Abstract: A method and process of target pricing a value, such as a bid, or other price which includes the steps of pricing the value using stored list prices in a product model, costing the value using stored costs in the product model, calculating. an equivalent competitor net price for the value using a competitor net price model, calculating. the probability of winning the value as a function of price using parameters from a market response model, and calculating a target price for the value. The preferred target price maximizes expected contribution using an optimization model that determines competitive response to any potential value, or bid. The method and process further preferably include the steps of calculating one or more benefits of target pricing in comparison to a pre-existing pricing approach, determining a target range for the target price to be within, and determining strategic objects that constrain the target price of the value or bid.

Abstract: The system for implementing Customized Pricing includes, in a preferred embodiment, four modules operable within a server or workstation environment, including a CP Statistics Calibration module, a CP Pricer, a CP Strategy Tool, and a CP Performance Monitor. The CP Statistics Calibration module examines the historical pricing proposals and their corresponding subsequent fulfillment data (e.g., what products were delivered at the offered prices). The historical pricing proposals are generated from or stored within databases coupled to the system. The CP Statistics Calibration module generates the market response parameters that are key to quantifying predicted future buyer behavior. Customer response behavior to various offers for products is preferably modeled using a Zero Inflated Regression Model approach. The CP Pricer software module is operative to construct a pricing proposal using the market response parameters generated by the CP Statistics Calibration module.

Abstract: A method for pricing products (e.g., goods or services) offered to a customer comprises the steps of modeling customer behavior using a Zero Inflated Regression Model approach, using records of buyer responses to past offers, to yield an expected demand for the goods or services as a function of price; calculating the seller performance goal as a function of price using the expected customer demand; and selecting the price proposal to maximize the seller performance goal. The Zero Inflated Model is used to calculate the likelihood that the customer may have a non-zero demand for the product or service as a function of price. The Non-Negative Regression Model is used to calculate the expected demand for the product or service given that the customer may have non-zero demand.

Abstract: The present invention provides a configurable pricing system that allows users to define or modify data used to analyze, evaluate, improve, and design pricing changes according to the user's need. A Graphical user interface or some other type of user interface allows the user to access and review various data to be used during pricing optimization. The user may then modify this data as needed to improve the pricing evaluation, such as defining sales or pricing trends, or relationships between the product of interest and other competing items. The user interface may further display changes in pricing and the effects of the pricing changes, as caused by the user's changes. The interface may also allow the user to modify the mathematical model to be used during price optimization, as well as define variables, constraints, and boundaries to be considered during the price optimization.

Abstract: A business process and computer system known as the “Target Pricing System” (TPS) that generates an optimum bid or value for a competitively bid good or service. The system is resident on one or more host processors in connection with one or more data stores, and includes a product model that defines list values for the bid using stored price data and costs the values using stored cost data, a competitor net price model that calculates an equivalent competitor net price for the value, and a market response model that calculates the probability of winning with the value as a function of price. The system further preferably includes an optimization model that computes the target price of an optimal value that maximizes expected contribution for the bid or value. The system alternately further includes a benefits model for calculating the benefits of using target pricing over a pre-existing approach, and strategic objects which each affect the target price.