An expected win rate-based real-time bidding strategy for branding campaigns on display advertising

Wen Yueh Shih, Jiun Long Huang*

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

For branding campaigns, the demand-side platforms (DSPs) in real-time bidding (RTB) usually need to win as many impressions as possible to inform most audiences about the product messages under constraints on budgets, campaign lifetimes and budget spending plans. In this paper, we propose a novel bidding strategy by introducing the concept of expected win rate. With the proposed expected win rate-based bidding strategy, the DSP can dynamically adjust the expected win rate for each incoming bid request based on factors such as the predicted number of bid requests in the near future, the remaining budget and the remaining lifetime of the campaign. The experimental results show that the proposed bidding strategy has a lower cost per thousand impressions and cost per clicks than existing pacing model-based bidding strategies for branding campaigns with the same budgets and budget spending plans.

Original languageEnglish
Pages (from-to)1395-1430
Number of pages36
JournalKnowledge and Information Systems
Volume61
Issue number3
DOIs
StatePublished - Dec 2019

Keywords

  • Bid price
  • Bidding strategy
  • Expected win rate
  • Online advertisement
  • Real-time bidding

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