Transforming the Future of Retail with Vision AI 

When it comes to digital transformation, retailers are no longer asking, “What if?” They’re saying the time is now. The continuing pandemic, increasing worker shortages, and frustrating supply chain challenges require retailers to increase automation and efficiency as quickly as possible to navigate the convergence of trends and prepare for the future. 

For brick-and-mortar retail stores to survive and thrive today, it’s paramount that they integrate technology-based automation to improve operations, meet customer demand, and deliver service excellence.  

Partner with Plainsight to develop custom computer vision applications for your retail business.

Computer vision is a form of AI that applies algorithms to images and video, offering businesses a new way to gain insights into their day-to-day operations. Retailers can create custom vision AI models that provide entirely new solutions to both broad and specific issues, allowing brands to innovate in transformative ways. For example, large national retailer Home Depot has used visual search technology in their mobile app and noticed significant growth in just eighteen months once the feature was integrated.

For the retail industry in particular, integrating vision AI applications into traditional store operations can open up a world of fresh insights that empower better decision making. 

One especially valuable tool that retailers rely on are planograms, which help optimize space utilization, customer experience, and maximize sales in brick and mortar locations. 

Employees work from planograms to ensure in-house inventory is properly shelved, account for product sales, and determine how much product to re-order. When combined with vision AI algorithms, smart planograms can help retailers gather consistent, high-quality, real-time data in greater quantities than ever before. 

In short, computer vision insights can explode traditional retail sales analysis and bring an entire industry into the digital age. 

Smart Planograms and Vision AI 

Planograms are most commonly used to map store layouts and shelves. For example, retailers may use them to decide placement of coolers and fridges, or finalize the precise placement of specific products. 

When combined, planograms, cameras, and AI algorithms can offer retailers automated insights into sales, customer behavior, and predictive replenishment. Vision AI models can be created based on unique store planograms to map customer movement, confirm that store employees are adhering to approved product placement standards, and even alert managers when item inventory is getting low.

Planogram example found at

Imagine a vision AI solution that has memorized the preferred planogram of a grocery store, from the macro level of the store footprint to the micro level of shelving in aisle 5. A series of cameras, either installed or mobile (tablets), delivers images of store shelves several times a day. 

These images are then processed by comparing them to their shelf’s designated planogram. Instead of a team member auditing the aisles manually, the vision AI deployment would send the exact location and number of stock needed to the manager on duty. This manager can then facilitate timely restocking. Crucially, vision AI solutions can also report on these data points with a cadence and efficiency that humans simply can not match.


Vision AI for Optimized Store Operations

Smarter planogramming is just the beginning of how vision AI can transform day-to-day operations for retailers. Data-driven insights and real-time video analytics can track activities both within and across locations to empower better planning and decision making. 

  • Automated Shelf Management: Shelf-scanning robots are already making their way around the aisles of Giants, Stop & Shops, and other grocery stores. With the addition of shelf-managing AI, their cameras (and other cameras found throughout stores) will become more valuable data sources and empower automated alerts. 
  • Shopper Insights: Improved tools for tracking shopper behavior provide insight into volume, dwell times, people flow, and shopping trends at the store level and beyond.

    Unlocking Vision AI Insights for Retailers with Plainsight

    Traditionally, creating a high-quality dataset can be a long and tedious process. In the past, retailers looking to incorporate computer vision solutions into their business would need to hire a highly-specialized team consisting of data scientists and machine learning engineers to work on different steps of the computer vision pipeline. A labeling team might have to annotate thousands of images by hand, for instance, and finding the skilled coders necessary to train, deploy, and monitor AI models can be extremely challenging – and costly. 

    With Plainsight, every step of the vision AI lifecycle is optimized through a single solution. Our platform helps retailers to automate shelf management, empower predictive replenishment for inventory management, and build brand and customer loyalty with seamless vision AI solutions. 

    Our AI-powered labeling tools accelerate labeling tasks and dataset creation. From there, Plainsight’s automated model training and deployment pipeline creation makes operationalizing vision AI solutions feasible for users of all technical levels. Our platform was designed with the goal of making vision AI collaborative across organizations and intuitive for every member of every team.

    Plainsight empowers non-technical subject matter experts and machine learning engineers alike to create custom vision AI solutions to address industry challenges and, in the case of retail, solve problems across multiple locations down to the individual store.

    To learn more about how Plainsight’s vision AI platform helps retailers, contact us today.

     View All Blogs