Abstract: The present invention relates to a system and method for efficiently identifying the sales opportunities in a business-to-business market environment. It provides a computer-implemented predictive sales intelligence system and method for identifying sales opportunities. The present invention is a computer implemented system and method for efficiently identifying reliable purchase pattern profiles through scientific analysis of customer data. It includes a system and method for calculating a customer's purchase profile, clustering customers based on similarity of their purchase profile, and efficiently providing a reliable set of opportunities including lost sales (retention) and cross-selling (wallet share expansion) opportunities. It uses this reliable estimate of sales opportunities to retain and expand wallet share for customers.

Abstract: To determine pricing recommendations for goods and service products in a business-to-business environment, a set of transaction data corresponding to a set of products are processed to generate a set of pricing recommendations optimized according to an objective. Furthermore, a set of product segments may be determined, transaction data may be associated with one or more of the product segments and a demand model and associated price elasticity may be formulated for one or more of the product segments based upon the transaction data associated with the segment. Using these formulated price elasticities, pricing recommendations for each product may be determined for each of a set of customers. Using an optimization process, price elasticities are used to determine price dependent entity goals for any combination of products, customers and sets of prices, using a mathematical objective function.