A Spectral Approach to Collaborative Ranking

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 geographic location are popular means to get to know customers. Here we report on an approach to analyze preference data that consumers provide in stated choice experiments which can be conducted on a company’s web site. Naturally, the information one captures with web based questionnaires 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.