Optimizing Budget Constrained Spend in Search Advertising
Venue
Sixth ACM International Conference on Web Search and Data Mining, WSDM 2013, ACM, pp. 697-706
Publication Year
2013
Authors
Chinmay Karande, Aranyak Mehta, Ramakrishnan Srikant
BibTeX
Abstract
Search engine ad auctions typically have a significant fraction of advertisers who
are budget constrained, i.e., if allowed to participate in every auction that they
bid on, they would spend more than their budget. This yields an important problem:
selecting the ad auctions in which these advertisers participate, in order to
optimize different system objectives such as the return on investment for
advertisers, and the quality of ads shown to users. We present a system and
algorithms for optimizing such budget constrained spend. The system is designed be
deployed in a large search engine, with hundreds of thousands of advertisers,
millions of searches per hour, and with the query stream being only partially
predictable. We have validated the system design by implementing it in the Google
ads serving system and running experiments on live traffic. We have also compared
our algorithm to previous work that casts this problem as a large linear
programming problem limited to popular queries, and show that our algorithms yield
substantially better results.
