Rahil Patel

Senior Computer Vision Engineer at Snap2Insight

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Bengaluru, India

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Snap2Insight

One of the leading health and personal care brands had planned a promotional campaign offering bonus packs at a promotional price in the face of some intense competition from its rival brand. Their customer (Team Leader for the brand at a retail chain) had worked with a major retailer to put up pallet displays with eye catching graphic skirtsacross all its stores nationwide. Their customer has often seen poor sales lift across 30-40% stores for such campaigns in the past. Snap2Insight was tasked to verify quality of execution nationwide and identify stores with incomplete execution or no execution. Leveraging their partnership with a leading crowdsourcing vendor, they quickly gathered photos of displays from every single store and using their patent pending Deep Learning technology, they analysed them to recognise SKUs stocked, present of graphic skirt, promotional price and type of display put up. Using execution scores they provided for each store covered under this promotional campaign, their customer worked with their retail coverage partner (merchandiser) to prioritise and fix all stores with low execution score and high potential for sales lift, thereby improving sales and achieving break over for over 90% of stores.


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11-50

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