A Study of Analytics Driven Solutions for Customer Targeting and Sales Force Allocation in Data Mining

OnTARGET and MAP are examples of analytics-based solutions that were designed from the outset to address specific business challenges in the broad area of sales force productivity. Although they address different underlying issues, these solutions implement a common approach that is generally applicable to a broad class of operational challenges. Both solutions rely on rigorously defined data models that integrate all relevant data into a common database. Choices of the data to be included in the data model are driven both by end-user requirements as well as the need for relevant inputs to analytical models. Both business problems have a natural mapping to applications of predictive modeling: predicting the probability to purchase in the case of OnTARGET, and estimating the realistic revenue opportunity in the case of MAP. Delivering the underlying data and the analytic insights directly to frontline decision makers (sales representatives for OnTARGET and sales executives for MAP) is crucial to driving business impact, and a significant effort has been invested in developing efficient web-based tools with the necessary supporting infrastructure. In this paper we discuss several aspects and analyze them.