The retail landscape is rapidly changing as consumers expect more convenience and better service across the entire retail customer journey. Research shows that 98% of retailers think their stores have to remove friction to survive in a new competitive landscape where seamless in-store experiences are expected.
In the e-commerce world, companies like Stitch Fix, Warby Parker, and Casper have removed all the friction customers used to encounter when shopping online: you can easily find what you’re looking for, try it on at home before you buy, and conveniently return items for free. Brick-and-mortar businesses are starting to catch up, and some stores, like Amazon Go and Zippin, already allow customers to leave the store without having to wait in line and visit a cashier to check out. But cumbersome check-out processes are not the only source of in-store friction—stock availability, incorrect or missing information, and poor customer service rank high when it comes to improving the shopping experience for customers.
Artificial intelligence and machine learning models that use computer vision to detect and track inventory and activity at the store are helping retailers solve these challenges. Here are the main ways in which computer vision is disrupting the retail industry:
No more empty shelves
With margins as low as 1 to 3%, retailers can’t afford inventory inefficiencies such as overstocks or out-of-stocks. Traditionally, store employees would manually count stock to ensure shelves were replenished when needed. Using computer vision, that task can be left to a machine, which eliminates human error, ensures shelves are always optimized, and frees up the employee’s time to assist customers and provide a much better in-store experience.
Accurate information and pricing on products
Picking up an item from the shelf thinking it’s 50% off and then discovering during check-out that the label was misplaced will leave customers disappointed and frustrated. Retail giant Walmart has been using artificial intelligence to ensure shelves are always labeled and information is correctly displayed for customers. Computer vision-powered sensors constantly scan labels and items to detect discrepancies and alert sales representatives when there is a price error or a promotion.
Superior customer assistance
Finding ways to personalize and enhance the customer experience is a very high priority for any retailer. With computer vision programs, shoppers can now test out products without actually trying them on to make sure they find their favorite item before leaving the store. For example, cosmetics leader Sephora uses computer vision-powered technology to track facial features and measure where the lips and eyes are, so customers can see how different types of makeup products look on them.
Cashier-less stores for faster check-out
Amazon is leading the way on the cashier-less stores front, and has opened four to-date. Cameras and sensors follow customers as they walk through the store, take items off shelves, and leave without checking out at a register. Computer vision models identify when an item is being picked up or put back onto a shelf, and match the item with its price to ensure customers are charged correctly. Moreover, this technology could play a crucial role in drastically reducing shoplifting issues as stores are constantly being monitored with computer vision systems.
More accurate pick-up and delivery orders
As online orders continue to grow, retail businesses are implementing more efficient processes to fulfill those orders. In the past, stores had personal shoppers that would be tasked with walking the store to fulfill online orders. Now, leading retailers like Zara, use robots with computer vision to take over that task, ensuring accuracy and speed, while employees can spend more time helping customers who need assistance in the store or while they pick up their order. Similarly, delivery orders are starting to be completed by autonomous vehicles in cities like Miami, for example, where Ford is delivering orders from over 70 businesses ranging from restaurants to hardware stores.
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