Interaction Mining - Knowledge Discovery
Retailers already collect and analyze sales transaction data to better understand their stock position, inventory turns, store promotions, and customer promotions. In the future retailers are also likely to collect data about product returns, customer inquiries, price checks, customer complaints, customers that visit a store but do not buy anything, and a customers browsing behavior in the store. In fact, electronic storefronts can already capture much of this data. Customer interaction data is sales data plus all other data related to a customers total relationships with a retailer. Customer Interaction Mining is the analysis of customer interaction data to garner insight about a retailers customers.
Customer Interaction Mining research at the HITC attempts to answer the following questions:
Two research problems are created by customer interaction data:
Technologies being investigated at the HITC for Customer Interaction Mining are Bayesian Belief Networks, Case-Based Reasoning, Hidden Markov Models and the Minimum Description Length Principle