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System and method for identifying and reacting to shopper flow impediments in physical stores Disclosure Number: IPCOM000239097D
Publication Date: 2014-Oct-10
Document File: 2 page(s) / 39K

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The Prior Art Database


Disclosed is a real-time system for monitoring customer walking patterns and flow in a physical store and alerting employees when a disruption or impediment is detected.

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System and method for identifying and reacting to shopper flow impediments in physical stores

Major retailers are starting to adopt shopper flow pattern and recognition software that tracks individuals within the physical stores. Current technology can be enhanced to extend the merchants' ability to manage employees' and shoppers' experiences in the situations when regular shopping flows become abnormally blocked.

In an example of the problem, Shop A runs a campaign to sell more Brand Z cereal. After long negotiations with supplier, the prices for cereal are dropped by 40% for one day only. On the day of the sale, in the morning, a shopper accidently spills a full cup of coffee in the cereal aisle. Because of that spill, many shoppers decide not to enter the isle, and while the problem is rectified 40 minutes later a number of potential sales is already lost.

The only existing solution is to have enough employees on the store floor to watch for potential shopping route blockages . While that strategy might work in smaller stores, it certainly has many drawbacks in larger stores. With current trends toward self- shopping and self-checkout, such shopping flow blockages might go unnoticed for a rather long time.

With existing systems, the data that is stored on a central server is generally analyzed in off-peak times to identify shopper flow patterns and identify areas of clustering for marketing and promotional events. Real-time data analysis is currently limited to marketing or promoting to an individual shopper.

The novel contribution is a real-time s...