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Publications
Publications
  • December 2019
  • Article
  • Journal of Marketing Research (JMR)

The Impact of Increasing Search Frictions on Online Shopping Behavior: Evidence from a Field Experiment

By: Donald Ngwe, Kris J. Ferreira and Thales Teixeira
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Abstract

Many online stores are designed such that shoppers can easily access any available discounted products. We propose that deliberately increasing search frictions by placing small obstacles to locating discounted items can improve online retailers’ margins and even increase conversion. We demonstrate using a simple theoretical framework that inducing consumers to inspect higher-priced items first may simultaneously increase the average price of items sold and the overall expected purchase probability by inducing consumers to search more products. We test and confirm these predictions in a series of field experiments conducted with a dominant online fashion and apparel retailer. Furthermore, using information in historical transaction data about each consumer, we demonstrate that price-sensitive shoppers are more likely to incur search costs to locate discounted items. Our results show that increasing search frictions can be used as a self-selecting price discrimination tool to match high discounts with price-sensitive consumers and full-priced offerings with price-insensitive consumers.

Keywords

Online Retailing; Friction; Effor; Search Costs; Price Discrimination; Marketing; Consumer Behavior; Strategy; Price; E-commerce; Retail Industry; Fashion Industry

Citation

Ngwe, Donald, Kris J. Ferreira, and Thales Teixeira. "The Impact of Increasing Search Frictions on Online Shopping Behavior: Evidence from a Field Experiment." Journal of Marketing Research (JMR) 56, no. 6 (December 2019): 944–959.
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About The Author

Kris Johnson Ferreira

Technology and Operations Management
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More from the Authors
  • Demand Learning and Pricing for Varying Assortments By: Kris Ferreira and Emily Mower
  • Market Segmentation Trees By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
  • Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
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