Abstract: Elasticity of a particular product is calculated based on product demand against various price points. Accurate product demand calculations are ensured by calculating the price journey of the product, with appropriate adjustments made for out of stock conditions and promotions and or discounts. The price journey data is then input into an impact estimation algorithm which allows calculation of demand elasticity accounting for various real-world factors impacting demand and elasticity, such as: price of a substitute or compliment, competitor price, weather, local events, calendar events, and other factors. This approach allows for superior price journey-based item-specific elasticity calculation, which allows for superior optimization of item price to maximize volume and profit.

Abstract: The system and method described herein provide a computationally efficient clearance markdown planning system that may quickly automate the calculations of many possible markdown plans to determine the impact of various pricing options on total sales volume and revenue. While considering business constraints and other parameters, the markdown planning system may determine an optimized markdown plan for a particular product, season, and locale. In some aspects, the markdown planning system may use scaling and a variation of dynamic programming (DP) to quickly calculate and compare different potential markdown plans.

Abstract: Elasticity of a particular product is calculated based on product demand against various price points. Accurate product demand calculations are ensured by calculating the price journey of the product, with appropriate adjustments made for out of stock conditions and promotions and or discounts. The price journey data is then input into an impact estimation algorithm which allows calculation of demand elasticity accounting for various real-world factors impacting demand and elasticity, such as: price of a substitute or compliment, competitor price, weather, local events, calendar events, and other factors. This approach allows for superior price journey-based item-specific elasticity calculation, which allows for superior optimization of item price to maximize volume and profit.

Abstract: Systems, apparatuses, and methods are provided herein for rule-based automated retail product line linkage. The control circuit is configured to retrieve product data for a new product, comprising product categorical data, product numerical data, and product description data, and calculate unified line scores for each of the plurality of product lines in the product line database based on a categorical data score, a numerical data score, and a description data score. The control circuit is further configured to determine whether the new product corresponds to a new product line based on the unified line scores of the plurality of product lines and select a matching product line from the plurality of product lines for the new product based on the unified line scores of each of the plurality of product lines.

Abstract: Examples of the disclosure provide a system and method for entity-specific value optimization. An elasticity estimation module receives a data request for an item associated with an individual entity, and identifies a value response curve for the item associated with the individual entity. The elasticity estimation module determines an elasticity measure for the item associated with the individual entity. A value optimization module dynamically adjusts the identified value response curve for the item associated with the individual entity as new data corresponding to the item and the individual entity is received, and generates a value optimization recommendation based on the dynamic adjustment.

Abstract: In some embodiments, methods and systems of forecasting on-shelf availability of products at a retail sales facility for a selected interval of time are described. One or more on-shelf prediction factors associated with the products and/or shelf space at the retail sales facility may be processed by an electronic inventory management device to estimate whether a product is present or not present at a selected time interval on the shelf on the sales floor of the retail sales facility.

Abstract: Exemplary embodiments are directed to dynamically reconfiguring parameter values based on scanning or otherwise receiving entry of an identifier associated with physical objects. A value of a parameter associated with physical objects is determined for a first time period at one or more geographic locations and the value is stored in a first database. An identifier is scanned and/or entered into a computing device. Information related to a quantity of times the identifier is scanned and/or entered is recorded in a second database. A rate at which the identifier is scanned and/or entered during the first time period is analyzed. When the rate is less than a specified rate, a subsequent value of the parameter and a second time period for setting the subsequent value is determined based on a predicted response to the subsequent value, and the value in the first database is replaced with the subsequent value for the second time period.

Abstract: Provided herein are methodologies, systems, apparatus, and non-transitory computer-readable media for controlling a graphical user interface of an electronic display device to display a snow removal process type recommendation and a snow removal process value recommendation. A snow removal process recommendation tool can consider various store attributes, historical weather data, and other factors to compute a process type and process value recommendation for a selected store. A number of comparable stores, or sister-stores, can be computed based the stores which are most similar to the selected store in parking lot size, transaction volume, metadata, and other attributes. The snow removal process type recommendation and snow removal process value recommendation can be determined based on historical process data corresponding to these comparable stores.

Abstract: Methodologies, systems, and computer-readable media are provided for generating procurement aid recommendations and controlling a graphical user interface (GUI) of an electronic display device to render the a aid recommendations in response to a computational analysis of consumer activity data and estimated consumer procurement times. A procurement aid recommendation tool can receive store identification information via the GUI. A desired service level corresponding to a specific store can also be received. An estimated procurement time corresponding to consumers within the specific store can be computed, based in part on consumer activity data collected at the store. A minimal number of procurement aids required to meet the desired service level is computed, based in part on the estimated procurement time of the consumers. The GUI is configured to generate a graphical indication of the minimal number of procurement aids required to meet the desired service level at the specific store.