Abstract: The embodiments described herein can provide systems and methods utilize competitive history data to provide improved pricing recommendations for sellers. This competitive history data can include a time series of one or more competitor's prices for a set of products. This use of competitive history data to provide improved pricing recommendations to sellers introduces significant non-convexity to the determination of pricing recommendations. Accordingly, the systems and methods described herein employ a variety of technical approaches to generating the price recommendations in light of this introduced complexity. Additionally, the systems and methods employ various techniques to providing these price recommendations even when competitive history data is limited. Specifically, by using the limited to competitive history data to generate constraints, where the constraints can then be used for additional price optimizations where competitive history data is unavailable.

Abstract: The embodiments described herein can provide systems and methods for optimizing prizes. Specifically, these systems and methods utilize competitive history data to provide improved pricing recommendations for sellers. This competitive history data can include a time series of one or more competitor's prices for a set of products. The systems and methods described herein can use this competitor price data with a corresponding time series of seller's data on their product prices and resulting demand to provide improved pricing recommendations to the seller. This use of competitive history data to provide improved pricing recommendations to sellers introduces significant complexity to the optimization of prices. Specifically, this use of competitive history data introduces significant non-convexity to the determination of pricing recommendations.

Abstract: Disclosed is a market-based software system that will help user-retailers manage price and inventories more effectively. The system will take advantage of available price and sales data to provide pricing recommendations that will achieve a retail user's objectives. The system will offer a solution that will allow for pricing improvement shortly after installation by utilizing data that is readily available. The system will recommend price changes that help a user achieve specified objectives such as contribution, sales volume, desired margins, and the like. The system can also collect and process price and sales data on an ongoing basis, which can enable improved estimates of customer price sensitivity and performance on a category-by-category basis. This data can be used to improve further pricing decisions.

Abstract: A system and method for changing functionalities to websites uses a widget that retrieves at least one executable program file and a configuration file, which are published to a network, to execute the executable program and self-configure using the new configuration file.

Abstract: A tiered offer forecasting process is performed on a system executing code contained on a computer-readable storage medium. The process includes receiving purchase records for a product, each of the purchase records including a basket count identifying a quantity of the product purchased and a unit price identifying a purchase cost for the product. Pricing for a tiered offer is received. The pricing includes a first offer price for the product at a first tier, a second offer price for the product at a second tier, and a tier breakpoint differentiating the first tier from the second tier. Consumer acceptance of each of the first and second offer prices is ascertained. The consumer acceptance is utilized to forecast quantities of sales of the product at each of the first and second offer prices. This forecast of sales is provided to a user for implementation in the tiered offer.

Abstract: A markdown definition process is performed on a system executing code contained on a computer-readable storage medium to define a markdown event for a plurality of stores. The markdown definition process includes computing initial markdown schedules for products eligible for a markdown event, where an initial markdown schedule is computed for each store. The stores are categorized into store clusters in accordance with the initial markdown schedules so that stores having the greatest degree of commonality are grouped together. Final markdown schedules are determined for the markdown event, where a final markdown schedule is determined for each store cluster. Each final markdown schedule includes optimized markdown solutions specific to one of the store clusters for the products eligible for the markdown event. The final markdown schedules are provided to the stores, so that each of the stores categorized into one of the store clusters receives the same final markdown schedule.

Abstract: Disclosed is a market-based software system that will help user-retailers manage price and inventories more effectively. The system will take advantage of available price and sales data to provide pricing recommendations that will achieve a retail user's objectives. The system will offer a solution that will allow for pricing improvement shortly after installation by utilizing data that is readily available. The system will recommend price changes that help a user achieve specified objectives such as contribution, sales volume, desired margins, and the like. The system can also collect and process price and sales data on an ongoing basis, which can enable improved estimates of customer price sensitivity and performance on a category-by-category basis. This data can be used to improve further pricing decisions.

Abstract: Disclosed is a market-based software system that will help user-retailers manage price and inventories more effectively. The system will take advantage of available price and sales data to provide pricing recommendations that will achieve a retail user's objectives. The system will offer a solution that will allow for pricing improvement shortly after installation by utilizing data that is readily available. The system will recommend price changes that help a user achieve specified objectives such as contribution, sales volume, desired margins, and the like. The system can also collect and process price and sales data on an ongoing basis, which can enable improved estimates of customer price sensitivity and performance on a category-by-category basis. This data can be used to improve further pricing decisions.

Abstract: A market-based software system that will help user-retailers manage price and inventories more effectively. The system will take advantage of available price and sales data to provide pricing recommendations that will achieve a retail user's objectives. The system will offer a solution that will allow for pricing improvement shortly after installation by utilizing data that is readily available. The system will recommend price changes that help a user achieve specified objectives such as contribution, sales volume, desired margins, and the like. The system can also collect and process price and sales data on an ongoing basis, which can enable improved estimates of customer price sensitivity and performance on a category-by-category basis. This data can be used to improve further pricing decisions.