The value of online customer reviews

Georgios Askalidis, Edward C. Malthouse

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

38 Scopus citations


We study the effect of the volume of consumer reviews on the purchase likelihood (conversion rate) of users browsing a product page. We propose using the exponential learning curve model to study how conversion rates change with the number of reviews. We call the difference in conversion rate between having no reviews and an infinite number the value of reviews. We find that, on average, the conversion rate of a product can increase by as much as 270% as it accumulates reviews, amongst the users that choose to display them. We also find diminishing marginal value as a product accumu- lates reviews, with the first five reviews driving the bulk of the aforementioned increase. To address the problem of si- multaneity of increase of reviews and conversion rate, we use customer sessions in which reviews were not displayed as a control for trends that would have happened regardless of the increase in the review volume. Using our framework, we further find that high priced items have a higher value for reviews than lower priced items. High priced items can see their conversion rate increase by as much as 380% as they accumulate reviews compared to 190% for low priced items.We infer that the existence of reviews provides valu- able signals to the customers, increasing their propensity to purchase. We also infer that users usually don't pay atten- tion to the entire set of reviews, especially if there are a lot of them, but instead they focus on the first few available. Our approach can be extended and applied in a variety of settings to gain further insights.

Original languageEnglish (US)
Title of host publicationRecSys 2016 - Proceedings of the 10th ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery, Inc
Number of pages4
ISBN (Electronic)9781450340359
StatePublished - Sep 7 2016
Event10th ACM Conference on Recommender Systems, RecSys 2016 - Boston, United States
Duration: Sep 15 2016Sep 19 2016

Publication series

NameRecSys 2016 - Proceedings of the 10th ACM Conference on Recommender Systems


Other10th ACM Conference on Recommender Systems, RecSys 2016
Country/TerritoryUnited States


  • Marketing
  • Online Reviews
  • Word of Mouth

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture
  • Computer Networks and Communications


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