“AI is in a ‘golden age’ and solving problems that were once in the realm of sci-fi.”
– Jeff Bezos

Retailers have gone far beyond using simple data analysis. They are turning to artificial intelligence and machine learning for understanding their customers better, unifying commerce and optimizing service delivery.

Thanks to the advancements in deep learning, computer vision is providing retailers with visual insights needed to take their customer and employee experience to the next level.

According to the 32nd Annual Retail Technology Study by RIS, 30% of the retailers report that computer vision will be one of the top tech investments in the next two years.

Going beyond object classification

Today’s computer vision applications have evolved beyond simple object classification and are employing visual search, automated product recommendations, emotion detection, effective omnichannel strategies, and more.

• Object Detection: From identifying on-shelf/off-shelf products at the store to tracking in-stock and out-of-stock products, retailers are implementing object/product detection solutions using deep learning to quickly detect items with higher accuracy.

• Image Segmentation: Retailers are deploying several segmentation approaches to automate inventory analysis, collect product information, and optimize store display.

• Deep Tracking: In-store customer and employee behavior tracking have gone to another level with deep tracking. For example, emotion identification can help store managers to understand what customers feel and measure employee performance by watching shopper emotions for dissatisfaction, confusion, or hesitation.

Let’s explore some of the most exciting opportunities for Retailers.

Automated Stores

Enabling in-store cameras and sensors to track the products, auto-scan the bar codes, derive pricing, and offer accuracy in payments, retailers can now streamline customer service through self-checkouts.

Amazon’s offline division, Amazon Go is revolutionizing the future of retail stores by offering cashier-less checkouts across 27 plus stores. Customers simply can walk in, pick what they want, and walk out. Amazon’s “just walk out technology” is a combination of the following components.

• Sensor fusion
• Calibration
• Person detection
• Object detection
• Pose estimates
• Activity analysis

Improving the customer shopping experience

With natural language processing, computer vision, and machine learning, AI has opened so many avenues for retailers to deliver personalized shopping experiences. Let’s take the case of the French retailer of personal care and beauty products, Sephora. They implemented facial analysis and visualization technology to scan the skin of customers and automatically recommend the most compatible shade. They also provide users access to beauty tutorials on their own faces digitally to help achieve certain looks. This accelerates buying decisions and retains loyalty among the customers. Interesting and engaging, isn’t it!

Heatmap Analytics

Heatmaps are one of the AI superheroes with a special ability to perform intuitive visualization for analyzing footfall and movement of the customers and employees in the retail store. Deep learning algorithms are used for detecting and tracking the individuals in the videos captured through CCTV surveillance cameras. The point of interest section in the store and where the customers are gathering more can be evaluated through this excellent AI model.

All this will become a reality only if retailers’ AI and machine learning applications consist of contextual and relevant training data. Our computer vision experts at Apex CoVantage will help you develop a robust workflow that’s best suited to train your AI/ML project. With over 25 Years of experience delivering high-quality data labeling and data conversion services, Apex CoVantage is one of the top data labeling companies that have the expertise and resources to help you build production models faster and with greater accuracy. We will make sure your business stays ahead and is never outmoded. Together, let’s say “yay” to AI!