Patent ID: 8386298

Claim:
A computer-implemented method to estimate a price for selling a product j in a commerce channel comprising the steps of: a) receiving, at a processor device, real market data including sales and price history data of a product j sold by multiple retailers over alternate sales channels t; b) generating, by said processor device, a competitive advantage parameter value based on said sales and price history data, said generating of the competitive advantage parameter value comprising: receiving at input nodes of a configured neural network, a data vector including the prices and customer preferences of a product j at different times, said configured neural network representing a dynamic procedure of competition in retailer market; propagating said data to one or more intermediate nodes of said configured neural network; implementing a function, at said intermediate nodes, for calculating a customer preference parameter value C ij t ; and implementing a back propagation computation of said neural network to obtain gradients for use in calculating said customer preference parameter value C ij 2 calculating the competitive advantage ψ ij k of customer segment i and product j in channel t according to: ψ ij t (k)=max {θ 1 max{0,p j s −p j t },θ 2 max{0,C ij t −C ij s }} where k denotes a time period, p j s (p j t ) denotes the price of product “j” in respective channel s(t), c ij t (c ij s ) denotes a calculated customer preference parameter value for respective channel t(s) of customer segment “i” while buying product “j”, and θ 1 , θ 2 are the weights of price and customer preference, respectively; c) computing, utilizing said competitive advantage parameter value, a simulated sales volume q ij t , for a channel t in a particular price setting, said simulated sales volume used in calculating an optimum price for a particular product to be marketed in one of said alternate sales channel.