Patent ID: 7379890
Filing Date: 2008-05-27
Classification: G06Q

Abstract:
1. A decision support system that uses a merchandising parameter including a revenue or a profit, the support system comprising: prediction means for predicting a product demand for a plurality of non-identical products in a target period using predetermined purchasing data and predetermined pricing factors for the plurality of non-identical products; optimization means for optimizing a price and a promotion schedule of at least one of the non-identical products for the target period, the optimization means maximizing the merchandising parameter based on the predicted product demand for the plurality of non-identical products; a database for storing the predetermined purchasing data, the predetermined pricing factors, the optimized price and the optimized promotion schedule, the predetermined purchasing data including scanner data or historical purchase data that contains at least a date of purchase, a time of purchase, a bar code, a quantity bought and a price at the time of purchase; means for modeling and optimization of joint effects of the predetermined purchasing data and the predetermined pricing factors, said predetermined pricing factors including one or more of product brands, sales discounts, quantity discounts, promotion schedules, days of the week, pre-holiday days, post-holiday days, year seasons, and past sales histories of the plurality of non-identical products; means for data mining of the said historical database that performs aggregation of individual sale and promotion records into data batches corresponding to user-selected or system-determined time periods, and of extracting the contents of database fields corresponding to the said predetermined pricing factors; means for construction of an integrated pricing and promotion regression model or of a set of integrated pricing and promotion regression models to model joint effects of the plurality of said predetermined purchasing data and said predetermined pricing factors including pricing and promotion variables on the product demand of the plurality of non-identical products on sale; means for simultaneous estimation of said integrated pricing and promotion regression model or said set of integrated pricing and regression models and for separate stepwise estimation; means for construction of the predicted demand for products in categories with substitute demands and with complementary demands; means for separately demonstrating effects of prices on said predicted product demand in said categories based on said means for estimation; means for separately demonstrating effects of display times of a plurality of promotion clips running on in-store monitors on said predicted product demand in said categories based on said means for estimation; means for providing said database containing filtered data used for estimation computations, the filtered data including fields directly corresponding to regression factors in said integrated pricing and promotion regression models, and storing them in a format for reading and processing; the optimization means further: a) for optimizing a selected merchandising parameter for user-selected single products under regular sales conditions; b) for optimizing a selected merchandising parameter for user-selected product groups under regular sales conditions; c) for optimizing a selected merchandising parameter for user-selected single products under clearance sales conditions; d) for optimizing a selected merchandising parameter for user-selected product groups under clearance sales conditions; e) for constructing scenario reports that contains information units in tabled and graphical forms, the information units including a scenario task specification, all group profits, all group revenues, a group availability, an individual group task specification, individual group product pricing, individual group product profits, individual group product revenues, individual group product sales volumes, and individual group product availability, and for allowing a user to review price changes computed by the optimization system and to register a consent to the price changes through a password-protected channel between a user interface and the system prior to any implemented price changes.