Anand V. Bodapati

About

Anand V. Bodapati is an Associate Professor of Marketing at UCLA Anderson School of Management. His research is at the intersection of consumer psychology, decision making, statistics, marketing, and computer science. His interests include the development of statistical models, methodologies, and decision support systems to address marketing problems related to value creation, value communication, customer acquisition, customer development, customer retention, and the assessment of customer response to marketing. Bodapati has worked on customer acquisition targeting, product optimization, consumer preference assessment, conjoint analysis, segmentation, advertising response, direct marketing, customer relationship management, Bayesian statistics, and experimental design. His domain-specific interests encompass advertising, retailing, direct marketing, digital marketing, and social marketing for health and public policy.

Research topics

• Advertising
• Business
• Computer Science
• Marketing
• Commerce
• Psychology

Selected publications

• Determining Influential Users in Internet Social Networks

  Journal of Marketing Research · 2010-07-12 · 646 citations

  article

  The success of Internet social networking sites depends on the number and activity levels of their user members. Although users typically have numerous connections to other site members (i.e., “friends”), only a fraction of those so-called friends may actually influence a member's site usage. Because the influence of potentially hundreds of friends needs to be evaluated for each user, inferring precisely who is influential—and, therefore, of managerial interest for advertising targeting and rete…

  PublisherDOI

• Recommendation Systems with Purchase Data

  Journal of Marketing Research · 2008-01-09 · 245 citations

  article1st authorCorresponding

  Abstract Many firms use decision tools called “automatic recommendation systems” that attempt to analyze a customer's purchase history and identify products the customer may buy if the firm were to bring these products to the customer's attention. Much of the research in the literature today attempts to recommend products that have a high probability of purchase (conditional on the customer's history). However, the author posits that the recommendation decision should be based not on purchase pr…

  PublisherDOI

• The interrelationships between brand and channel choice

  Marketing Letters · 2014-06-24 · 121 citations

  articleOpen access
  PublisherOA PDFDOI

• Determining Influential Users in Internet Social Networks

  SSRN Electronic Journal · 2009-01-01 · 117 citations

  articleOpen access
  PublisherDOI

• Retailer Marketing Communications in the Digital Age: Getting the Right Message to the Right Shopper at the Right Time

  Journal of Retailing · 2021 · 73 citations

  PublisherOA PDFDOI

Frequent coauthors

• Sachin Gupta

  SC Johnson (United States)

  9 shared

• Wagner A. Kamakura

  Rice University

  7 shared

• P. A. Naik

  University of Liverpool

  7 shared

• Aimée Drolet

  Anderson University - South Carolina

  7 shared

• Randolph E. Bucklin

  6 shared

• Michel Wedel

  6 shared

• Peter C. Verhoef

  5 shared

• Peter Lenk

  5 shared

Awards & honors

• American Marketing Association's Paul Green Award twice
• American Marketing Association's Lehmann Award
• finalist for the O'Dell Award for his work on recommendation…
• Paul Green 'Best Paper' Award (2008)
• O'Dell Award for Long Term Impact

Similar researchers at University of California, Los Angeles

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• Hal Hershfieldh-35
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