Abstract: The present invention relates to a system and method for analyzing product roles. The system receives a listing of products for classification into roles. The system receives volume data for each item, as well as demand coefficient. Elasticity of the products may be determined from the demand coefficients. Product volumes and elasticities may then be compared against one another by graphing the product by its volume versus elasticity. From this comparison the products may be classified into one or more roles. These roles include image items, niche products, assortment completers, and profit drivers. The assortment completer role is populated with products which have high relative elasticity and low relative volume. Niche product role is populated with products which have low relative elasticity and low relative volume. The image item role is populated with products which have high relative elasticity and high relative volume.

Abstract: A method for creating a sales model for a plurality of products is provided. Generally a plurality demand groups are created, where each demand group is a set of at least one product and wherein at least one of the demand groups is a set of at least two products. A sales model is created for each demand group. A market share model is created for each product in each demand group. In addition, an econometric engine for modeling sales as a function of price is provided. An imputed variable generator and a coefficient estimator coupled to the imputed variable generator form the econometric engine, where imputed variables generated by the variable generator are used by the coefficient estimator to create a sales model.

Abstract: A method for computing a preferred set of prices for products in a subset of a plurality of products is provided. Generally, initial prices for a plurality of products are stored. A subset of products of the plurality of products is designated, where the number of products in the subset of products is less than the number of products in the plurality of products. A demand model is created based on Bayesian modeling. Prices for the products in the subset of products are optimized, while maintaining the initial prices of products of the plurality of products that are not in the subset of products, wherein the optimization uses a grid method to determine the optimized prices.

Abstract: The present invention relates to a system and method for analyzing product roles. The system receives a listing of products for classification into roles. The system receives volume data for each item, as well as demand coefficient. Elasticity of the products may be determined from the demand coefficients. Product volumes and elasticities may then be compared against one another by graphing the product by its volume versus elasticity. From this comparison the products may be classified into one or more roles. These roles include image items, niche products, assortment completers, and profit drivers. The assortment completer role is populated with products which have high relative elasticity and low relative volume. Niche product role is populated with products which have low relative elasticity and low relative volume. The image item role is populated with products which have high relative elasticity and high relative volume.

Abstract: A method for computing a preferred set of prices for products in a subset of a plurality of products is provided. Generally, initial prices for a plurality of products are stored. A subset of products of the plurality of products is designated, where the number of products in the subset of products is less than the number of products in the plurality of products. Prices for the products in the subset of products are optimized, while maintaining the initial prices of products of the plurality of products that are not in the subset of products.

Abstract: A preferred set of prices for a plurality of products, generally demand coefficients is provided. Cost data including activity-based costs is also received. A preferred set of prices that will provide a local optimum for the preferred set of prices which maximizes profit is then determined. In one embodiment, a sales model and a cost model are created. A plurality of rules is specified. The preferred set of prices is then determined based on the sales model, the cost model, and the plurality of rules.

Abstract: Methods and apparatus for creating a promotional event calendar are provided. A sales model and a cost model are created The value of offers and promotional events using the sales model and cost model is determined. Combinations of offers and promotional events based on determined value are selected to create a promotion event calendar subject to the conditions from at least one store. The apparatus includes an econometric engine for modeling sales as a function of price to create a sales model, a financial model engine for modeling costs to create a cost model, a promotional engine coupled to the econometric engine, and financial model engine to receive input from the econometric engine and financial model engine. The promotional engine analyzes a plurality of offers and a plurality of promotional events to optimally match offers with promotional events to create a promotional event calendar.

Abstract: A method for modeling cost is provided. Sales data is received. Cost data is also received. Cost per unit of product is estimated from the sales data and the cost data. In addition, an apparatus for modeling costs, useful in association with an optimization engine, is provided. Generally, an econometric engine for receiving sales data, cleaning the data and generating imputed variables is combined with a financial engine for receiving imputed variables from the econometric engine, receiving cost data, generating a cost model, and outputting the cost model to the optimization engine.

Abstract: A price optimization system computes a preferred set of prices for a plurality of products. The optimization system stores a plurality of rules. The system may also prioritize the plurality of rules, and further relax lower priority rules to allow higher priority rules to become feasible. The feasible set of rules may then be utilized to generate the preferred set of prices.

Abstract: A method for determining a preferred set of prices for a plurality of products is provided. Generally, a sales model is created. A cost model is also created. A preferred set of prices for the plurality of products based on the sales model and cost model is then generated. An apparatus for computing a preferred set of prices for a plurality of products is provided. An econometric engine for modeling sales as a function of price to create a sales model is provided. A financial model engine for modeling costs to create a cost model is provided. An optimization engine is coupled to the econometric engine and financial model engine to receive input from the econometric engine and financial model engine, wherein the optimization engine generates the preferred set of prices.

Abstract: A method for forming a plurality of stores into a plurality of clusters is provided. Store specific information is collected. Optimized combinations for each individual store are provided based on the store specific information. Clusters are created based on the closeness of the optimal combinations.

