Budget optimization for online campaigns with positive carryover effects

Nikolay Archak, Vahab Mirrokni, S. Muthukrishnan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

While it is relatively easy to start an online advertising campaign, proper allocation of the marketing budget is far from trivial. A major challenge faced by the marketers attempting to optimize their campaigns is in the sheer number of variables involved, the many individual decisions they make in fixing or changing these variables, and the nontrivial short and long-term interplay among these variables and decisions. In this paper, we study interactions among individual advertising decisions using a Markov model of user behavior. We formulate the budget allocation task of an advertiser as a constrained optimal control problem for a Markov Decision Process (MDP). Using the theory of constrained MDPs, a simple LP algorithm yields the optimal solution. Our main result is that, under a reasonable assumption that online advertising has positive carryover effects on the propensity and the form of user interactions with the same advertiser in the future, there is a simple greedy algorithm for the budget allocation with the worst-case running time cubic in the number of model states (potential advertising keywords) and an efficient parallel implementation in a distributed computing framework like MapReduce. Using real-world anonymized datasets from sponsored search advertising campaigns of several advertisers, we evaluate performance of the proposed budget allocation algorithm, and show that the greedy algorithm performs well compared to the optimal LP solution on these datasets and that both show consistent 5-10% improvement in the expected revenue against the optimal baseline algorithm ignoring carryover effects.

Original languageEnglish (US)
Title of host publicationInternet and Network Economics - 8th International Workshop, WINE 2012, Proceedings
Pages86-99
Number of pages14
DOIs
StatePublished - Dec 26 2012
Event8th International Workshop on Internet and Network Economics, WINE 2012 - Liverpool, United Kingdom
Duration: Dec 10 2012Dec 12 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7695 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Workshop on Internet and Network Economics, WINE 2012
CountryUnited Kingdom
CityLiverpool
Period12/10/1212/12/12

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Budget optimization for online campaigns with positive carryover effects'. Together they form a unique fingerprint.

Cite this