Real time bid optimization with smooth budget delivery in online advertising

Abstract

Today, billions of display ad impressions are purchased on a daily basis through a public auction hosted by real time bidding (RTB) exchanges. A decision has to be made for advertisers to submit a bid for each selected RTB ad request in milliseconds. Restricted by the budget, the goal is to buy a set of ad impressions to reach as many targeted users as possible. A desired action (conversion), advertiser specific, includes purchasing a product, filling out a form, signing up for emails, etc. In addition, advertisers typically prefer to spend their budget smoothly over the time in order to reach a wider range of audience accessible throughout a day and have a sustainable impact. However, since the conversions occur rarely and the occurrence feedback is normally delayed, it is very challenging to achieve both budget and performance goals at the same time. In this paper, we present an online approach to the smooth budget delivery while optimizing for the conversion performance. Our algorithm tries to select high quality impressions and adjust the bid price based on the prior performance distribution in an adaptive manner by distributing the budget optimally across time. Our experimental results from real advertising campaigns demonstrate the effectiveness of our proposed approach.

Optimal real-time bidding for display advertising

“…As a new advertising paradigm, other problems in RTB have also been studied. In [25] the authors focus on the pacing problem, where the target is to smoothly deliver the campaign budget. From the SSP perspective, the reserve price setting in RTB ad auctions is studied in [36].…”

Bid Optimization by Multivariable Control in Display Advertising

“…In our case, we model the bidding environment with respect to the cost and CPC as shown in Eq. (16), where X is a 2 × 2 matrix and b is a 2 × 1 matrix. After we obtain the expected ∆cost and ∆CPC from the feedback, we could adjust p and q by solving the equation in Eq.…”

Logistical modelling of managerial decisions in social and marketing business systems

“…Pérez-Gladish et al (2010) suggested linear logistical models in the field of advertising with the function of efficiency-maximization of a general amount of sales. Studies by K. C. Lee et al (2013) and C. Karande et al (2013) are focused on optimization of costs in the internet-advertising environment. Logistical models which ignore limitations on production capacities, possible efficiency of each separate type of advertising, amount of covering the target audience of potential consumers, minimal necessary volumes of using certain sources of advertising and a set of other factors have been suggested.…”