications.   https://gfs.eiu.com

Mergent. (2020, July 6).  Computer Peripheral Equipment Manufacturing. First Research. Retrieved July 15, 2020, from https://mergent.firstresearch-learn.com

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Gambardella, A. (2020, May).  IBISWorld Industry 52391 Venture Capital & Principal Trading in the US. Retrieved July 10, 2020 from https://www.ibisworld.com

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IBISWorld (n.d).  US Company Benchmarking Report 429335 Sunrun Inc. Retrieved February 2, 2023 from https://www.ibisworld.com

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IBISWorld (April 2022).  US Business Environment Profiles Report G122 Price of eggs.  Retrieved February 2, 2023 from https://www.ibisworld.com

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Freedonia Focus Reports. (2018, April). Reactive Adhesives & Sealants: United States . MarketResearch.com.  https://www.marketresearch.com

Mergent. (n.d.).  UPS Supply Chain Solutions, Inc. - Family Tree . Mergent Intellect. Retrieved October 25, 2019 from https://www.mergentintellect.com

Citing part of a company profile

Mergent. (2019). Apple Inc. company financials: income statement [Data set]. Mergent Online. Retrieved August 1, 2020 from  https://www.mergentonline.com

Citing an industry report

Cullen, R. (2020, July).  Pet Supplies. Mintel. Retrieved from https://www.mintel.com

Morningstar. (n.d.).  Google: Key ratios.  Morningstar Investment Research. Retrieved from https://www.morningstar.com

Morningstar. (2019, February 28)  Fidelity Blue Chip Growth: Rating and risk .  Morningstar Investment Research. Retrieved from https://www.morningstar.com

MRI-Simmons. (2019).  National Consumer Study 12 month  [CONCISELY DESCRIBE VARIABLE ONE AND VARIABLE TWO]. https://mrisimmons.com

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Citing statistics

Euromonitor. (2019). [Market share, beer, per capita at legal purchasing age, all countries] [Data set]. Passport. https://www.euromonitor.com/

Citing a report

Euromonitor. (2020, March 18). Retailing in Egypt [Industry report]. Passport. https://www.euromonitor.com/

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For undated or dynamically-updated items:

PitchBook. (n.d.). Uber Company Profile. PitchBook. Retrieved January 11, 2019 from https://www.pitchbook.com

Sport Fitness Industry Association. (2020, February).  Sport & Fitness Industry Association Sports, Fitness, And Leisure Activities Topline Participation Report. SFIA. https://www.sfia.org

Tables/Data Examples:

National Sporting Goods Association. (n.d.).  Participation (ages 7+) ranking: Females (no. of part. in thous.)  [Data]. SMA Sport Market Analytics. Retrieved January 29, 2020, from https://www.sportsmarketanalytics.com

SBRnet. (n.d.).  Sports fan market/market size, by sport: Number of fans . [Data]. SMA Sport Market Analytics. Retrieved March 13, 2020, from www.sportsmarketanalytics.com

SRDS. (n.d.). State Analysis -   Virginia & Washington. SRDS Circulation 2016.  SRDS. Retrieved May 10, 2019, from https://next.srds.com

SRDS. (n.d.). The Boston Globe [Publication profile]. Newspaper Advertising Source . SRDS. Retrieved November 30, 2019, from https://next.srds.com

Claritas, Inc. (2010). Boston, MA/Manchester, NH [DMA profile]. Radio Advertising Source . SRDS. Retrieved December 14, 2019, from https://next.srds.com

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Citing the American Community Survey

Census Bureau. (2018). Earnings in the past 12 months (in 2018 inflation-adjusted dollars): Eugene city, Oregon [Data set]. American Community Survey, 5-year estimates. Data.census.gov. https://data.census.gov/cedsci/table?g=0500000US41039&hidePreview

Citing the Economic Census

Census Bureau. (2017). All Sectors: Summary Statistics for the U.S., States, and Selected Geographies: 2017: Alaska, NAICS 211: Oil and gas extraction [Data set]. Economic Census. Data.census.gov.   https://data.census.gov/cedsci/table?q=economic%20census%202017

Citing the Business Patterns dataset

Census Bureau. (2017). All Sectors: County Business Patterns by Legal Form of Organization and Employment Size Class for U.S., States, and Selected Geographies: 2017: Alaska [Data set]. Data.census.gov. https://data.census.gov/cedsci/table?q=county%20business%20patterns

Brownsell, A., Petio, C. (2022, May). Big Tech's share of global ad spend reaches 6% . Retrieved from WARC database.

WARC. (2022, May). What's working in direct to consumer 2022 . Retrieved from WARC database.

Compustat Industrial [Annual Data] . (YEARS). Available: Standard & Poor's/Compustat [access date]. Retrieved from https://wrds-www.wharton.upenn.edu/

CRSP Stocks.  (YEARS). Available: Center for Research in Security Prices . Graduate School of Business. University of Chicago [access date]. Retrieved from https://wrds-www.wharton.upenn.edu/

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Market Research: A How-To Guide and Template

Discover the different types of market research, how to conduct your own market research, and use a free template to help you along the way.

MARKET RESEARCH KIT

5 Research and Planning Templates + a Free Guide on How to Use Them in Your Market Research

Updated: 02/21/24

Published: 02/21/24

Today's consumers have a lot of power. As a business, you must have a deep understanding of who your buyers are and what influences their purchase decisions.

Enter: Market Research.

Whether you're new to market research or not, I created this guide to help you conduct a thorough study of your market, target audience, competition, and more. Let’s dive in.

Table of Contents

What is market research?

Primary vs. secondary research, types of market research, how to do market research, market research report template, market research examples.

Market research is the process of gathering information about your target market and customers to verify the success of a new product, help your team iterate on an existing product, or understand brand perception to ensure your team is effectively communicating your company's value effectively.

Market research can answer various questions about the state of an industry. But if you ask me, it's hardly a crystal ball that marketers can rely on for insights on their customers.

Market researchers investigate several areas of the market, and it can take weeks or even months to paint an accurate picture of the business landscape.

However, researching just one of those areas can make you more intuitive to who your buyers are and how to deliver value that no other business is offering them right now.

How? Consider these two things:

• Your competitors also have experienced individuals in the industry and a customer base. It‘s very possible that your immediate resources are, in many ways, equal to those of your competition’s immediate resources. Seeking a larger sample size for answers can provide a better edge.
• Your customers don't represent the attitudes of an entire market. They represent the attitudes of the part of the market that is already drawn to your brand.

The market research services market is growing rapidly, which signifies a strong interest in market research as we enter 2024. The market is expected to grow from roughly $75 billion in 2021 to $90.79 billion in 2025 .

Free Market Research Kit

• SWOT Analysis Template
• Survey Template
• Focus Group Template

You're all set!

Click this link to access this resource at any time.

Why do market research?

Market research allows you to meet your buyer where they are.

As our world becomes louder and demands more of our attention, this proves invaluable.

By understanding your buyer's problems, pain points, and desired solutions, you can aptly craft your product or service to naturally appeal to them.

Market research also provides insight into the following:

• Where your target audience and current customers conduct their product or service research
• Which of your competitors your target audience looks to for information, options, or purchases
• What's trending in your industry and in the eyes of your buyer
• Who makes up your market and what their challenges are
• What influences purchases and conversions among your target audience
• Consumer attitudes about a particular topic, pain, product, or brand
• Whether there‘s demand for the business initiatives you’re investing in
• Unaddressed or underserved customer needs that can be flipped into selling opportunity
• Attitudes about pricing for a particular product or service

Ultimately, market research allows you to get information from a larger sample size of your target audience, eliminating bias and assumptions so that you can get to the heart of consumer attitudes.

As a result, you can make better business decisions.

To give you an idea of how extensive market research can get , consider that it can either be qualitative or quantitative in nature — depending on the studies you conduct and what you're trying to learn about your industry.

Qualitative research is concerned with public opinion, and explores how the market feels about the products currently available in that market.

