Abstract: The present invention relates to a system and method for customer segment analysis. The system receives customer transaction data for the generation of segments, including point of sales data and customer identification information. Errors in the data may be resolved. Then, individual customers may be segmented by statistically relevant groups. The segmentation of consumers may be accomplished by comparing data of known customers to known segments. Unknown customers, new customers and point of sales data which is missing customer data may also be segmented via statistical similarity to known segments. Using the customer segments, segment wide point of sale data may be generated. This data may then be aggregated by consumer groups. Consumer groups may include by household or other communal purchasing entity. The aggregated segment data may be validated and transformed for outputting to the optimization system. The price optimization system may the use the segment data for generation of preferred prices.

Abstract: An apparatus for providing relative optimized pricing for markdown items is provided. A financial engine for determining revenue for determining sales costs is provided. An optimization engine receiving input from the financial engine and uses the determined sales costs to provide relative optimized pricing for markdown items and provides pricing and a promotion calendar for non-markdown items.

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: 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: 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 system and method for tuning markdown plans is provided. Such a system and method may include configuring initial rule set. Initial Demand models are generated. A first optimization for inventory pricing may be received from the price optimization system. The first optimization uses the initial demand models and cost data. A markdown plan is generated by applying the initial rule set to the first optimization. The plan is implemented. Updated data may be received which mandates a re-optimization of the plan. Demand models are refreshed using the updated data. Initial rule set is updated by cross referencing plan history with the initial rule set and subtracting rule events that have previously occurred. A second optimization is received which uses the refreshed demand models and cost data. Then, the markdown plan is re-optimized by applying the updated rule set to the second optimization. The re-optimized markdown plan is reported, approved and implemented.

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: An apparatus for providing relative optimized pricing for markdown items is provided. A financial engine for determining revenue for determining sales costs is provided. An optimization engine receiving input from the financial engine and uses the determined sales costs to provide relative optimized pricing for markdown items and provides pricing and a promotion calendar for non-markdown items.

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 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: 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: A computer implemented method and system for providing price updates is provided. Data is received by a system. The received data is filtered by the system to identify triggers in the received data. Actions related to identified triggers are performed by the system. Business rule compliance is performed according to a business rule hierarchy. Updated prices are provided.

Abstract: A computer implemented method and system for providing price updates is provided. Data is received by a system. The received data is filtered by the system to identify triggers in the received data. Actions related to identified triggers are performed by the system. Business rule compliance is performed according to a business rule hierarchy. Updated prices are provided.