Google AdWords has thousands of advertisers participating in auctions to show their advertisements. Google's business model has two goals: first, provide relevant information to users and second, provide advertising opportunities to advertisers to achieve their business needs. To better serve these two parties, it is important to find relevant information for users and at the same time assist advertisers in advertising more efficiently and effectively. In this paper, we try to tackle this problem of better connecting users and advertisers from a customer relationship management point of view. More specifically, we try to retain more advertisers in AdWords by identifying and helping advertisers that are not successful in using Google AdWords. In this work, we first propose a new definition of advertiser churn for AdWords advertisers; second we present a method to carefully select a homogeneous group of advertisers to use in understanding and predicting advertiser churn; and third we build a model to predict advertiser churn using machine learning algorithms.