Quantitative research is concerned with data, and looks for relevant trends in the information that's gathered from public records.

That said, there are two main types of market research that your business can conduct to collect actionable information on your products: primary research and secondary research.

Primary Research

Primary research is the pursuit of first-hand information about your market and the customers within your market.

It's useful when segmenting your market and establishing your buyer personas.

Primary market research tends to fall into one of two buckets:

• Exploratory Primary Research: This kind of primary market research normally takes place as a first step — before any specific research has been performed — and may involve open-ended interviews or surveys with small numbers of people.
• Specific Primary Research: This type of research often follows exploratory research. In specific research, you take a smaller or more precise segment of your audience and ask questions aimed at solving a suspected problem.

Secondary Research

Secondary research is all the data and public records you have at your disposal to draw conclusions from (e.g. trend reports, market statistics, industry content, and sales data you already have on your business).

Secondary research is particularly useful for analyzing your competitors . The main buckets your secondary market research will fall into include:

• Public Sources: These sources are your first and most-accessible layer of material when conducting secondary market research. They're often free to find and review — like government statistics (e.g., from the U.S. Census Bureau ).
• Commercial Sources: These sources often come in the form of pay-to-access market reports, consisting of industry insight compiled by a research agency like Pew , Gartner , or Forrester .
• Internal Sources: This is the market data your organization already has like average revenue per sale, customer retention rates, and other historical data that can help you draw conclusions on buyer needs.
• Focus Groups
• Product/ Service Use Research
• Observation-Based Research
• Buyer Persona Research
• Market Segmentation Research
• Pricing Research
• Competitive Analysis Research
• Customer Satisfaction and Loyalty Research
• Brand Awareness Research
• Campaign Research

1. Interviews

Interviews allow for face-to-face discussions so you can allow for a natural flow of conversation. Your interviewees can answer questions about themselves to help you design your buyer personas and shape your entire marketing strategy.

2. Focus Groups

Focus groups provide you with a handful of carefully-selected people that can test out your product and provide feedback. This type of market research can give you ideas for product differentiation.

3. Product/Service Use Research

Product or service use research offers insight into how and why your audience uses your product or service. This type of market research also gives you an idea of the product or service's usability for your target audience.

4. Observation-Based Research

Observation-based research allows you to sit back and watch the ways in which your target audience members go about using your product or service, what works well in terms of UX , and which aspects of it could be improved.

5. Buyer Persona Research

Buyer persona research gives you a realistic look at who makes up your target audience, what their challenges are, why they want your product or service, and what they need from your business or brand.

6. Market Segmentation Research

Market segmentation research allows you to categorize your target audience into different groups (or segments) based on specific and defining characteristics. This way, you can determine effective ways to meet their needs.

7. Pricing Research

Pricing research helps you define your pricing strategy . It gives you an idea of what similar products or services in your market sell for and what your target audience is willing to pay.

8. Competitive Analysis

Competitive analyses give you a deep understanding of the competition in your market and industry. You can learn about what's doing well in your industry and how you can separate yourself from the competition .

9. Customer Satisfaction and Loyalty Research

Customer satisfaction and loyalty research gives you a look into how you can get current customers to return for more business and what will motivate them to do so (e.g., loyalty programs , rewards, remarkable customer service).

10. Brand Awareness Research

Brand awareness research tells you what your target audience knows about and recognizes from your brand. It tells you about the associations people make when they think about your business.

11. Campaign Research

Campaign research entails looking into your past campaigns and analyzing their success among your target audience and current customers. The goal is to use these learnings to inform future campaigns.

• Define your buyer persona.
• Identify a persona group to engage.
• Prepare research questions for your market research participants.
• List your primary competitors.
• Summarize your findings.

1. Define your buyer persona.

You have to understand who your customers are and how customers in your industry make buying decisions.

This is where your buyer personas come in handy. Buyer personas — sometimes referred to as marketing personas — are fictional, generalized representations of your ideal customers.

Use a free tool to create a buyer persona that your entire company can use to market, sell, and serve better.

Don't forget to share this post!

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McDonald's Corporation. (February 24, 2014). Form   10-K 2013 .  https://www.sec.gov/edgar/shtml

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Marketing Research

Direct mail to prospects and email to current customers? Modeling and field-testing multichannel marketing

• Original Empirical Research
• Open access
• Published: 05 August 2023

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• Albert Valenti   ORCID: orcid.org/0000-0003-2887-7712 1 ,
• Shuba Srinivasan 2 ,
• Gokhan Yildirim 3 &
• Koen Pauwels 4 , 5  

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Multichannel retailers need to understand how to allocate marketing budgets to customer segments and online and offline sales channels. We propose an integrated methodological approach to assess how email and direct mail effectiveness vary by channel and customer value segment. We apply this approach to an international beauty retailer in six countries and to an apparel retailer in the United States. We estimate multi-equation hierarchical linear models and find that sales responsiveness to email and direct mail varies by customer value segment. Specifically, direct mail drives customer acquisition in the offline channel, while email drives sales for both online and offline channels for current customer segments. A randomized field experiment with the beauty retailer provides causal support for the findings. The proposed reallocation of marketing resources would yield a revenue lift of 13.5% for the beauty retailer and 9.3% for the apparel retailer, compared with the 6.5% actual increase in the field experiment.

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Introduction

Multichannel retail is important for today’s marketers (Cui et al., 2021 ; Dekimpe, 2020 ), but it requires managers to allocate marketing budgets to channels and customer segments. Customer transactional data give retailers detailed information about existing customers’ purchase history, allowing them to prioritize customer segments by value. However, which segments are most responsive to which marketing action is unclear a priori (Zhang et al., 2014 ). For example, direct mail volume increased 46% between 2019 and 2022 (Gendusa, 2022 ), with growth in impressions (28%) outpacing digital ad impressions (10%) in 2021; yet direct mail is also very expensive and therefore often targeted to the highest-value segments (Sahni et al., 2017 ). Our survey of 351 marketing managers reveals that 46% believe that the most expensive marketing action should be targeted at the most valuable customers while 41% believe that all marketing should be sent to all customer types. Footnote 1 Consistent with these statements, most companies target emails to least valuable customer segments, including prospects, with its low cost as the primary reason (Levinson, 2019 ; Medlar, 2017 ), and target costly marketing actions to high-value customer segments. However, managers need to assess marketing response in multiple channels to understand which marketing actions produce the best returns and to make budgeting decisions on which actions to invest in and which customer segments to target.

Prior marketing research advises companies to allocate marketing actions to customer segments most receptive to them (Kamakura & Russell, 1989 ) and finds that customers’ past experience with the company’s offering does not necessarily mean greater responsiveness to marketing actions (Ascarza, 2018 ). First, some current customers may not peruse direct mail because they already know the firm and its offerings and prefer reminder emails. However, prospective customers (prospects hereinafter), for whom transactional data is not available, and light buyers might be more responsive to direct mail because of the rich information provided. How much these customers subsequently buy is an open question. Second, customers’ intrinsic preferences for email and direct mail may depend on the intensity of their interactions with the firm (i.e., email opening or direct mail browsing frequencies) differ among customers. Consistent with this argument, Return Path’s ( 2015 ) study suggests that email targeting should depend on customers’ engagement level. Third, recent legal developments such as the European Union’s General Data Protection Regulation (GDPR), are removing up to 75% of third-party data from analysis, Indeed, direct mail “has greatly benefited from GDPR because it does not require consent from recipients” (PostGrid, 2022 ) while the use of emails may be impacted, making it more crucial to identify and target marketing-responsive customers instead of maximizing impressions (e.g., by emailing all customers) (Morris, 2019 ; Snyder, 2018 ).

