Inferring Market Structure from Customer Response to Competing and Complementary Products

We consider customer influences on market structure, arguing that market structure should explain the extent to which any given set of market offerings are substitutes or complements. We describe recent additions to the market structure analysis literature and identify promising directions for new research in market structure analysis. Impressive advances in data collection, statistical methodology and information technology provide unique opportunities for researchers to build market structure tools that can assist “real-time” marketing decision-making.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46981/1/11002_2004_Article_5088105.pd

THE DETECTION OF LUMINANCE PATTERNS IN THE LEFT AND RIGHT VISUAL FIELD.

THE DETECTION OF LUMINANCE PATTERNS IN THE LEFT AND RIGHT VISUAL FIELD

Predictive CRM In A B2B Context: Evaluating Cross-Selling Opportunities Based On Likely Response To The Offer

Abstract Most companies struggle with the issue of what products to offer their existing customers. An important CRM goal is offering customer what they are most likely to buy, not necessarily what they they ask for. The key is to offer customers what they are must likely to buy, given that an offer or recommendation is made. We describe the development of a B2B CRM system that provides tactical sales support through the use of sensor (GIS) and account management data. It deploys hierarchical Bayes models of purchase behavior that condition on sales interventions, and that incorporate customer covariates to account for heterogeneity. We compare our procedure to the company's current practices, and provide an contextual computing IT systems perspective