An Interactive Online Audience Extension System

In online advertising market, advertisers aim to target the right audience through media channels such as display, mobile, video, or social with limited budget. Usually the advertiser can collect high valuable users from their existing customs, whose size however is usually small. Hence, it is very important for advertisers to reach more audiences who can potentially be turned into future customers. How to induce the preferable attributes from the seed audience and hence identify more similar users from billions of cookie-able users within the runtime of a few minutes is a challenge to data science techniques. This is an important problem and many researchers have proposed several solutions [1]-[6] In this paper, we propose an efficient approach which can return a set of Boolean rules that defines the extended audience by analyzing the seed audience. As an additional feature, the proposed system also provides an option for advertisers to participate in the decision making process which could potentially improve the user reachability as well as the campaign performance. The experiment results show the superior performance of the proposed system compared with other methods in terms of efficiency, user reachability, action rate, click through rate, etc.