Empirical analysis of the impact of product diversity on long-term performance of recommender systems

Sung Hyuk Park, Sang Pil Han

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

3 Scopus citations

Abstract

This study explains how the product diversity affects long-term performance of recommendation systems. We examine how the number of product categories offered to customers is related to customer churn incidence. We collect a large scale panel data consisting of product category, revenues and customer churn information from a large offline retailer. We find that as the number of product categories recommended increases, the likelihood that customers churn strikingly decreases after controlling for the number of individual products being recommended. Our results suggest that companies can achieve better outcomes in their recommendation systems by explicitly incorporating the diversity of products being offered to their customers. Further, simulation results show that our proposed diversity-based recommendation strategy can save the company approximately $26 million per year (7.5% of the company's annual revenue) by preventing customer churn.

Original languageEnglish (US)
Title of host publicationICEC 2012 - 14th Annual International Conference on Electronic Commerce
Pages280-281
Number of pages2
DOIs
StatePublished - 2012
Externally publishedYes
Event14th Annual International Conference on Electronic Commerce, ICEC 2012 - Singapore, Singapore
Duration: Aug 7 2012Aug 8 2012

Publication series

NameACM International Conference Proceeding Series

Other

Other14th Annual International Conference on Electronic Commerce, ICEC 2012
Country/TerritorySingapore
CitySingapore
Period8/7/128/8/12

Keywords

  • cross-selling
  • customer churn
  • product diversity
  • recommender system

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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