International Business Machines Corporation

Stephen Hollis Lund

Brian John Cragun

Todd Mark Kelsey

An automated sales promotion selection system uses neural networks to identify promising sales promotions based on recent customer purchases. The system includes a customer information device that receives customer data relating to customer purchases of items from an inventory of items, a central processing unit having a sales promotion neural network and a storage unit containing a plurality of item identifiers comprising potential customer purchases of additional items from the inventory, wherein the sales opportunity neural network responds to customer data received from the customer information device by determining if one or more of the item identifiers in the storage unit corresponds to an item likely to be purchased by one of the customers, and an output device that receives the item identifiers of the likely purchases determined by the sales promotion neural network and produces a sales promotion relating to at least one of the item identifiers.

Automatic sales promotion selection system and method

A sales promotion program is dynamically selected from a plurality of programs for presentation in a program presentation unit by a neural network that makes its selection based on first detecting if a person is in the area immediately around the program presentation unit, then either selecting a general attract loop sales promotion program with the trained neural network using a set of predetermined system criteria if no person is detected in the immediate area or selecting a specific loop sales promotion program if at least one person is detected in the immediate area. The neural network is trained by selecting general attract loop programs that are run and then collecting data indicative of the number of persons responding to the general attract loop and also by selecting specific loop programs that are run if a person is in the immediate area and then collecting data indicative of the responses to the specific loop programs. The collected data thereby represents the success of the various sales programs in attracting and holding the attention of persons. The collected data is provided to the neural network in any one of a plurality of training schemes typical for neural networks, after which the trained neural network is provided with current, real-time selection data such that the trained network can select the most appropriate sales promotion program for running. The network can be retrained at regular intervals or in response to sales data or changes in the collected data.

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Boulder, CO, United States of America

Stephen Hollis Lund