A Spectral Approach to Collaborative Ranking

Abstract

Knowing your customers and their needs is mandatory when conducting business. In an e-commerce environment, where one often knows much less about individual customers than in a face-to-face business, questionnaires - besides historical transaction data and basic information like names and ge ographic location - are popular means to get to know cus tomers. Here we report on an approach to analyze prefer ence data that consumers provide in stated choice experi ments which can be conducted on a company’s web site. Nat urally, the information one captures with web based question naires tends to be sparse and noisy. Nevertheless, our results show that if one collects data from enough consumers one can learn about different segments and their needs. The results are obtained with a spectral collaborative ranking algorithm that can be applied to stated choice data, especially, choice based conjoint analysis data.