IDEAS home Printed from https://ideas.repec.org/a/bla/popmgt/v32y2023i12p4005-4020.html
   My bibliography  Save this article

Strategic social media marketing: An empirical analysis of sequential advertising

Author

Listed:
  • Parshuram Hotkar
  • Rajiv Garg
  • Kristen Sussman

Abstract

Social media platforms like Facebook and Twitter have emerged as effective channels for advertising that enable consumer targeting based on demographics, interests, and user behavior. Social media marketers have utilized information spillover within these platforms to reach a larger customer base. This information spillover also exists across groups of users within the platform and enhances returns from social media advertising. Thus, this information spillover can be utilized to strategically sequence targeted advertising to amplify the returns from social media ads. In this paper, we present a theoretical model for information retention and show that the sequential advertising strategy is effective in targeting groups of users on a social media platform. In addition, we provide empirical evidence through two series of randomized field experiments. From experiments for a health services organization, we find that sequential advertising campaigns provide 23% more clicks when compared to campaigns that target groups simultaneously, which translates to a saving of 18.7% in the advertising budget to achieve similar results as simultaneous advertising. Additionally, we found that sequential advertising campaigns targeting a smaller group first followed by a larger group provide 10.7% additional clicks when compared to targeting a larger group first followed by a smaller group. These results were consistent for consumer packaged goods that were advertised on Facebook and Twitter. These results provide implications for social media advertising research and practice.

Suggested Citation

  • Parshuram Hotkar & Rajiv Garg & Kristen Sussman, 2023. "Strategic social media marketing: An empirical analysis of sequential advertising," Production and Operations Management, Production and Operations Management Society, vol. 32(12), pages 4005-4020, December.
  • Handle: RePEc:bla:popmgt:v:32:y:2023:i:12:p:4005-4020
    DOI: 10.1111/poms.14075
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/poms.14075
    Download Restriction: no