Our research objective is therefore to address an important marketing-mix resource allocation problem for multichannel retailers. That is, we propose an integrated methodological approach to allocate online and offline marketing actions (in our case, email and direct mail), given the different responses in channels and customer segments, including prospects and dormant customers (i.e., those who have not purchased for a long time). To this end, we develop a decision-support system based on a systematic empirical modeling approach. We begin by describing the value of customers using the recency–frequency–monetary value–clumpiness (RFMC) model, which allows us to classify customers into value segments (Zhang et al., 2014 ). We then estimate multi-equation hierarchical linear models (HLMs) to assess the online and offline sales responsiveness to email and direct mail and customer value segment levels. When the data are from multinational retailers, we perform a meta-analysis of the estimates across countries for comparison. We use HLMs for out-of-sample sales prediction and marketing resource reallocation. Finally, we perform a field experiment to obtain the predicted benefits of the reallocation in a causal setting.

Specifically, we perform three empirical analyses. The first involves an international beauty retailer with data on every purchase transaction and all marketing communications for a four-year period for almost 85,000 customers randomly sampled from its six main markets: United States, Great Britain, Germany, France, Spain, and Italy. The second analysis involves a US apparel retailer with transactional data, online and offline channels, and marketing actions. In the third analysis, to evaluate our model-based results and provide causal inference support, we design and implement a randomized field experiment for the beauty retailer with all its 120,000 customers in Italy.

From a substantive perspective, our research is grounded in marketing managers’ challenges in multichannel retail, addressed with the empirics-first approach advocated by Golder et al. ( 2023 ) instead of starting from theory often borrowed from the founding disciplines (Kohli & Haenlein, 2021 ). Our work combines “conceptualization, research design and research execution” with “deep socialization with practice” (Stremersch, 2021 , p. 13) and challenges the current wisdom held by many high-level decision makers (Kohli & Haenlein, 2021 ). Following Lehmann ( 2020 ), we adopt an integrative modeling approach that blends data and theory by combining prediction and explanation for two specific retailers in six developed countries. In terms of prescriptive implications, we assess potential revenue improvements (e.g., Lemmens & Gupta, 2020 ) following Mantrala et al. ( 1992 ), who argue that the biggest gains are to be realized not by optimizing the total budget, but by doing a reallocation of the current budget. Consistent with this argument, we find that a reallocation of the marketing budget over customer value groups yields substantial revenue improvement. While the specific results are particularly relevant to the marketing actions and companies studied, our findings may encourage scholarly thinking about how they generalize to other contexts (Stremersch et al., 2023 ).

Research on multichannel response to direct mail and email

Within the rich literature on multichannel marketing response, we focus our review on the two marketing actions, direct mail and emails, that capture offline and online marketing in our contexts and on how marketing responsiveness differs by customer segments. Table  1 shows our study’s contributions and positions it within related marketing literature.

Direct mail effectiveness

Despite the growth of online marketing, multichannel retailers rely on direct mail given its ease of processing by consumers, ability to generate greater brand recall, and higher response rates than digital marketing communication (e.g., email, paid search, online display, social media). Direct mail, which accounts for more than one-third of direct marketing expenditures in many countries (Direct Marketing Association, 2015 ), can arouse interest in a firm’s products and result in purchase through short-term rewards (Roberts & Berger, 1999 ; Rust & Verhoef, 2005 ).

Several studies have shown that direct mail significantly affects behavior (Hill et al., 2006 ; Verhoef, 2003 ) and adoption of a new technological product (Prins & Verhoef, 2007 ; Risselada et al., 2014 ). Naik and Peters ( 2009 ) provide empirical evidence that direct mail directly drives online visits to enable car configurations. Valentini et al. ( 2011 ) find that direct mail by a multichannel retailer can drive new customers’ choice of shopping in either online or offline channels (for a review of omnichannel retail, see Timoumi et al., 2022 ). In the context of direct mail for charity donations, Seenivasan et al. ( 2016 ) conduct a field experiment that varies the framing of the message and find that monthly framing of the donation, including a story of an in-group person, yields better outcomes. Verhoef et al. ( 2007 ) argue that direct mail has high ease of use, can result in channel lock-in, and exhibits cross-channel synergy between direct mail search and web purchase. Danaher and Dagger ( 2013 ) cite direct mail as an effective tool to reach unaware consumers. In their comparison of the relative effectiveness of multiple marketing tools, they identify direct mail as the second most effective tool when considering dollar sales as the focal outcome and the most effective when profit is the focal outcome. At the same time, contradictory evidence in the business-to-business sector suggests that direct mail is not effective in driving sales (Wiesel et al., 2011 ).

Direct mail response varies for customer groups and marketing interventions, which can be explained by customer characteristics and past purchase history (Rust & Verhoef, 2005 ). Research has found that marketing response can differ among customer groups depending on demographics or recency–frequency–monetary (RFM) value metrics (Wedel & Kamakura, 2002 ). For example, marketing actions such as promotions are more effective for prospects (Van Heerde & Bijmolt, 2005 ) but do little for acquired customers and could even have negative effects (Anderson & Simester, 2004 ). Rust and Verhoef ( 2005 ) find that loyal customers might have reached their full value in the service relationship in terms of the number of financial services purchased and might be less likely to purchase additional services, despite receiving direct mail with a call for action. Mark et al. ( 2019 ) develop a dynamic segmentation model of channel choice and purchase frequency to assess the responsiveness of segments to direct mail and email. They find that direct mail is an effective tool at influencing purchases in both offline and online channels. However, none of these studies consider how response to direct mail might vary for prospects versus acquired customers over time, in online and offline channels, and assessed with consumer transactional data in an econometrics analysis or a randomized field experiment (see Table 1 ).

Email effectiveness

Emails are effective in driving sales response for several reasons. First, they enable marketers to reach their customers at a low cost. Chittenden and Rettie ( 2003 ) report that the total cost per 5000 customers for email campaigns is $26,500 versus $69,600 for direct mail, so email costs about 38% of direct mail. Second, emails provide information that motivates customers to visit the physical store (Tezinde et al., 2002 ). Emails drive sales (Danaher & Dagger, 2013 ), average spending (Kumar et al., 2014 ), and customer retention (Drèze & Bonfrer, 2008 ). Third, emails may generate faster responses and create an opportunity for interactive communication with customers; customers can respond to an email the moment they receive it on their computer or mobile device.

As to cross-channel effects, emails make it more convenient for customers to use the online (vs. offline) channel because they can land on the firm’s web page by clicking on the email links. Ansari et al. ( 2008 ) find that emails have a positive effect on online sales but a negative effect on offline sales. Sahni et al. ( 2017 ) conduct a post hoc analysis of experiments and show the aggregate-level effects of emails on expenditure. Similarly, Zhang et al. ( 2017 ) capture the average effect of a customer’s response to emails on purchase.

Finally, several meta-analyses find that marketing effectiveness varies across countries and that country effects moderate the elasticity of advertising (Sethuraman et al., 2011 ) and promotions (Kremer et al., 2008 ). Importantly, this evidence comes mostly from a comparison between mature and emerging markets, whereas our data are from mature markets. In addition, as Table 1 shows, these studies do not consider cross-channel effects of marketing actions, except for a few single-country works (Pauwels & Neslin, 2015 ; Valentini et al., 2011 ).

Direct mail and email comparison in consumer segment response

How do direct mail and email compare in consumer responses? In surveys, 70% of Americans find direct mail more personal than email (Direct Marketing Association, 2020 ). Consumers view direct mail as more believable, formal, and important and email as quicker, more informal, and spontaneous (Niblock, 2017 ). While 56% of consumers note that direct mail makes them feel valued, only 40% indicate such about email (Niblock, 2017 ). When delving deeper into why this is so, consumers report that direct mail is tangible and real (Bozeman, 2019 ) and, “as a physical object, provides the space and time needed to appreciate what the company sends” (Medlar, 2017 ).

