Abstract: A data warehouse system and application which analyzes historical sales and product data contained within a data warehouse to determine the best product prices across a set of products for a retailer. The application analyzes historical sales and product data contained in a database to determine an opportunity score for multiple products sold by a retailer, the opportunity score indicating potential benefit to said business from changing the pricing of a product; and analyzes historical sales data contained in the database to determine an ability to change score for each product, the ability to change score indicating potential risk of lost sales for the retailer from changing the pricing of a product. Results of the analyses are displayed in a scatter plot graph with the graph axes being the opportunity scores and ability to change scores, respectively.

Abstract: A data warehouse system and application which analyzes historical sales and product data contained within a data warehouse to determine the best product prices across a set of products for a retailer. The application analyzes historical sales and product data contained in a database to determine an opportunity score for multiple products sold by a retailer, the opportunity score indicating potential benefit to said business from changing the pricing of a product; and analyzes historical sales data contained in the database to determine an ability to change score for each product, the ability to change score indicating potential risk of lost sales for the retailer from changing the pricing of a product. Results of the analyses are displayed in a scatter plot graph with the graph axes being the opportunity scores and ability to change scores, respectively.

Abstract: A data warehouse system and application which analyzes historical sales and product data contained within a data warehouse to determine the best product prices across a set of products for a retailer. Historical demand data for products is grouped and mined using data mining techniques to identify products having opposing sales relationships, and determine how a reduction in the price or increase in sales for a specific product will impact the demand for other products sold by a retailer.

Abstract: A data warehouse system and application which analyzes historical sales and product data contained within a data warehouse to determine the best product prices across a set of products for a retailer. Historical demand data for products is grouped and mined using data mining techniques to identify products having affinity relationships, and determine how changes to the price and demand for a specific product will increase the demand for other products sold by a retailer.

Abstract: A data warehouse system and application which analyzes historical sales and product data contained within a data warehouse to determine the best product prices across a set of products for a retailer. The application automatically creates statistical models, determines product price elasticity, and identifies and estimates product cross-sell and substitution effects. It does all modeling and analysis directly on the data within a data warehouse system, without any data extraction or manual data preparation. Output from the analytic application can be used operationally to set new product prices, or the application can be utilized as a decision support tool to help retailers understand the influencers on their product sales and profitability.

Abstract: A data warehouse system and application which analyzes historical sales and product data contained within a data warehouse to determine the best product price for a retail product. The application automatically creates statistical models using relevant information in the database and determines price elasticity characteristics for the retail product indicating the probable change in sales volume of the product resulting from a change in the selling price for the product. Output from the application can be used operationally to set new product prices, or the application can be utilized as a decision support tool to help retailers understand the influencers on their product sales and profitability.