Real-Time Bidding by Proportional Control in Display Advertising

摘要

In real-time bidding (RTB), advertisers need to give a price for each ad request, but in the face of millions of ad requests per day, it is particularly important for advertisers to design an automatic bidding strategy. Linear bidding is the most popular bidding strategy in the industry. The model considers the value of every impression, but a static bidding model cannot adapt to a complex and changeable auction environment. Most previous works focused on dynamic bidding strategies with continuous feedback, but fine-grained optimization of each bid made the model more difficult to calculate, and there were certain errors in the model of advertising click-through rate prediction. This paper combines the advantages of the two models and proposes a dynamic bidding strategy based on the overall proportional control, which controls the advertiser's return on investment by controlling the number of low click-through rates and high-click-rate ads to a certain proportion. In addition, this model can realize the dynamic adjustment of the proportion through the increase or decrease of price. Finally, the effectiveness of the strategy is experimentally confirmed in real data sets.