Regarding differences among consumer segments, direct mail’s trustworthiness and ability to evoke feelings of being valued might be more important for prospects than for current customers. Only 44% of consumers could recall the brand right after seeing a digital ad, while 75% could recall it after receiving direct mail (Niblock, 2017 ). Consumers prefer to receive direct mail for brochures and catalogs (63% vs 21%) and welcome packs (62% vs 23%) but prefer emails for news and updates (62% vs 17%) and confirmation or follow-up messages (57% vs 21%) (Niblock, 2017 ). While direct mail “appeals to … prospects in a very different way – a more emotional way” (Medlar, 2017 ), email is read while at work or relaxing at home and “doesn’t feel the same … as opening a piece of direct mail does” (Bozeman, 2019 ). Moreover, the physicality of direct mail versus email provides the space to communicate more creatively (Levinson, 2019 ), which might be more appealing for prospects who know less about the company offering.

Contributions

This research makes substantive and methodological contributions to the marketing literature on multichannel resource allocation (see Table 1 ). First, from a substantive standpoint, it tackles an important marketing mix resource allocation problem facing multichannel retailers—namely, how to allocate online and offline marketing actions given the different responses in channels and customer segments, including prospect and dormant customers. This research is the first to show that sending direct mail—the most expensive marketing action—to the highest-value customers results in lower performance. Our model-based results in several countries and across retailers, confirmed by a field experiment, show that retailers should allocate direct mail for customer acquisition. From a practice perspective, our decision-support system is embedded in a beauty retailer’s decision processes (Lilien, 2011 ).

Second, from a methodological perspective, we adopt an integrated approach to assess the effectiveness of email and direct mail, per channel and segment. Inspired by the iterative model-experiment decision-making procedure (Hanssens & Pauwels, 2016 ), we also assess our model-based findings in a field experiment. Fischer et al. ( 2011 ) similarly propose a decision model to guide marketing resource allocation in a business-to-business health care setting by determining near-optimal marketing budgets at the country–product–marketing activity level in an Excel-supported environment. Our approach differs from theirs in three ways. First, they do not obtain insights into direct mail and email effectiveness for customer segments, which are of academic and managerial interest. Second, their approach lacks an experimental field test, which is helpful for normative implications that prescriptively guide marketing resource allocation. Third, they analyze their budget allocation estimations under the assumption of the specific response function that best represents the data in their study. Instead, we use more flexible econometric estimation techniques.

Methodological approach

Modeling requirements.

Our research objectives impose several methodological requirements. First, the modeling approach should allow for customer heterogeneity. An important decision is whether customer heterogeneity should be captured at the individual or segment level. We refer to aggregate segment-level models for three reasons: (1) we compare current customers with prospects and dormants, for whom historical purchase data are not available; (2) our objective is to support strategic decision-making on marketing resource allocation, and therefore we follow the literature on such models, which are typically at the aggregate level (e.g., Fischer et al., 2011 ; Hanssens et al., 2014 ; Srinivasan et al., 2016 ); and (3) targeting-related privacy concerns loom large when using consumer-level data, and scholars in the RFM tradition have advocated for summarizing consumer purchase histories and using data-compressed variables for modeling (e.g., Zhang et al., 2014 ).

Second, when confronted with email and direct mail campaigns, customer segments may exhibit different purchase behavior because of differences in overall consumption levels (i.e., intercept heterogeneity) and variations in their responses to email and direct mail campaigns (i.e., slope heterogeneity). These sources of variation are referred to as unobserved heterogeneity (Jain et al., 1994 ). Thus, our model should be flexible in accommodating unobserved heterogeneity among customer segments.

Third, we require a model that involves online and offline channels simultaneously and allows for cross-channel correlation. This enables us to account for channel variation in marketing responsiveness of each customer segment and consider the dependence between online and offline channels. These requirements lead us to estimate a multi-equation HLM (Leckie & Charlton, 2013 ) with two levels, with time-series observations nested within customer segments. Finally, because consumer segments could differ by country, we estimate our model separately for each country.

Thus, we develop and implement a multimethod modeling approach plus a field experiment to address retailers’ marketing problem. Table  2 outlines this approach, which combines customer value segmentation and cluster analysis (descriptive), econometric analyses through multi-equation HLMs (predictive), reallocation of marketing resources (prescriptive), and a field experimental study (causal).

Empirical methodology

Quantify customer value.

We quantify customer value with the RFMC approach because it only requires customer purchase history and can be readily implemented by managers (Zhang et al., 2014 ). Footnote 2 The RFMC approach is an extension of the traditional RFM, which is widely used for customer valuation (Gupta et al., 2006 ), and adds the clumpiness metric. Clumpiness is the degree of nonconformity to identical spacing in purchasing, and its addition helps achieve improved customer valuation and predictive accuracy (Zhang et al., 2014 ). We operationalize clumpiness using the entropy measure. Footnote 3

Create customer segments

We create customer segments according to the standardized RFMC metrics in each country using k-means cluster analysis, an approach preferred for large data sets (James et al., 2013 ). Footnote 4 We use the Euclidean distance as the dissimilarity measure (Gordon, 1999 ). As a starting point for the clusters’ centroids, we use the quantiles of the standardized RFMC values because we want to obtain clusters that reflect a customer value continuum. For example, for a four-cluster solution, the starting points are the 20%–40%–60%–80% values of each standardized RFMC metric. In consultation with the beauty retailer, we opted for a static segmentation to ensure managerial tractability and ease of implementation, given the firm’s annual marketing budget allocation. Importantly, we consider two additional customer segments, prospects and dormants, for which RFMC values cannot be computed because data are not existent or not available because they have not purchased for a long time.

Evaluate responsiveness to emails and direct mail

We estimate multi-equation HLMs to assess online and offline sales responsiveness to emails and direct mail by customer value segment (Leckie & Charlton, 2013 ). Specifically, for each country, we use a two-level structure in which time-series observations are nested within customer value segments (Auer & Papies, 2020 ; Rabe-Hesketh & Skrondal, 2008 ; Raudenbush & Bryk, 2002 ). Similar to Steenkamp and Geyskens ( 2014 ), we develop our model formulation for each level to arrive at the equation we estimate.

We include variables that vary with time as predictors in the level 1 formulation. Equations ( 1 ) and ( 2 ) include all the time-varying predictors (subscripts t and i denote time index and customer value segment index, respectively). Because we deal with time-series data, we specify a k th –order autoregressive terms to account for the autocorrelations in the residuals. Footnote 5 Thus, for both offline and online equations, we formulate level 1 as follows:

Across time within a customer value segment

where the superscripts off and on indicate that the coefficient is for the offline and online equation, respectively, OFF_SALES and ON_SALES stand for offline and online sales, and EMAIL and DIRECT_MAIL stand for email and direct mail. Moreover, DISC is the discount variable that controls for the applied promotions, and HOLIDAY is a categorical variable that captures the effect of major holidays. Footnote 6 The error terms, \({\varepsilon}_{ti}^{off}\) and \({\varepsilon}_{ti}^{on}\) , follow a bivariate normal distribution with zero mean and time-invariant variance–covariance matrix, \(\Omega =\left[\begin{array}{cc}{\sigma}_{off}^2& {\sigma}_{off, on}\\ {}{\sigma}_{on, off}& {\sigma}_{on}^2\end{array}\right]\) . Thus, Ω is nondiagonal; that is, the errors of the two equations are correlated (Leckie & Charlton, 2013 ).

