IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v64y2018i11p5105-5131.html
   My bibliography  Save this article

Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook

Author

Listed:
  • Dokyun Lee

    (Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • Kartik Hosanagar

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Harikesh S. Nair

    (Stanford Graduate School of Business, Stanford University, Stanford, California 94305; JD.com American Technologies Corporation USA, Santa Clara, California 95054)

Abstract

We describe the effect of social media advertising content on customer engagement using data from Facebook. We content-code 106,316 Facebook messages across 782 companies, using a combination of Amazon Mechanical Turk and natural language processing algorithms. We use this data set to study the association of various kinds of social media marketing content with user engagement—defined as Likes , comments, shares, and click-throughs—with the messages. We find that inclusion of widely used content related to brand personality—like humor and emotion—is associated with higher levels of consumer engagement ( Likes , comments, shares) with a message. We find that directly informative content—like mentions of price and deals—is associated with lower levels of engagement when included in messages in isolation, but higher engagement levels when provided in combination with brand personality–related attributes. Also, certain directly informative content, such as deals and promotions, drive consumers’ path to conversion (click-throughs). These results persist after incorporating corrections for the nonrandom targeting of Facebook’s EdgeRank (News Feed) algorithm and so reflect more closely user reaction to content than Facebook’s behavioral targeting. Our results suggest that there are benefits to content engineering that combines informative characteristics that help in obtaining immediate leads (via improved click-throughs) with brand personality–related content that helps in maintaining future reach and branding on the social media site (via improved engagement). These results inform content design strategies. Separately, the methodology we apply to content-code text is useful for future studies utilizing unstructured data such as advertising content or product reviews.