Abstract: A preferred set of prices for a plurality of products, generally demand coefficients is provided. Cost data including activity-based costs is also received. A preferred set of prices that will provide a local optimum for the preferred set of prices which maximizes profit is then determined. In one embodiment, a sales model and a cost model are created. A plurality of rules is specified. The preferred set of prices is then determined based on the sales model, the cost model, and the plurality of rules.

Abstract: A preferred set of prices for a plurality of products, generally demand coefficients is provided. Cost data including activity-based costs is also received. A preferred set of prices that will provided a local optimum for the preferred set of prices which maximizes profit is then determined. In one embodiment, a sales model and a cost model are created. A plurality of rules is specified. The preferred set of prices is then determined based on the sales model, the cost model, and the plurality of rules.

Abstract: An apparatus is provided for determining optimum prices of products for sale. The apparatus includes a scenario/results processor through which a user prescribes an optimization scenario, and through which optimum prices are presented to the user. The optimum prices are determined by execution of the optimization scenario, where the optimum prices are determined based upon estimated product demand and calculated activity based costs. The scenario/results processor has an input/output processor and a scenario controller. The input/output processor acquires data corresponding to the optimization scenario from the user, and distributes optimization results to the user. The scenario controller is coupled to the input/output processor. The scenario controller controls acquisition of the data and the distribution of the optimization results in accordance with a price optimization procedure. The price optimization procedure enables the user to selectively prescribe the subset of the products for sale.

Abstract: An interface that enables a user to determine optimum prices of products for sale. The interface includes a scenario/results processor through which the user prescribes an optimization scenario, and through which optimum prices are presented to the user. The optimum prices are determined by execution of the optimization scenario, where the optimum prices are determined based upon estimated product demand and calculated activity based costs. The scenario/results processor has an input/output processor and a scenario controller. The input/output processor acquires data corresponding to the optimization scenario from the user, and distributes optimization results to the user. The scenario controller is coupled to the input/output processor. The scenario controller controls acquisition of the data and the distribution of the optimization results in accordance with a price optimization procedure.

Abstract: A method for optimizing the prices of products for sale. The method includes utilizing a computer-based scenario/results processor within an optimization server to present a sequence of data entry templates to a user, whereby the user specifies an optimization scenario, and whereby the user is enabled to prescribed and prioritize rules for the optimization scenario; within the optimization server, optimizing the prices according to market demand for the products and demand chain costs for the products; and generating a plurality of optimization results templates and providing these templates to the user, wherein the optimum prices are presented. The optimizing includes estimating the market demand and calculating the demand chain costs for the products; selectively limiting the number of prices that are optimized by said optimizing; and, up to a limit, progressively relaxing lower priority rules that contribute to a conflict in order to render the optimizing feasible.

Abstract: An apparatus is provided for an interface enabling a user to determine optimum prices of products for sale. The interface includes a scenario/results processor that enables the user to prescribe an optimization scenario, and that presents the optimum prices to the user. The optimum prices are determined by execution of the optimization scenario, where the optimum prices are determined based upon estimated product demand and calculated activity based costs. The scenario/results processor has an input/output processor and a scenario controller. The input/output processor acquires data corresponding to the optimization scenario from the user, and distributes optimization results to the user, where the data includes activity based cost data. The scenario controller is coupled to the input/output processor. The scenario controller controls acquisition of the data and the distribution of the optimization results in accordance with a price optimization procedure.

Abstract: A method for updating a master product attribute catalog database for consumer response modeling is provided. Data is received from at least one source of product data. A data integrity check is preformed on the received data. A reconciliation is performed between the received data and the master product attribute catalog. The reconciled received data is placed in a master product attribute catalog.

Abstract: Apparatus and method for determining an optimum promotion plan for merchandising of products for sale. A scenario/results processor enables a user to prescribe an optimization scenario, and presents the optimum promotion plan to the user, where the optimum promotion plan is determined by execution of the optimization scenario. The demand engine models relationships between potential prices of the products and market demand for the products, where the potential prices correspond to potential promotion events and potential supplier offers. The activity based cost engine estimates demand chain costs for the products based upon the market demand. The promotion optimization engine employs the market demand and the demand chain costs to determine the optimum promotion plan, where the optimum promotion plan maximizes a merchandising performance figure of merit according to the optimization scenario, and where the optimum promotion plan comprises a subset of the promotion events and potential supplier offers.

Abstract: An interface that enables a user to determine optimum prices of products for sale. The interface includes a scenario/results processor through which the user prescribes an optimization scenario, and through which optimum prices are presented to the user. The optimum prices are determined by execution of the optimization scenario, where the optimum prices are determined based upon estimated product demand and calculated activity based costs. The scenario/results processor has an input/output processor and a scenario controller. The input/output processor acquires data corresponding to the optimization scenario from the user, and distributes optimization results to the user. The scenario controller is coupled to the input/output processor. The scenario controller controls acquisition of the data and the distribution of the optimization results in accordance with a price optimization procedure.