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US Patent 7379890 System and method for profit maximization in retail industry

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Is a
Patent
Patent
0

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
73798900
Patent Inventor Names
David Myr0
Eugene Grechanovsky0
Yuri Kazarinov0
Date of Patent
May 27, 2008
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Patent Application Number
106880180
Date Filed
October 17, 2003
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Patent Citations Received
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US Patent 12093989 Generating product recommendations using a blend of collaborative and content-based data
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US Patent 11887138 System and method for retail price optimization
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US Patent 11928685 System, method, and program product for recognizing and rejecting fraudulent purchase attempts in e-commerce
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US Patent 11941659 Systems and methods for intelligent promotion design with promotion scoring
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US Patent 11972460 System and method of personalizing online marketing campaigns
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US Patent 12008593 System, method and computer program for varying affiliate position displayed by intermediary
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US Patent 12014389 Systems and methods for collaborative offer generation
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US Patent 11676192 Localized sort of ranked product recommendations based on predicted user intent
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...
Patent Primary Examiner
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Susanna M. Diaz
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Patent abstract

A computer-based method and system accomplish automatic optimization of a preferred merchandising figure of merit like revenue, profit, etc. by concurrent optimization of prices and in-store promotion schedules for groups of interrelated products in a supermarket or in a chain of supermarkets. The basis of the system is a statistical model that combines effects of prices, promotion schedules and other factors that could influence demands, and produces a flexible nonparametric predictive demand function that can be optimized simultaneously in prices and promotion schedules. The system generates demand predictions for groups of interrelated products by applying data mining procedures to historical database that contains sales data along with various sales conditions, adjusting statistical predictive demand models, and then optimizing them in prices and promotion schedules. The user can interact with the system by selecting and customizing optimization and prediction scenarios provided by the system, and by requesting customized reports with results of particular optimization and prediction schemes.

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