Journal Article

Website Morphing

Liberali, Guilherme, Hauser, John R, Urban, Glen L, Braun, Michael

2009

Overview

Virtual advisors often increase sales for those customers who find such online advice to be convenient and helpful. However, other customers take a more active role in their purchase decisions and prefer more detailed data. In general, we expect that websites are more preferred and increase sales if their characteristics (e.g., more detailed data) match customers' cognitive styles (e.g., more analytic). \"Morphing\" involves automatically matching the basic \"look and feel\" of a website, not just the content, to cognitive styles. We infer cognitive styles from clickstream data with Bayesian updating. We then balance exploration (learning how morphing affects purchase probabilities) with exploitation (maximizing short-term sales) by solving a dynamic program (partially observable Markov decision process). The solution is made feasible in real time with expected Gittins indices. We apply the Bayesian updating and dynamic programming to an experimental BT Group (formerly British Telecom) website using data from 835 priming respondents. If we had perfect information on cognitive styles, the optimal \"morph\" assignments would increase purchase intentions by 21%. When cognitive styles are partially observable, dynamic programming does almost as well—purchase intentions can increase by almost 20%. If implemented system-wide, such increases represent approximately $80 million in additional revenue.

• Publisher: INFORMS,Institute for Operations Research and the Management Sciences
• Subject: Advisors / Analysis / automated marketing / Bayesian analysis / Bayesian method / Bayesian methods / Bayesian statistical decision theory / Bleeding time / Broadband transmission / Business management / clickstream analysis / Cognition / Cognitive style / cognitive styles / Consumer behaviour / Consumers / Customer services / Customers / Data / Design and construction / Dynamic programming / Exploitation / Factorial experiments / Fads / Inference / Interactive marketing / Internet / Internet marketing / Machine learning / Marketing / Markov analysis / Motivation / Perfect information / Priming / Profits / Psychological aspects / Purchase intention / Respondents / Sales / Software / Strategic planning / Telecommunications / User behavior / Web site design / Web sites / website design / Websites