The level 1 equations suggest that the intercepts and slopes of the email and direct mail variables vary across customer value segments. Level 2 includes these varying parameters from level 1 as dependent variables:

Across customer value segments

Equation ( 3 ) shows that overall offline sales in segment i are a function of a baseline ( \({\alpha}_{00}^{off}\Big)\) and a segment-specific intercept ( \({\alpha}_{0i}^{off}\) ). Similarly, Eq. ( 4 ) shows that overall online sales in segment j are a function of a baseline ( \({\alpha}_{00}^{on}\Big)\) and a segment-specific intercept ( \({\alpha}_{0i}^{on}\) ). Equations ( 5 )–( 8 ) specify the slopes of the email and direct mail variables as fixed across time and varying across segments. For example, the slope for email in the offline sales equation is a function of the overall effect ( \({\delta}_{00}^{off}\) ) and a segment-specific effect ( \({\delta}_{0i}^{off}\) ). Footnote 7

We combine the two levels in a single formulation, as shown in Eqs. ( 9 ) and ( 10 ):

Model Estimation

We estimate the model simultaneously using maximum likelihood for each country, allowing the errors of the equations to be correlated (Leckie & Charlton, 2013 ). We focus on the combined significance of the parameter estimates across countries using the meta-analytical test of added Z’s (Rosenthal, 1984 ), because our main interest is in the overall effects of online and offline marketing actions (ter Braak et al., 2014 ). This test allows us to derive more generalizable insights because it combines evidence of the six countries in our data. The effect size of the parameters are the weighted mean response elasticity parameters across countries. The weight is the inverse of the estimate’s standard error, normalized to 1. Thus, weighted coefficients can be interpreted as a reliability-weighted mean, with estimates with higher reliability (lower standard error) obtaining a higher weight (ter Braak et al., 2014 ).

Endogeneity

Our explanatory variables may not be strictly exogenous. For example, managers may set email and direct mail levels according to certain customer responsiveness. This type of endogeneity can be overcome by using exclusion restrictions. In the “Robustness checks” section, we derive these exclusion restrictions and explain how we use the control function (CF) approach to account for this source of endogeneity exploiting multi-country data (Papies et al., 2017 ; Wooldridge, 2015 ). In addition, we conducted a field experiment that assesses the causal effects.

Obtain out-of-sample predictions

We compare the forecast accuracy of the proposed HLMs with several benchmarks. We re-estimate the model parameters holding out 15% of the estimation period to evaluate prediction accuracy. We use three benchmarks commonly used by managers: random walk (i.e., the value in the previous period), last value in the estimation period, and mean of the country’s customer segment in the estimation period. We also use two machine learning models as benchmarks: random forests and support vector machines (Hennig-Thurau et al., 2015 ; Zhang & Chang, 2021 ). We evaluate the forecast accuracy with two measures: mean absolute error (MAE) and mean absolute percentage error (MAPE).

Reallocate optimally emails and direct mail

We (re)allocate emails and direct mail using the HLM estimates that incorporate customer value segments as drivers of marketing effectiveness, under the constraint of management’s maximum total number of emails and direct mail to avoid consumer fatigue and backlash (see Web Appendix A instead for a reallocation setup under the constraint of a total monetary budget). In doing so, we obtain the online and offline contributions in terms of sales increase per unit of email and direct mail per customer segment in each country (Dinner et al., 2014 ). For a given customer segment, we define the constrained resource allocation decision as

where Π is a differentiable profit function, m is the contribution margin (%), OFF  _  SALES is offline sales, ON  _  SALES is online sales, c em is the unit cost of emails (€), and c dm is the unit cost of direct mail (€). We note that the feasible region is compact by Eq. ( 11 ), and therefore Π attains a local maximum on the feasible region according to the Weierstrass theorem (Sundaram, 1996 ). Thus, the solution of this problem is characterized by the Karush–Kuhn–Tucker (KKT) conditions, which we develop in detail in Web Appendix B . Since the beauty retailer had upper bounds for both email and direct mail campaigns, the net returns of email ( NR em ) become:

Assuming c em is constant, we define  NR em  =  FC em  −  c em , where FC em denotes the financial contribution of emails. Then, as the short-term elasticities of offline and online sales with respect to number of emails are \({\eta}_{off, em}=\frac{\partial OFF\_ SALES}{\partial EMAIL}\ \frac{EMAIL}{OFF\_ SALES}\) and \({\eta}_{on, em}=\frac{\partial ON\_ SALES}{\partial EMAIL}\ \frac{EMAIL}{ON\_ SALES}\) , we can define FC em  as

Similarly, the financial contribution of direct mail is

International beauty retailer data

We obtained data from L’Occitane en Provence, an international natural and organic ingredient-based beauty and wellness products retailer. Its product portfolio includes skin care, hair care, fragrance, and body and bath offerings, and stores exclusively sell their own products. In addition to the brick-and-mortar stores, the company sells online through an e-commerce website for each country. These websites do not differ across countries, beyond the different languages.

The purchase transaction data, which cover four years between 2011 and 2014, include both online and offline transactions and discounts at purchase at the individual customer level for 84,110 customers. We randomly sampled customers from the firm’s six main countries: United States, Great Britain, Germany, France, Spain, and Italy. The data comprise prospect, dormant, and active customers.

The marketing communication data, which cover the years 2013 and 2014, contain all the online and offline communications from the retailer. The only online communication the retailer uses is email, and the data include whether and when the email was received, opened, and clicked. The only offline communication is direct mail, and the data include the start and end dates of the direct mail campaigns. According to the retailer’s management, the content is typically the same for both marketing actions; we employed two independent coders to confirm that this is the case for a sample of 385 emails and direct mail pieces from the United States and Great Britain (both were in English, the native language of the coders).

Beyond emails and direct mail, the company offers discounts, which we treat as a control variable in our model (Srinivasan et al., 2010 ). During the analysis period, the prices were the same in both the online and offline channels in each country. The firm has email and postal addresses for 42% and 65% of its customers, respectively. Footnote 8 In addition, the firm has the contact information of multiple prospects, who have shown interest in the brand at the point of sale or website but have not yet purchased from the firm.

Data operationalization

For the operationalization, we specify emails as an email sent, instead of “opened,” because emails sent represent a firm marketing decision. We operationalize the direct mail variable as 1 divided by the length of the campaign for each week of the campaign, because we do not know the exact day customers received the direct mail and thus must assume a constant impact throughout the campaign. We measure discount as the value amount of the discount (Wiesel et al., 2011 ). Finally, we test for seasonality by considering all periods, as in Srinivasan et al. ( 2004 ), but we find that seasonality occurs only for the Christmas period. We therefore create a dummy variable that takes the value of 1 between weeks 47 and 52 around the Christmas holiday. Table  3 provides descriptive statistics of the variables by country.

We aggregate the data at the weekly level to obtain a panel of customer transactions and marketing actions. We used 96 weeks of data for the calibration period to compute RFMC metrics and to create customer value segments. For the estimation of the HLMs, we used between 51 and 60 weeks, depending on data availability per country. These HLMs use log-transformed data to reduce skewness in the variables, to facilitate interpretation of the coefficients directly as elasticities, and to make comparisons among marketing actions, segments, and countries feasible; the estimated elasticities are the basis of the recommended effective marketing resource (re)allocation.

US apparel retailer data

We obtained data for a second retailer on all purchases and marketing communications for 23,891 randomly selected customers in the United States from 2010 to 2012. The retailer’s products, apparel and accessories targeted at women, are sold exclusively through company-owned brick-and-mortar stores or through the retailer’s own website. Similar to the beauty retailer, the retailer’s only online (offline) communication channel is email (direct mail). Moreover, this retailer has a different marketing approach than the beauty retailer; it allocates a larger proportion of emails to the medium- and high-value segments, while direct mail allocation is proportional to the size of the segments. Web Appendix C provides descriptive statistics.

Model-free evidence

We first explore the relationship between both direct mail and email and sales. We do so without imposing any structure in the data by examining the correlations at the individual customer level for the three predefined customer groups: prospects, dormants, and current customers.

As shown on Table  4 , the correlations between direct mail and sales are larger for prospects than for both dormants and current customers in four of the six countries (US, Great Britain, Germany, and Spain), while the correlation for prospects is of similar magnitude as for current customers in two countries (France and Italy). In contrast, for emails, the correlations with sales are mostly negative across these three customer groups and six countries and without a clear pattern of correlation magnitude. These results suggest that direct mail might be more effective for prospects.

Econometric analysis results

We begin with the results of the econometric analysis of the historical transaction data for both retailers. Then, we present several robustness checks where we: (1) specify a three-level cross-random-effects (CRE) model to evaluate sales variation drivers, (2) estimate a three-level HLM that combines all six countries, (3) estimate the HLM model with a Bayesian approach, and (4) assess endogeneity with the CF approach. We describe the field experiment design and results in the subsequent section.