    File URL: https://libkey.io/10.1111/poms.14075?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. Simon P. Anderson & André de Palma, 2012. "Competition for attention in the Information (overload) Age," RAND Journal of Economics, RAND Corporation, vol. 43(1), pages 1-25, March.
    2. Sulin Ba & Shu He & Shun‐Yang Lee, 2022. "Mobile App Adoption and Its Differential Impact on Consumer Shopping Behavior," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 764-780, February.
    3. Cangqi Zhou & Qianchuan Zhao & Wenbo Lu, 2015. "Impact of Repeated Exposures on Information Spreading in Social Networks," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-21, October.
    4. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    5. Yifan Dou & Marius F. Niculescu & D. J. Wu, 2013. "Engineering Optimal Network Effects via Social Media Features and Seeding in Markets for Digital Goods and Services," Information Systems Research, INFORMS, vol. 24(1), pages 164-185, March.
    6. Mahmood Pedram & Subramanian Balachander, 2015. "Increasing Quality Sequence: When Is It an Optimal Product Introduction Strategy?," Management Science, INFORMS, vol. 61(10), pages 2487-2494, October.
    7. Michael Braun & Wendy W. Moe, 2013. "Online Display Advertising: Modeling the Effects of Multiple Creatives and Individual Impression Histories," Marketing Science, INFORMS, vol. 32(5), pages 753-767, September.
    8. Ravi Bapna & Akhmed Umyarov, 2015. "Do Your Online Friends Make You Pay? A Randomized Field Experiment on Peer Influence in Online Social Networks," Management Science, INFORMS, vol. 61(8), pages 1902-1920, August.
    9. Zaiyan Wei & Mo Xiao & Rong Rong, 2021. "Network Size and Content Generation on Social Media Platforms," Production and Operations Management, Production and Operations Management Society, vol. 30(5), pages 1406-1426, May.
    10. Simon P. Anderson & André de Palma, 2013. "Shouting to Be Heard in Advertising," Management Science, INFORMS, vol. 59(7), pages 1545-1556, July.
    11. Samayita Guha & Subodha Kumar, 2018. "Emergence of Big Data Research in Operations Management, Information Systems, and Healthcare: Past Contributions and Future Roadmap," Production and Operations Management, Production and Operations Management Society, vol. 27(9), pages 1724-1735, September.
    12. Huaxiao Shen & Yanzhi Li & Jingjing Guan & Geoffrey K.F. Tso, 2021. "A Planning Approach to Revenue Management for Non‐Guaranteed Targeted Display Advertising," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1583-1602, June.
    13. Castillo, Marco & Petrie, Ragan & Wardell, Clarence, 2014. "Fundraising through online social networks: A field experiment on peer-to-peer solicitation," Journal of Public Economics, Elsevier, vol. 114(C), pages 29-35.
    14. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    15. Vijay Mahajan & Eitan Muller, 1986. "Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 89-106.
    16. Sinan Aral & Dylan Walker, 2011. "Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks," Management Science, INFORMS, vol. 57(9), pages 1623-1639, February.
    17. Ganesh Iyer & Zsolt Katona, 2016. "Competing for Attention in Social Communication Markets," Management Science, INFORMS, vol. 62(8), pages 2304-2320, August.
    18. Kostas Bimpikis & Asuman Ozdaglar & Ercan Yildiz, 2016. "Competitive Targeted Advertising Over Networks," Operations Research, INFORMS, vol. 64(3), pages 705-720, June.
    19. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    20. Xuhan Tian & Junmin (Jim) Shi & Xiangtong Qi, 2022. "Stochastic Sequential Allocations for Creative Crowdsourcing," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 697-714, February.
    21. Kumar, Subodha & Jacob, Varghese S. & Sriskandarajah, Chelliah, 2006. "Scheduling advertisements on a web page to maximize revenue," European Journal of Operational Research, Elsevier, vol. 173(3), pages 1067-1089, September.
    22. Vijay Mahajan & Eitan Muller, 1986. "Reply—Reflections on Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 110-111.
    23. Bill McEvily & Akbar Zaheer, 1999. "Bridging ties: a source of firm heterogeneity in competitive capabilities," Strategic Management Journal, Wiley Blackwell, vol. 20(12), pages 1133-1156, December.
    24. Radha Mookerjee & Subodha Kumar & Vijay S. Mookerjee, 2017. "Optimizing Performance-Based Internet Advertisement Campaigns," Operations Research, INFORMS, vol. 65(1), pages 38-54, February.
    25. Robert P. Rooderkerk & Nicole DeHoratius & Andrés Musalem, 2022. "The past, present, and future of retail analytics: Insights from a survey of academic research and interviews with practitioners," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3727-3748, October.
    26. K. Sridhar Moorthy & I. P. L. Png, 1992. "Market Segmentation, Cannibalization, and the Timing of Product Introductions," Management Science, INFORMS, vol. 38(3), pages 345-359, March.
    27. Tsan‐Ming Choi & Subodha Kumar & Xiaohang Yue & Hau‐Ling Chan, 2022. "Disruptive Technologies and Operations Management in the Industry 4.0 Era and Beyond," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 9-31, January.
    28. Rakesh R. Mallipeddi & Subodha Kumar & Chelliah Sriskandarajah & Yunxia Zhu, 2022. "A Framework for Analyzing Influencer Marketing in Social Networks: Selection and Scheduling of Influencers," Management Science, INFORMS, vol. 68(1), pages 75-104, January.
    29. Chao Liang & Metin Çakanyildirim & Suresh P. Sethi, 2018. "Can Strategic Customer Behavior Speed Up Product Innovation?," Production and Operations Management, Production and Operations Management Society, vol. 27(8), pages 1516-1533, August.
