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Increasing the effectiveness of display social media ads for startups: The role of different claims and executional characteristics

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  • Hervet, Guillaume
  • Guitart, Ivan A.

Abstract

Although social media ads are the preferred advertising format for entrepreneurs, the literature has paid little attention to this advertising form in the startup context. In collaboration with a startup, we conducted randomized field experiments reaching more than 800,000 potential customers to assess the effectiveness of display social media ads and explore how different claims and executional characteristics impact this effectiveness. The experiments were the company’s first advertising campaign in an effort to expand to a new country. Our analyses show that the elasticity of display social media ads is equal to 0.815 and 98% of the effect occurs within two hours. We also find that adding informative claims to an ad reduces the click-through rate (CTR) by between 24.8% and 43%. Regarding executional characteristics, we find that ad repetition significantly increases the CTR by 19.9%, whereas including a character and using gender-congruity in ads do not significantly increase their CTR.

Suggested Citation

  • Hervet, Guillaume & Guitart, Ivan A., 2022. "Increasing the effectiveness of display social media ads for startups: The role of different claims and executional characteristics," Journal of Business Research, Elsevier, vol. 153(C), pages 467-478.
    • Handle: RePEc:eee:jbrese:v:153:y:2022:i:c:p:467-478
    DOI: 10.1016/j.jbusres.2022.08.052
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    References listed on IDEAS

    as
    1. Pham, Michel Tuan & Geuens, Maggie & De Pelsmacker, Patrick, 2013. "The influence of ad-evoked feelings on brand evaluations: Empirical generalizations from consumer responses to more than 1000 TV commercials," International Journal of Research in Marketing, Elsevier, vol. 30(4), pages 383-394.
    2. Joo, Mingyu & Wilbur, Kenneth C. & Zhu, Yi, 2016. "Effects of TV advertising on keyword search," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 508-523.
    3. Nelson, Phillip J, 1975. "The Economic Consequences of Advertising," The Journal of Business, University of Chicago Press, vol. 48(2), pages 213-241, April.
    4. Ivan Guitart & Guillaume Hervet, 2017. "The impact of contextual television ads on online conversions : An application in the insurance industry," Post-Print hal-02312174, HAL.
    5. Brett R. Gordon & Florian Zettelmeyer & Neha Bhargava & Dan Chapsky, 2019. "A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook," Marketing Science, INFORMS, vol. 38(2), pages 193-225, March.
    6. Yaping Chang & You Li & Jun Yan & V. Kumar, 2019. "Getting more likes: the impact of narrative person and brand image on customer–brand interactions," Journal of the Academy of Marketing Science, Springer, vol. 47(6), pages 1027-1045, November.
    7. Alalwan, Ali Abdallah, 2018. "Investigating the impact of social media advertising features on customer purchase intention," International Journal of Information Management, Elsevier, vol. 42(C), pages 65-77.
    8. Guitart, Ivan A. & Hervet, Guillaume, 2017. "The impact of contextual television ads on online conversions: An application in the insurance industry," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 480-498.
    9. Darke, Peter R. & Brady, Michael K. & Benedicktus, Ray L. & Wilson, Andrew E., 2016. "Feeling Close From Afar: The Role of Psychological Distance in Offsetting Distrust in Unfamiliar Online Retailers," Journal of Retailing, Elsevier, vol. 92(3), pages 287-299.
    10. Pham, Michel Tuan, 1998. "Representativeness, Relevance, and the Use of Feelings in Decision Making," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(2), pages 144-159, September.
    11. Xiang Fang & Surendra Singh & Rohini Ahluwalia, 2007. "An Examination of Different Explanations for the Mere Exposure Effect," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(1), pages 97-103, March.
    12. Anja Lambrecht & Catherine Tucker & Caroline Wiertz, 2018. "Advertising to Early Trend Propagators: Evidence from Twitter," Marketing Science, INFORMS, vol. 37(2), pages 177-199, March.
    13. Ackerberg, Daniel A, 2001. "Empirically Distinguishing Informative and Prestige Effects of Advertising," RAND Journal of Economics, The RAND Corporation, vol. 32(2), pages 316-333, Summer.
    14. Miniard, Paul W, et al, 1991. "Picture-Based Persuasion Processes and the Moderating Role of Involvement," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(1), pages 92-107, June.
    15. Ivan A. Guitart & Guillaume Hervet & Sarah Gelper, 2020. "Competitive advertising strategies for programmatic television," Journal of the Academy of Marketing Science, Springer, vol. 48(4), pages 753-775, July.
    16. Jia Liu & Shawndra Hill, 2021. "Frontiers: Moment Marketing: Measuring Dynamics in Cross-Channel Ad Effectiveness," Marketing Science, INFORMS, vol. 40(1), pages 13-22, January.
    17. Hans Haans & Néomie Raassens & Roel Hout, 2013. "Search engine advertisements: The impact of advertising statements on click-through and conversion rates," Marketing Letters, Springer, vol. 24(2), pages 151-163, June.
    18. Lohtia, Ritu & Donthu, Naveen & Hershberger, Edmund K., 2003. "The Impact of Content and Design Elements on Banner Advertising Click-through Rates," Journal of Advertising Research, Cambridge University Press, vol. 43(4), pages 410-418, December.
    19. Nickel, Kristina & Orth, Ulrich R. & Kumar, Minu, 2020. "Designing for the genders: The role of visual harmony," International Journal of Research in Marketing, Elsevier, vol. 37(4), pages 697-713.
    20. Reed, Americus & Forehand, Mark R. & Puntoni, Stefano & Warlop, Luk, 2012. "Identity-based consumer behavior," International Journal of Research in Marketing, Elsevier, vol. 29(4), pages 310-321.
    21. Ivan Guitart & Stefan Stremersch, 2021. "The impact of informational and emotional television ad content on online search and sales," Post-Print hal-03193729, HAL.
    22. Mingyu Joo & Kenneth C. Wilbur & Bo Cowgill & Yi Zhu, 2014. "Television Advertising and Online Search," Management Science, INFORMS, vol. 60(1), pages 56-73, January.
    23. Janiszewski, Chris, 1993. "Preattentive Mere Exposure Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(3), pages 376-392, December.
    24. Philip Hans Franses, 2004. "Fifty years since Koyck (1954)," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 381-387, November.
    25. MacInnis, Deborah J & Price, Linda L, 1987. "The Role of Imagery in Information Processing: Review and Extensions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(4), pages 473-491, March.
    26. Eelco Kappe & Ashley Stadler Blank & Wayne S. DeSarbo, 2014. "A General Multiple Distributed Lag Framework for Estimating the Dynamic Effects of Promotions," Management Science, INFORMS, vol. 60(6), pages 1489-1510, June.
    27. Fennis, Bob M. & Das, Enny & Fransen, Marieke L., 2012. "Print advertising: Vivid content," Journal of Business Research, Elsevier, vol. 65(6), pages 861-864.
    28. 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.
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    Cited by:

    1. Chen, Jiawen & Liu, Linlin, 2023. "Social media usage and entrepreneurial investment: An information-based view," Journal of Business Research, Elsevier, vol. 155(PB).

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