International beauty retailer results

Customer value segments.

We compute customer value in terms of the RFMC metrics for each customer. With these metrics, we then create customer value segments using cluster analysis. Footnote 9 From the comparison of different cluster solutions (see Web Appendix D ), we obtain seven segments in the United States and Italy and six segments in Great Britain, Germany, France, and Spain. In each country, two segments consist of prospects and dormants, that is, customers who have never purchased from the retailer and customers who did not purchase during the two-year calibration period but have purchased before from the retailer. We label the other segments (i.e., consumers who made purchases during the calibration period) as nonrecent low value, recent low value, medium value, high value, and very high value. Table  5 reports the results of the cluster analysis. The table shows the breakdown of the customer value segments by country and the means and standard deviations of the RFMC metrics.

Prospects and dormants in combination represent at least half the customer base in all countries. However, there are notable country-specific differences: the United States has a larger proportion of prospects (38%) and a lower proportion of dormants (26%), while Great Britain has a larger proportion of dormants (40%) and a lower proportion of prospects (10%). The two low-value segments have similar levels of frequency, monetary value, and clumpiness but differ on the recency dimension. The recent low-value segment (nonrecent low-value segment) purchased, on average, eight weeks (one and half years) before the end of the calibration period. The United States (13%) and France (14%) have a lower proportion of these two segments. The medium-value segment mirrors the population average for the four metrics, while the high-value segments have large values of both frequency and monetary value. All countries are fairly similar in terms of the proportion of medium- and high-value customers, ranging from 25% to 30%, except the United States, which has a slightly lower representation of these customers (22%).

Effectiveness of direct mail and email

We estimate the HLMs with maximum likelihood estimation. All variables are stationary according to the augmented Dickey–Fuller and Levin–Lin–Chu panel unit-root tests (see Web Appendix E ). We check for homoskedasticity of the residuals (see Web Appendix F ). To determine the number of autoregressive terms, we test for residual autocorrelation, adding lags until the autocorrelation has been purged from the residuals; this resulted in two lags for the autoregressive terms. Our empirical findings suggest that random-effects components are not statistically significant in any of the six countries, and therefore a fixed-coefficients specification should be employed. Thus, in our models, we capture segment-level customer heterogeneity through the fixed-coefficients specification.

Table  6 presents the main results on the offline and online sales elasticities of email and direct mail for value segments consolidated across countries (ter Braak et al., 2014 ). Direct mail has positive and significant offline sales effects for prospects (.164, Z = 3.940, p  < .05). The magnitude of the estimated direct mail elasticity is in line with expectations from previous research: Danaher and Dagger ( 2013 ) report .104 as an average direct mail elasticity. and Danaher et al. ( 2020 ) find catalog elasticities of .02 (online) to .03 (in-store). Email, by contrast, has positive and significant online sales effects for medium- and high-value segments (.432, Z = 1.793 and .478, Z = 1.764, both p  < .1). We present the HLM estimation results for each country in Web Appendices H and I and the long-term elasticities in Web Appendix J .

In summary, we find important differences in the effectiveness of email and direct mail for channels and value segments. First, email has sales effects on medium- and high-value segments, while direct mail works only for prospects. Second, email has online sales effects, while direct mail has offline sales effects.

Out-of-sample forecasts

We compare the conditional forecast results for the last 15% of observations, for which the brand’s marketing-mix decisions are known. We obtain the forecasts from three traditional benchmarks (i.e., mean of customer value segment per country in the estimation period, the last period value in the estimation period, and a random walk) and from two machine learning models (i.e., random forest and support vector machines). As Table  7 shows, the best forecast accuracy comes from the HLM, given that it exploits the cross-sectional, time-series, and hierarchical structure of the data. Footnote 10

US apparel retailer results

For the second retailer, we compute the RFMC metrics for each individual customer at the weekly level for a calibration period of one year. We then segment the customer base according to the RFMC metrics into six segments to facilitate comparisons with the beauty retailer analysis. Table  8 shows that the proportion of customers in each segment is prospects (14%), dormants (7%), nonrecent low value (26%), recent low value (16%), medium value (34%), and high value (3%). We then evaluate the responsiveness to emails and direct mail in the estimation period consisting of 52 weeks.

Our results shown in Table  9 confirm the findings of the main analysis that own- and cross-channel effects of emails and direct mail vary by customer value segment. Specifically, direct mail has both offline and online effects for dormants (.02, p  < .05; .05 p  < 0.05, respectively), while email only has offline effects for both prospects and dormants (.12, p  < .01; .14 p  < 0.01, respectively). Notably, email shows only offline effects, and direct mail shows both offline and online effects.

Robustness checks

We test whether the results are robust to capturing country heterogeneity in a single main model, instead of having a separate model per each country. For the beauty retailer, first, we estimate three-level CRE models to evaluate the extent to which sales variation is explained by each possible level: time, customer value segment, and country. Second, we estimate a three-level HLM to incorporate country as a third level. We also present the robustness of our results to a Bayesian estimation and a CF approach.

Assessment of sales variation drivers

Similar to Hanssens et al. ( 2014 ), we estimate CRE models to examine the sales variation drivers. The CRE models show that for offline sales, customer value accounts for 90% of the explained variance, and country effects and time effects account for 8% and 2%, respectively. However, we find important differences for online sales—country effects explain as much as 50% of the explained variance, while customer value and time effects account for 42% and 8%, respectively. Thus, both country effects and customer value are essential to understand online sales variation, while customer value explains the majority of offline sales variation. All in all, the CRE results provide further empirical support for using multichannel marketing for customer value segments.

Analysis of countries jointly

Our model is flexible to allow resource allocation for customer segments at the global corporate level. That is, instead of six two-level HLMs, we estimate a three-level model, in which we constraint the number of segments to be the same in each country. This approach may be preferred by multinational retailers whose decisions for within-country allocations of expenditures between emails and direct mail are centralized. The number of optimal segments per country is six. The results are similar to the main results in both signs and significance. Specifically, the main finding that the most expensive marketing action, direct mail, is effective in driving customer acquisition of prospects in the offline channel holds (see Web Appendices K and L for details).

Bayesian estimation

To confirm that the results are not driven by the estimation procedure, we estimate the HLMs with a Bayesian approach for the main models and an alternative model with random intercepts, instead of fixed intercepts as in the main model. The results are similar to the main estimations in both signs and significance (see Web Appendix M ).

CF approach

The marketing communication variables might be correlated with the error term. Such endogeneity can be overcome using exclusion restrictions. We explore the possible estimate bias with a CF approach (Papies et al., 2017 ; Wooldridge, 2015 ), which is equivalent to the two-stage least squares approach for linear models but uses fitted values of the first stage as additional regressors in the second stage. To construct instruments for each country, we use the level of marketing in the other countries (Kuebler et al., 2018 ). The assumption is that country managers do not consider the sales levels of other countries when determining the marketing actions for a focal country (exclusion restriction). That is, managers set marketing actions levels expecting a response on the consumers they impact, i.e., customers in their country of responsibility and not in other countries. At the same time, managers follow similar strategies per segment across countries, and therefore marketing actions in the same segment may be correlated across countries (relevance condition). Indeed, the correlations between the instruments and the endogenous variables fall in the ranges of .88 and .94 for direct mail and .72 and .88 for email, supporting our assumption on the relevance condition.

The CF analysis largely confirms the main analysis results. The CF estimates coincide in terms of direction and significance with those of the main analysis, except for the effect of email on online sales for high-value customers in the United States (see Web Appendix N ). The instruments for the offline sales model are not significant (−.010, p  > .1 and .064, p  > .05, for direct mail and email, respectively), suggesting that the estimates of the offline sales model in the main analysis are not biased. However, the instruments for the online sales model are positive and significant (.112, p  < .05 and .161, p  < .05, for direct mail and email, respectively). When we account for this positive bias, the online equation results in a nonsignificant effect of emails for high-value customers in the United States. Moreover, the magnitude of the effect of email on online sales for high value customers in Italy and France is reduced but remains significant. All other results remain the same.

