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Optimal dynamic multi-keyword bidding policy of an advertiser in search-based advertising

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  • Savas Dayanik

    (Bilkent University)

  • Semih O. Sezer

    (Sabancı University)

Abstract

Sponsored search advertisement allows advertisers to target their messages to appropriate customer segments at low costs. While search engines are interested in auction mechanisms that boost their revenues, advertisers seek optimal bidding strategies to increase their net sale revenues for multiple keywords under strict daily budget constraints in an environment where keyword query arrivals, competitor bid amounts, and user purchases are random. We focus on the advertiser’s question and formulate her optimal intraday dynamic multi-keyword bidding problem as a continuous-time stochastic optimization problem. We solve the problem, characterize an optimal policy, and bring a numerical algorithm for implementation. We also illustrate our optimal bidding policy and its benefits over heuristic solutions on numerical examples.

Suggested Citation

  • Savas Dayanik & Semih O. Sezer, 2023. "Optimal dynamic multi-keyword bidding policy of an advertiser in search-based advertising," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 97(1), pages 25-56, February.
    • Handle: RePEc:spr:mathme:v:97:y:2023:i:1:d:10.1007_s00186-022-00803-y
    DOI: 10.1007/s00186-022-00803-y
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    References listed on IDEAS

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    1. Li, Baoku & Nan, Yafeng & Yao, Ruoxi, 2024. "The inverted U-shaped relationship between information entropy of keyword combinations and sales of digital products: Evidence from China Tmall," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).

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