TY - GEN
T1 - Empirical analysis of the impact of product diversity on long-term performance of recommender systems
AU - Park, Sung-Hyuk
AU - Han, Sang Pil
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to <a href="mailto:[email protected]">[email protected]</a>.
PY - 2012
Y1 - 2012
N2 - 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. © 2012 Authors.
AB - 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. © 2012 Authors.
KW - cross-selling
KW - customer churn
KW - product diversity
KW - recommender system
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84866051920&origin=recordpage
U2 - 10.1145/2346536.2346592
DO - 10.1145/2346536.2346592
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781450311977
T3 - ACM International Conference Proceeding Series
SP - 280
EP - 281
BT - ICEC 2012 - 14th Annual International Conference on Electronic Commerce
T2 - 14th Annual International Conference on Electronic Commerce, ICEC 2012
Y2 - 7 August 2012 through 8 August 2012
ER -