• Field experiment

Field experiment design

The main goal of the field experiment is to test the model-based findings on the differential effects of emails and direct mail by customer value segment in a controlled causal setting. We designed and implemented the experiment together with the marketing team of the beauty retailer between July and November 2017 in Italy. The four experimental cells are (1) control (no marketing), (2) only emails, (3) only direct mail, and (4) both emails and direct mail. To ensure a balanced proportion in each cell, we stratified each cell in the six customer value segments. To create the six segments, we obtained individual-customer purchase data spanning two years before the experiment. The field experiment took into account customers’ expressed preferences not to be contacted by certain channels and therefore was run on a sample of customers contactable by both channels, to avoid self-selection, to compare email and direct mail responsiveness in online and offline channels. Although a pure random assignment should result in each segment being equally represented in the four experimental cells in theory, proportionate stratification ensures that all segments are equally represented in each cell in practice (Duflo et al., 2007 ). This stratification is especially important because the total amount of direct mail was constrained for budgetary reasons to 33,000 pieces, and we wanted to ensure that high-value customers, who are a small fraction of the overall population, are proportionally represented in cells 3 and 4. The total sample consists of 122,394 customers (Table  10 ).

To evaluate the differential effects of the treatment groups, we specify a random-effects regression for customers in the prospect and dormant segments, because the treatment is exogenous (Chintagunta et al., 1991 ). For customers in the other four value segments, we specify a difference-in-differences regression, because the treatment is exogenous and customers in these segments purchased within the two-year period before the experiment. We run a separate regression per each segment, in which customer sales ( SALES ) vary per customer (index i ) and week (index t ). Equation ( 14 ) presents the random-effects regression and considers only the campaign period because prospects and dormants did not purchase before the experiment. Equation ( 15 ) presents the difference-in-differences regression and considers the campaign period and the two years prior.

where α i represents the customer-level intercept; CELL2 , CELL3 , and CELL4 capture whether the customer belongs to cells 2, 3, and 4, respectively; 𝛾 t represents time fixed effects; CAMPAIGN is a dummy variable that takes the value of 1 if the period belongs to the campaign and 0 otherwise; and ε it is the residual error. The coefficients of interest are β 2 , β 3 , and β 4 for Eq. ( 14 ) and β 5 , β 6 , and β 7 for Eq. ( 15 ).

Field experiment results

Figure  1 shows the results of the field experiment on the differential effectiveness of email and direct mail for different consumer value segments. First, we confirm that direct mail is only effective for prospects, with an elasticity of .132 ( p  < .05), compared with the .164 estimate in the main analysis. Second, email is not effective for any of the segments, while it was significantly effective for medium- and high-value segments in the main analysis. Third, direct mail and email in combination (interaction effects) are effective for the medium-value segment (.011, p  < .05), while the two marketing actions did not interact significantly in the main analysis; this effect, though significant, is small.

Email and direct mail effectiveness from field experiment for beauty retailer. Notes: Confidence level of error bars at p < .05.

Managerial implications

We calculate revenue lifts from (1) the econometric analysis of the beauty retailer data, (2) the econometric analysis of the apparel retailer, and (3) the field experiment. To calculate the financial contribution of emails and direct mail (Eqs. ( 12 ) and ( 13 )), we take the elasticity estimates from the empirical models and the mean levels of sales, emails, and direct mail per customer segment from the data. According to the beauty retailer’s annual report (L’Occitane, 2015 ), the cost of goods sold is 18%, and therefore we infer that the profit margin is 82%. Keeping the total number of emails and direct mail constrained in each country and holding the budget constant, Footnote 11 we assess how much the reallocation of marketing resources would improve the financial contribution.

Figure  2 compares the current allocation of marketing resources with the proposed reallocation and reports the sizes of the customer value segments (see Web Appendix O for details by country). For emails, the current allocation is proportional to the size of the customer value segments (i.e., “bigger gets more”; Corstjens & Merrihue, 2003 , p. 118); our reallocation proposes to reduce emails for prospects, dormants, and recent low-value segment and to increase them for nonrecent low-, medium-, and high-value segments, based on their response elasticities and segment sizes. For direct mail, the current allocation disproportionally considers the medium- and high-value segments and disregards prospects (i.e., the most expensive action for the most valuable customers); our reallocation suggests shifting direct mail to prospects. We evaluate the incremental revenue from the proposed reallocation by multiplying the financial contribution of the segment by the difference between the model-based proposed number of emails and direct mail and the actual number sent by the retailer based on the HLM.

Effective reallocation of emails and direct mail for beauty retailer

Our reallocation of marketing actions would yield a sales lift of €340,000, 33% due to better allocation of emails and 67% due to better allocation of direct mail, which represents a 13.5% total revenue increase. Given the beauty retailer’s size, the global implementation of the proposed reallocations would amount to hundreds of millions of euros in incremental revenues. Footnote 12 For the apparel retailer, the effective reallocation of marketing actions would yield a sales lift of $26,000, 84% due to better allocation of emails and 16% due to better allocation of direct mail, which represents a 9.3% revenue increase.

Finally, we quantify the revenue lift potential with a marketing resource allocation that considers the field experiment estimates. We compute the revenue lift with respect to the status quo of the typical marketing allocation used by the retailer, as this condition is not present in our experimental cells ( CELL1 in the experiment receives no marketing, which is not business-as-usual). Collectively, the marketing resource reallocation from the field experiment findings lifts revenue by 6.5% with respect to business-as-usual, holding marketing costs constant. The business-as-usual allocation has a revenue impact lift of 1.6% with respect to the control group of no marketing actions. Thus, we expect that a chainwide implementation of these recommendations will result in a lift of between 6.5% (from the field experiment) and 13.5% (using HLMs) in revenue for the beauty retailer.

Communication of these insights to the beauty retailer helped management adopt data-driven analytical tools and blend quantitative approaches with managerial intuition (Roberts, 2000 ). As one member of the marketing team noted: “The different effectiveness of direct mail and email depending on the customer type was surprising to us. Rethinking about this finding, we have a deep and increasing interest in investing in direct mail activities for customer acquisition and inactive customers.” The model-based recommendations helped the retailer embrace scientific decision-support systems and provided an opportunity to use marketing analytical dashboards with hands-on practice. In the words of Delphine Fournier, customer relationship management manager of L’Occitane: “The combination of marketing science tools with experimentation gives us a new perspective in understanding marketing effectiveness and helps us improve our resource allocation tremendously” (ISMS Practice Prize, 2018 ). L’Occitane has since implemented this model-based decision-making procedure consisting of iterative, model experiment, phases (Hanssens & Pauwels, 2016 ), and embedded marketing science models into its decision processes (Kumar & Petersen, 2005 ; Lilien, 2011 ).

Conclusions

Understanding online and offline sales responsiveness to email and direct mail for multichannel retailers is essential for academics and practitioners. Accordingly, we propose a systematic approach to quantify how email and direct mail influence online and offline sales for different customer value segments across countries. We conduct an empirical analysis using data from a beauty retailer with 84,110 customers from six countries and run a field experiment with 122,000 customers in one country for the retailer. We replicate the econometric analysis for an apparel retailer. In addition, we conduct several robustness checks to assess the validity of our findings.

This research provides four key insights. First, direct mail drives customer acquisition in the offline channel, while email drives both online and offline sales across different customer segments. Second, the model performs considerably better than benchmarks (up to 50%) in forecasting sales for channels and countries. Third, a reallocation of the marketing budget for customer value groups shows substantial revenue improvement of 13.5% for the HLM-based analysis and a revenue lift of 6.5% in the field experiment. Our model can be readily applied to other settings, as indicated by the 9.3% calculated revenue improvement for the apparel retailer. Moreover, the results of the field experiment in one country provide causal support for our empirical model findings.

