Prediction of Advertiser Churn for Google AdWords
Venue
JSM Proceedings, American Statistical Association (2010) (to appear)
Publication Year
2010
Authors
Sangho Yoon, Jim Koehler, Adam Ghobarah
BibTeX
Abstract
Google AdWords has thousands of advertisers participating in auctions to show their
advertisements. Google's business model has two goals: firrst, 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.
