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Dynamic budget allocation for social media advertising campaigns: optimization and learning

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  • Luzon, Yossi
  • Pinchover, Rotem
  • Khmelnitsky, Eugene

Abstract

This paper suggests a method for optimizing a dynamic budget allocation policy for an advertising campaign posted through a social network (e.g., Facebook, Instagram). The method, which considers unique features of social network marketing, yields an optimal targeted budget allocation policy over time for a single ad campaign and minimizes the campaign's length, given a specific budget and a desired level of exposure of each marketing segment. The model incorporates a general ‘effectiveness function’ that determines the relationship between the value of an advertising bid at a given time and the number of newly exposed users at that time. We develop closed-form solutions for dynamic budget allocation for several forms of the effectiveness function. We apply the approach to data obtained from a real-life ad campaign and show how a curve fitting regression procedure can estimate the shape and the parameters of the effectiveness function. Numerical simulations show the extent to which the optimal advertising policy is sensitive to the problem parameters.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:299:y:2022:i:1:p:223-234
    DOI: 10.1016/j.ejor.2021.08.019
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    References listed on IDEAS

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    1. Prasad A. Naik & Murali K. Mantrala & Alan G. Sawyer, 1998. "Planning Media Schedules in the Presence of Dynamic Advertising Quality," Marketing Science, INFORMS, vol. 17(3), pages 214-235.
    2. A. Prasad & S. P. Sethi, 2004. "Competitive Advertising Under Uncertainty: A Stochastic Differential Game Approach," Journal of Optimization Theory and Applications, Springer, vol. 123(1), pages 163-185, October.
    3. Fred M. Feinberg, 2001. "On Continuous-Time Optimal Advertising Under S-Shaped Response," Management Science, INFORMS, vol. 47(11), pages 1476-1487, November.
    4. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    5. Vijay Mahajan & Eitan Muller, 1986. "Advertising Pulsing Policies for Generating Awareness for New Products," Marketing Science, INFORMS, vol. 5(2), pages 89-106.
    6. 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.
    7. 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.
    8. Jianan Wu & Victor J. Cook & Edward C. Strong, 2005. "A Two-Stage Model of the Promotional Performance of Pure Online Firms," Information Systems Research, INFORMS, vol. 16(4), pages 334-351, December.
    9. M. L. Vidale & H. B. Wolfe, 1957. "An Operations-Research Study of Sales Response to Advertising," Operations Research, INFORMS, vol. 5(3), pages 370-381, June.
    10. Du, Rong & Hu, Qiying & Ai, Shizhong, 2007. "Stochastic optimal budget decision for advertising considering uncertain sales responses," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1042-1054, December.
    11. Ballings, Michel & Van den Poel, Dirk, 2015. "CRM in social media: Predicting increases in Facebook usage frequency," European Journal of Operational Research, Elsevier, vol. 244(1), pages 248-260.
    12. Mokhtar S. Bazaraa, 1975. "An efficient cyclic coordinate method for optimizing penalty functions," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 22(2), pages 399-404, June.
    13. Gustav Feichtinger & Richard F. Hartl & Suresh P. Sethi, 1994. "Dynamic Optimal Control Models in Advertising: Recent Developments," Management Science, INFORMS, vol. 40(2), pages 195-226, February.
    14. Jørgensen, Steffen & Zaccour, Georges, 2014. "A survey of game-theoretic models of cooperative advertising," European Journal of Operational Research, Elsevier, vol. 237(1), pages 1-14.
    15. Johannes Haupt & Stefan Lessmann, 2020. "Targeting customers under response-dependent costs," Papers 2003.06271, arXiv.org, revised Aug 2021.
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