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Abstract

The present invention is remotely controlled automatic optimization system for maximizing in-store net profits by customized script-generated clip promotions to thousands of individually networked retail display-nodes from central server (OptiRetailChain). The computer-based and machine-learning display system includes: an advertising optimization function for display nodes, point of sale (POS) data input, retail database mining engine (RDME), client access and management control module, and in-store networked electronic clip display apparatus. The optimization function obtains data from chain-store database, combines product bundling data, which describe the associative relationships of various product sales in stores with recorded times of sale, inventory costs, margin profits etc. Physical location of purchased products on the store floor-areas are correlated with relevant display-nodes to create optimal clip display program (playlist) configurations for that specific display location and time. Most preferred product advertising combinations will be displayed in the best time slots for each node automatically. OptiRetailChain uses two methods of promotion optimization: real time scheduling and longer-term statistical optimization. Utilizing the machine learning capabilities, actual video-clip playlists will be dynamically updated for every display-node and respond to daily sales fluctuations for that store display location. This enables the optimization system to effectively control and automatically feature target advertising to large number of display-nodes in supermarket chain networks optimizing advertising capital without necessitating outside intervention.

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First Claim