    30. Vahideh Manshadi & Sidhant Misra & Scott Rodilitz, 2020. "Diffusion in Random Networks: Impact of Degree Distribution," Operations Research, INFORMS, vol. 68(6), pages 1722-1741, November.
    31. Radha Mookerjee & Subodha Kumar & Vijay S. Mookerjee, 2017. "Optimizing Performance-Based Internet Advertisement Campaigns," Operations Research, INFORMS, vol. 65(1), pages 38-54, February.
    32. Ashwin Aravindakshan & Prasad A. Naik, 2015. "Understanding the Memory Effects in Pulsing Advertising," Operations Research, INFORMS, vol. 63(1), pages 35-47, February.
    33. Stephen, Andrew T. & Lehmann, Donald R., 2016. "How word-of-mouth transmission encouragement affects consumers' transmission decisions, receiver selection, and diffusion speed," International Journal of Research in Marketing, Elsevier, vol. 33(4), pages 755-766.
    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. Changseung Yoo & Eunae Yoo & Lu (Lucy) Yan & Alfonso Pedraza-Martinez, 2024. "Speak with One Voice? Examining Content Coordination and Social Media Engagement During Disasters," Information Systems Research, INFORMS, vol. 35(2), pages 551-569, June.
    2. Jaehwuen Jung & Ravi Bapna & Joseph M. Golden & Tianshu Sun, 2020. "Words Matter! Toward a Prosocial Call-to-Action for Online Referral: Evidence from Two Field Experiments," Information Systems Research, INFORMS, vol. 31(1), pages 16-36, March.
    3. Qingliang Wang & Fred Miao & Giri Kumar Tayi & En Xie, 2019. "What makes online content viral? The contingent effects of hub users versus non–hub users on social media platforms," Journal of the Academy of Marketing Science, Springer, vol. 47(6), pages 1005-1026, November.
    4. Miguel Godinho de Matos & Pedro Ferreira & Michael D. Smith & Rahul Telang, 2016. "Culling the Herd: Using Real-World Randomized Experiments to Measure Social Bias with Known Costly Goods," Management Science, INFORMS, vol. 62(9), pages 2563-2580, September.
    5. Tianyi Li & Xiaoquan (Michael) Zhang, 2024. "Development Trajectory of Blockchain Platforms: The Role of Multirole," Information Systems Research, INFORMS, vol. 35(3), pages 1296-1323, September.
    6. Park, Sang-June & Lee, Yeong-Ran & Borle, Sharad, 2018. "The shape of Word-of-Mouth response function," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 304-309.
    7. Jing Wang & Anocha Aribarg & Yves F. Atchadé, 2013. "Modeling Choice Interdependence in a Social Network," Marketing Science, INFORMS, vol. 32(6), pages 977-997, November.
    8. Yan Leng & Xiaowen Dong & Esteban Moro & Alex Pentland, 2024. "Long-Range Social Influence in Phone Communication Networks on Offline Adoption Decisions," Information Systems Research, INFORMS, vol. 35(1), pages 318-338, March.
    9. Johannes Loh, 2022. "Selection, Consumption, and New Music Exploration in an Online Social Network: A Dyadic Approach," CESifo Working Paper Series 10120, CESifo.
    10. Tianshu Sun & Siva Viswanathan & Elena Zheleva, 2021. "Creating Social Contagion Through Firm-Mediated Message Design: Evidence from a Randomized Field Experiment," Management Science, INFORMS, vol. 67(2), pages 808-827, February.
    11. Bo Li & Subodha Kumar, 2022. "Managing Software‐as‐a‐Service: Pricing and operations," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2588-2608, June.
    12. Landsman, Vardit & Nitzan, Irit, 2020. "Cross-decision social effects in product adoption and defection decisions," International Journal of Research in Marketing, Elsevier, vol. 37(2), pages 213-235.
    13. Navdeep Sahni, 2015. "Effect of temporal spacing between advertising exposures: Evidence from online field experiments," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 203-247, September.
    14. Gaurav Sabnis & Rajdeep Grewal, 2015. "Cable News Wars on the Internet: Competition and User-Generated Content," Information Systems Research, INFORMS, vol. 26(2), pages 301-319, June.
    15. Yuichiro Kamada & Aniko Öry, 2020. "Contracting with Word-of-Mouth Management," Management Science, INFORMS, vol. 66(11), pages 5094-5107, November.
    16. Haris Krijestorac & Rajiv Garg & Vijay Mahajan, 2020. "Cross-Platform Spillover Effects in Consumption of Viral Content: A Quasi-Experimental Analysis Using Synthetic Controls," Information Systems Research, INFORMS, vol. 31(2), pages 449-472, June.
    17. Subodha Kumar & Xiaowei Mei & Liangfei Qiu & Lai Wei, 2020. "Watching Ads for Free Mobile Data: A Game-Theoretic Analysis of Sponsored Data with Reward Task," Working Papers 20-08, NET Institute.
    18. Sarah Gelper & Ralf van der Lans & Gerrit van Bruggen, 2021. "Competition for Attention in Online Social Networks: Implications for Seeding Strategies," Management Science, INFORMS, vol. 67(2), pages 1026-1047, February.
    19. Luzon, Yossi & Pinchover, Rotem & Khmelnitsky, Eugene, 2022. "Dynamic budget allocation for social media advertising campaigns: optimization and learning," European Journal of Operational Research, Elsevier, vol. 299(1), pages 223-234.
    20. Huang, Jian & Leng, Mingming & Liang, Liping, 2012. "Recent developments in dynamic advertising research," European Journal of Operational Research, Elsevier, vol. 220(3), pages 591-609.

    More about this item

    Statistics

    Access and download statistics

    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:bla:popmgt:v:32:y:2023:i:12:p:4005-4020. 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: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1937-5956 .

    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.