Paper Info
Title
Measuring The Value Of Recommendation Links On Product Demand
Abstract
Recommending substitute products on focal products' pages on an e-commerce website can impact product sales in two ways. First, the visibility of a product as a recommendation on other products' pages may increase its exposure and result in a greater number of its page views. Second, visibility of substitute products on the product's page may cannibalize its own sales while resulting in greater exposure for the substitute products. The net impact of these opposing effects is unclear. We conduct a randomized experiment on a fashion apparel retailer's website to answer the following questions: (1) what is the causal value of recommendation links from a product to its recommended products in terms of the additional sales for both the product and its recommended products, and (2) how does the value of a product's recommendation links vary based on its network characteristics, such as its PageRank and the strength of its relationship with neighboring products? We find that as a result of a recommendation, on average, (1) the daily number of product page views increased by 7.5%, and (2) conditional on a product's page view, its sales decreased by 1.9%, and the sales of its recommended substitutes increased by 9%. On average, recommendation links of a product result in an 11% gain in total sales of the product and its recommended substitutes. However, these gains are not evenly distributed among all products. We find that although the number of page views for a product is positively affected by the number and strength of its incoming links, its sales (its recommended products' sales) conditional on its page view are negatively (positively) affected by the strength of its outgoing links. We conduct policy simulations to highlight how retailers and producers can apply this knowledge by engineering the recommendation network through sponsored links.
Year
DOI
Venue
2019
10.1287/isre.2018.0833
INFORMATION SYSTEMS RESEARCH
Keywords
DocType
Volume
product recommendation network, product recommendations, digital advertising, electronic commerce, randomized field experiment, sponsored product advertising, average treatment effect
Journal
30
Issue
ISSN
Citations 
3
1047-7047
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Anuj Kumar11911.09
Kartik Hosanagar260542.44