The Value of Online Customer Reviews

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 accumulates reviews, with the first five reviews driving the bulk of the aforementioned increase. To address the problem of simultaneity 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 valuable signals to the customers, increasing their propensity to purchase. We also infer that users usually don't pay attention 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.