Suggested Citation

  • Dokyun Lee & Kartik Hosanagar & Harikesh S. Nair, 2018. "Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook," Management Science, INFORMS, vol. 64(11), pages 5105-5131, November.
    • Handle: RePEc:inm:ormnsc:v:64:y:2018:i:11:p:5105-5131
    DOI: 10.1287/mnsc.2017.2902
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/mnsc.2017.2902
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.2017.2902?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Dina Mayzlin & Jiwoong Shin, 2011. "Uninformative Advertising as an Invitation to Search," Marketing Science, INFORMS, vol. 30(4), pages 666-685, July.
    2. Bharat Anand & Ron Shachar, 2009. "Targeted advertising as a signal," Quantitative Marketing and Economics (QME), Springer, vol. 7(3), pages 237-266, September.
    3. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273.
    4. Rishika Rishika & Ashish Kumar & Ramkumar Janakiraman & Ram Bezawada, 2013. "The Effect of Customers' Social Media Participation on Customer Visit Frequency and Profitability: An Empirical Investigation," Information Systems Research, INFORMS, vol. 24(1), pages 108-127, March.
    5. Gene M. Grossman & Carl Shapiro, 1984. "Informative Advertising with Differentiated Products," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 51(1), pages 63-81.
    6. Harikesh S. Nair & Sanjog Misra & William J. Hornbuckle IV & Ranjan Mishra & Anand Acharya, 2017. "Big Data and Marketing Analytics in Gaming: Combining Empirical Models and Field Experimentation," Marketing Science, INFORMS, vol. 36(5), pages 699-725, September.
    7. Simon P. Anderson & Régis Renault, 2006. "Advertising Content," American Economic Review, American Economic Association, vol. 96(1), pages 93-113, March.
    8. Milgrom, Paul & Roberts, John, 1986. "Price and Advertising Signals of Product Quality," Journal of Political Economy, University of Chicago Press, vol. 94(4), pages 796-821, August.
    9. K. Sudhir & Subroto Roy & Mathew Cherian, 2016. "Do Sympathy Biases Induce Charitable Giving? The Effects of Advertising Content," Marketing Science, INFORMS, vol. 35(6), pages 849-869, November.
    10. Jura Liaukonyte & Thales Teixeira & Kenneth C. Wilbur, 2015. "Television Advertising and Online Shopping," Marketing Science, INFORMS, vol. 34(3), pages 311-330, May.
    11. William Greene, 2004. "The behaviour of the maximum likelihood estimator of limited dependent variable models in the presence of fixed effects," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 98-119, June.
    12. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    13. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    14. K. Sudhir & Subroto Roy & Mathew Cherian, 2014. "Do Sympathy Biases Induce Charitable Giving" The Effects of Advertising Content," Cowles Foundation Discussion Papers 1940, Cowles Foundation for Research in Economics, Yale University, revised Jan 2016.
    15. Kihlstrom, Richard E & Riordan, Michael H, 1984. "Advertising as a Signal," Journal of Political Economy, University of Chicago Press, vol. 92(3), pages 427-450, June.
    16. Navdeep S. Sahni & S. Christian Wheeler & Pradeep Chintagunta, 2018. "Personalization in Email Marketing: The Role of Noninformative Advertising Content," Marketing Science, INFORMS, vol. 37(2), pages 236-258, March.
    17. Ahn, Hyungtaik & Powell, James L., 1993. "Semiparametric estimation of censored selection models with a nonparametric selection mechanism," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 3-29, July.
    18. Oded Netzer & Ronen Feldman & Jacob Goldenberg & Moshe Fresko, 2012. "Mine Your Own Business: Market-Structure Surveillance Through Text Mining," Marketing Science, INFORMS, vol. 31(3), pages 521-543, May.
    19. Nelson, Philip, 1974. "Advertising as Information," Journal of Political Economy, University of Chicago Press, vol. 82(4), pages 729-754, July/Aug..
    20. Pedro M. Gardete, 2013. "Cheap-Talk Advertising and Misrepresentation in Vertically Differentiated Markets," Marketing Science, INFORMS, vol. 32(4), pages 609-621, July.
    21. Matthew Gentzkow & Jesse M. Shapiro, 2010. "What Drives Media Slant? Evidence From U.S. Daily Newspapers," Econometrica, Econometric Society, vol. 78(1), pages 35-71, January.
    22. Mark Armstrong & Robert Porter (ed.), 2007. "Handbook of Industrial Organization," Handbook of Industrial Organization, Elsevier, edition 1, volume 3, number 1.
    23. Gerard R. Butters, 1977. "Equilibrium Distributions of Sales and Advertising Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 44(3), pages 465-491.
    24. Bagwell, Kyle, 2007. "The Economic Analysis of Advertising," Handbook of Industrial Organization, in: Mark Armstrong & Robert Porter (ed.), Handbook of Industrial Organization, edition 1, volume 3, chapter 28, pages 1701-1844, Elsevier.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Salvatore Piccolo & Piero Tedeschi & Giovanni Ursino, 2018. "Deceptive Advertising with Rational Buyers," Management Science, INFORMS, vol. 64(3), pages 1291-1310, March.
    2. Simon P. Anderson & Régis Renault, 2013. "The Advertising Mix for a Search Good," Management Science, INFORMS, vol. 59(1), pages 69-83, April.
    3. Dina Mayzlin & Jiwoong Shin, 2011. "Uninformative Advertising as an Invitation to Search," Marketing Science, INFORMS, vol. 30(4), pages 666-685, July.
    4. Tingting Nian & Arun Sundararajan, 2022. "Social Media Marketing, Quality Signaling, and the Goldilocks Principle," Information Systems Research, INFORMS, vol. 33(2), pages 540-556, June.
    5. Soberman, David A. & Xiang, Yi, 2022. "Designing the content of advertising in a differentiated market," International Journal of Research in Marketing, Elsevier, vol. 39(1), pages 190-211.
    6. Brett R Gordon & Kinshuk Jerath & Zsolt Katona & Sridhar Narayanan & Jiwoong Shin & Kenneth C Wilbur, 2019. "Inefficiencies in Digital Advertising Markets," Papers 1912.09012, arXiv.org, revised Feb 2020.
    7. Pedro M. Gardete, 2013. "Cheap-Talk Advertising and Misrepresentation in Vertically Differentiated Markets," Marketing Science, INFORMS, vol. 32(4), pages 609-621, July.
    8. Belleflamme,Paul & Peitz,Martin, 2015. "Industrial Organization," Cambridge Books, Cambridge University Press, number 9781107687899.
    9. Yang, Yupin & Lu, Qiang (Steven) & Tang, Guanting & Pei, Jian, 2015. "The Impact of Market Competition on Search Advertising," Journal of Interactive Marketing, Elsevier, vol. 30(C), pages 46-55.
    10. Laurent Cavenaile & Pau Roldan-Blanco, 2021. "Advertising, Innovation, and Economic Growth," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 251-303, July.
    11. Guofang Huang & Matthew Shum & Wei Tan, 2019. "Is pharmaceutical detailing informative? Evidence from contraindicated drug prescriptions," Quantitative Marketing and Economics (QME), Springer, vol. 17(2), pages 135-160, June.
    12. Justin P. Johnson & David P. Myatt, 2006. "On the Simple Economics of Advertising, Marketing, and Product Design," American Economic Review, American Economic Association, vol. 96(3), pages 756-784, June.
    13. Levent Çelik, 2008. "Monopoly Provision of Tune-ins," CERGE-EI Working Papers wp362, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    14. Anderson, Simon P. & Gabszewicz, Jean J., 2006. "The Media and Advertising: A Tale of Two-Sided Markets," Handbook of the Economics of Art and Culture, in: V.A. Ginsburgh & D. Throsby (ed.), Handbook of the Economics of Art and Culture, edition 1, volume 1, chapter 18, pages 567-614, Elsevier.
    15. Simon P. Anderson & Régis Renault, 2006. "Advertising Content," American Economic Review, American Economic Association, vol. 96(1), pages 93-113, March.
    16. Baker Matthew J. & George Lisa M, 2010. "The Role of Television in Household Debt: Evidence from the 1950's," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-38, May.
    17. Guillem Roig, 2017. "Product Compatibility as an Strategy to Hinder Entry Deterrence," Documentos de Trabajo 15773, Universidad del Rosario.
    18. Yuxin Chen & Qihong Liu, 2022. "Signaling Through Advertising When an Ad Can Be Blocked," Marketing Science, INFORMS, vol. 41(1), pages 166-187, January.
    19. Archishman Chakraborty & Rick Harbaugh, 2014. "Persuasive Puffery," Marketing Science, INFORMS, vol. 33(3), pages 382-400, May.
      • Archishman Chakraborty & Rick Harbaugh, 2012. "Persuasive Puffery," Working Papers 2012-05, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    20. Yogesh V. Joshi & Andres Musalem, 2021. "When Consumers Learn, Money Burns: Signaling Quality via Advertising with Observational Learning and Word of Mouth," Marketing Science, INFORMS, vol. 40(1), pages 168-188, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:64:y:2018:i:11:p:5105-5131. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.