Our findings challenge common wisdom, though they are consistent with surveys on different consumer experiences with direct mail versus emails. Receiving an expensive direct mail is more likely than an email to attract the attention of customers who have never purchased or stopped purchasing a while ago (dormants). This interpretation fits the broader consumer behavior theory that affective reactions are critical (e.g., Hoch & Loewenstein, 1991 ; Shiv & Fedorikhin, 1999 ); we would also add that emotional appeals are especially important to attract the attention of and gain new customers, while current customers do not need them to the same degree.

We offer several important insights for retail managers operating in a multichannel context. To allocate marketing resources effectively, managers should pay close attention to the different responsiveness of customer value segments to emails and direct mail. Both customer value and country effects are relevant to understand the online sales variation, even among the similar Western countries we analyzed. Our methodology can help retailers forecast future sales and optimally allocate marketing resources. Several of our insights may inspire companies to reassess how they run their email and direct mail campaigns. First, a customer’s “high-value” status with the company does not mean greater responsiveness to marketing actions. In our analysis, we find that such customers are less responsive to the (very expensive) direct mail. Second, as newly penetrated countries typically have a higher share of prospective customers and light buyers, direct mail resources might best be allocated to such countries. Finally, customer privacy issues have become even more important with recent legal developments, such as the GDPR, raising the stakes for companies to identify and target responsive customers.

This research has limitations that suggest directions for future research. First, we did not examine the order of emails and direct mail; thus, future research could test the ideal sequencing of email and direct mail, as “email makes for the perfect follow up to a direct mail campaign” (Bozeman, 2019 ) and companies should “create a lasting first impression with direct mail [and] reinforce it with email marketing” (Niblock, 2017 ). Future research could also explore a continuous (discrete) time dynamic optimization model through which Hamiltonian (Bellman) equations would be specified. Second, our data do not include competitors’ marketing actions. However, for both retail data sets used, the own-brand products are sold exclusively by the companies in question, rendering competition only indirect. Furthermore, future research could quantify marketing’s power to build long-term brand equity or to upgrade customers to higher-value segments. Our methodology can also be applied beyond the studied developed Western markets (e.g., developing countries), the analyzed product categories, and the studied channels (e.g., mobile) or marketing actions (e.g., phone calls, text notifications). In this study, we propose and implement a generalizable methodology for marketing resource allocation, which can be applied by any multichannel (multinational) retailer, whether they sell products or services, and can accommodate any number of countries, sales and communication channels. Finally, we call for future research to examine other regions to determine whether the findings generalize to non-Western countries.

Survey with N = 351, average experience = 3.8 years. The remainder (13%) agreed with the statement, “The most expensive communication should be sent to the least valuable customers.”

Other data (e.g., demographics, preferences, needs, attitudes) were not available for our partner companies.

Zhang et al. ( 2014 ) propose four measures (entropy, second moment, log utility, and sum of three largest components) and show that entropy is the most robust with the best performance.

Marketers have a long history of working with both a priori segmentation and latent response segments (e.g., Kamakura & Russell, 1989 ). The latter requires observing marketing response and leaves explaining the observed response differences to other analyses (e.g., comparing a priori customer characteristics to make the latent segments addressable). By contrast, a priori segmentation uses variables the company can observe (e.g., demographics) and then shows how marketing responses differ between these segments. A priori segmentation has evolved from demographics to customer purchase histories such as RFMC, which drive marketing response and are actionable for the company (e.g., Zhang et al., 2014 ). The evolving convention in the RFMC literature and our discussion with managers led us to choose this segmentation.

We estimated a model with heterogenous autoregressive coefficients across segments to assess whether they varied by segment. The likelihood ratio test results suggested the homogenous autoregressive coefficients across segments for all countries, except France. For France, we based our decision on the information criteria (AIC and BIC) result (see Web Appendix G), which favored the homogenous autoregressive coefficients across segments.

We estimated a model with interaction terms between the marketing actions to test whether they showed synergistic effects. Since we did not find significant synergistic effects, we choose to keep a more parsimonious specification in the model specification.

For the segment-specific intercepts and slopes, we use the fixed-effects formulation. An alternative approach is to use a random-effects specification that treats parameters as realizations of random variables following a probability distribution. To determine which specification to follow, we estimate the model with random-effects and test the significance of the random components. Our results favor the use of fixed-effects specification. We discuss this finding in the results section. This choice is also consistent with the recommendation that the fixed-effects approach should be used when the data have a small number of groups (i.e., fewer than 10) (Snijders & Bosker, 2011 ; Steenkamp & Geyskens, 2014 ).

We randomly selected the data for the econometric analysis in each country from the full customer base. Therefore, some sampled customers might not be contactable. The field experiment addresses the potential self-selection issue: we only include in the experiment the 120,000-plus customers who are contactable by email and direct mail to assess their responsiveness to both channels.

To select the number of cluster solutions, we take into account model requirement constraints, statistical criteria, and managerial considerations. We examine the reduction of variance in the RFMC metrics explained by the different number of clusters in each country. To this end, we use the comparison criteria of within-sum-of-squares, proportional reduction variance (eta coefficient), and proportional reduction error (Makles, 2012 ).

We focus on over-time forecasting validation because the HLM exploits the time-series structure as well as the cross-sectional and hierarchical structure of the data. However, we also perform a k-fold cross-validation. The fivefold validation uses 80% of the customers in a segment to predict the other 20%, rotating this approach through the full sample five times. The results based on the fivefold specification indicate an MAE and a MAPE of .732 and .265 for the offline sales equation, respectively, and .670 and .606 for the online sales equation, respectively.

The reason companies do not totally skew toward emails is twofold: (1) the optimal allocation depends on the ratio of elasticities (e.g., Dorfman & Steiner, 1954 ; Wright, 2009 ), and (2) companies want to avoid losing consumer goodwill by exceeding an unknown annoyance level of emails. We worked with the client, which set a maximum of three emails per week (seven in the United States). If we had not worked with a limit, some segments would have received two emails a day (i.e., 14 in one week), which seemed excessive to the managers.

Following Fischer et al. ( 2011 ), we also evaluate the reallocation considering the growth potential per segment and country applying a segment size multiplier. We obtain the multiplier from the growth observed in each segment. The reallocation results that consider this growth remain practically the same.

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Acknowledgements

We are grateful to the Wharton Customer Analytics Initiative for providing the data sets used in this study and the management of L’Occitane en Provence for their collaboration in this project and for their feedback. We thank Eric Bradlow, Peter Fader, Dominique Hanssens, Gary Lilien, John Roberts, and Christian Schulze for their useful suggestions on this work. The first author is grateful for Boston University’s Questrom School of Business doctoral funding support.

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Valenti, A., Srinivasan, S., Yildirim, G. et al. Direct mail to prospects and email to current customers? Modeling and field-testing multichannel marketing. J. of the Acad. Mark. Sci. (2023). https://doi.org/10.1007/s11747-023-00962-2

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DOI : https://doi.org/10.1007/s11747-023-00962-2

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Title: prompting for numerical sequences: a case study on market comment generation.

Abstract: Large language models (LLMs) have been applied to a wide range of data-to-text generation tasks, including tables, graphs, and time-series numerical data-to-text settings. While research on generating prompts for structured data such as tables and graphs is gaining momentum, in-depth investigations into prompting for time-series numerical data are lacking. Therefore, this study explores various input representations, including sequences of tokens and structured formats such as HTML, LaTeX, and Python-style codes. In our experiments, we focus on the task of Market Comment Generation, which involves taking a numerical sequence of stock prices as input and generating a corresponding market comment. Contrary to our expectations, the results show that prompts resembling programming languages yield better outcomes, whereas those similar to natural languages and longer formats, such as HTML and LaTeX, are less effective. Our findings offer insights into creating effective prompts for tasks that generate text from numerical sequences.

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