Analytical Solutions – Retail

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RETAILERS

Our focus with Retailers is to provide their customers with a better shopping experience while increasing sales and profitability. The analytical software provides a myriad of marketing tools to achieve the desired results.
Analytics such as age and gender recognition, customer dwell time, people/heat mapping, occupancy/counting, facial recognition, ticket POS and consumer behaviour patterns are just some of the Analytics we derive from our software. In turn, we take these Analytics and turn them into actionable marketing solutions for the Retailer.

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DWELL TIME

Our dwell time video analytic detects how long a person is standing in front of a particular display or product in the aisle. When a customer spends i.e more than 3 minutes in one place (time parameters are totally adjustable), the software will notify a sales associate through a smart device to have them come over and assist and potentially up sell them on the desired product. The sales associate could even issue an instant in store redeemable coupon to the customer if they bought i.e 2 or more items.

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FACIAL RECOGNITION

In a smaller more upscale retail environment, the facial recognition software will pick up a customer coming into the store on a second and subsequent visits. Assuming the customer was on a loyalty program or information collected from the first visit, a VIP loyalty program could now be put into use. For example, the store associate is instantly notified upon arrival of the customer, addresses them by name and has all their previous purchasing habits on his/her smart phone.

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TICKETING POS INTEGRATION

Theft and fraud at cash checkout are always a problem. The practice of “sweethearting”, when a checkout clerk doesn’t scan an item for a friend, this can be detected by overhead video surveillance. But now add in the POS ticket analytic capabilities to the camera. This matches the sales receipt by item to the video of the purchaser but also counts the number of items that passes through the scanning area. The number of items scanned have to match the number of items that have been sold. As an added benefit, we can search individual items sold by video POS integration timelines. The information we derive here is inventory cross referencing. Who bought what, when and how many items sold.