Summary: In today’s digitalized world, retailers are expected to keep up. The good news is, computer vision makes it possible.
Most will argue that the future of shopping is online. But if you look closer, you will find out that many retail chains are doing better than ever — of course, if they are quick to join the AI race and learn a thing or two from their eСommerce rivals.
To wit, 42% of multicategory retailers are already utilizing computer vision to address their pain points such as security, ever-changing demand, and product availability. Namely, computer vision helps them analyze the stock and customer behavior to identify problematic areas at a speed and depth unavailable to human employees.
Read on to find out which of your business-critical processes can be optimized with a computer vision software solution.
Preventing shoplifting
The Price Gun Store Infographic shows that American retailers lose 35 million dollars each day due to shoplifting.
To avoid being part of this alarming trend, enhance your CCTV security system with computer vision. Trained on historical data about previously committed acts of vandalism, such a solution will be able to prevent future thefts — by timely spotting fraudulent or slightly suspicious behavior from both customers and employees. This includes replacing barcode stickers, leaving something in the basket at the checkout counter, or hiding items in non-transparent bags.
Enhanced with face recognition, such monitoring systems can also identify previously caught shoplifters entering the store and notify your team about any suspicious activity.
Accelerating Restocking
Restocking and price tag auditing automated with a computer vision-powered assistant will allow you to revamp your daily in-store operations without hiring additional staff.
You can employ an autonomous helper like Tally the robot that scans the aisles and shelves, notifying the staff about the need to restock specific products, organize messy shelves, or fix outdated prices. With stock control assigned to a restless robot that pinpoints minor inconsistencies, your employees will have more time for tasks that require human involvement.
As a result, by streamlining inventory analysis with a computer vision-based assistant, you will not only address supply gaps but will also enhance customer service.
Understanding the demand better
Once you’ve determined which products are in high demand, you can employ computer vision to establish the link between a particular item and the person who buys it regularly. Namely, you can use this innovative tech to determine a person’s age, gender, race, and other attributes, creating a detailed portrait of your audience.
This portrait will be key to identifying other non-obvious needs of your customers. Maybe, you can do a better job serving old ladies who need a wider cat food choice, or students who prefer snacks and energy drinks the opportunities are endless.
Underpinned by demographic information about in-store shopper activity, you can create advanced heat maps and easily adapt your store layout for different categories of customers.
Automating Checkout
Computer vision can make checkout a self-service option or fully automate it, sparing clients an annoyable part of the shopping experience long queues.
To see the best cashierless practices in action, take a look at how Amazon Go stores work. Similar to self-driving cars, they leverage a mix of computer vision and deep learning technologies to detect when products are taken or returned to the shelves and keep track of them in their virtual cart. When shoppers leave the store with their goods, they are charged through their Amazon account.
Since customers don’t have to go to checkout, this technology contributes to client satisfaction. Moreover, it might drive spontaneous purchases, increasing the average bill.
What’s next?
While the retail gravitates towards digitalization, computer vision applications quite reasonably fit the bill.
This tech has the potential to become the next industry standard in a few years, helping you reinvent in-shop security, improve audience targeting, optimize poorly performing business models, and drastically save on hiring additional staff.
Author’s Bio:
Oksana Mikhalchuk is a Technology Writer at Oxagile, a New York-based provider of next-gen software engineering solutions around IoT, computer vision, biometrics, and more. Oksana creates content about state-of-the-art tech opportunities in healthcare, education, entertainment, and manufacturing. You can reach Oksana at oxana.mikhalchuk@oxagile.com or LinkedIn.