Paper Info
Title
An expected win rate-based real-time bidding strategy for branding campaigns on display advertising
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.
Year
DOI
Venue
2019
10.1007/s10115-019-01331-8
Knowledge and Information Systems
Keywords
Field
DocType
Real-time bidding, Online advertisement, Bid price, Expected win rate, Bidding strategy
Display advertising,Computer science,Operations research,Real-time bidding,Artificial intelligence,Cost per impression,Bidding,Machine learning,Bid price
Journal
Volume
Issue
ISSN
61
3
0219-3116
Citations 
PageRank 
References 
0
0.34
36
Authors
2
Name
Order
Citations
PageRank
Wen-Yueh Shih111.72
Jiun-Long Huang259247.09