Also referred to as the “eyes” of artificial intelligence (AI), computer vision technology seems to have the potential to transform the global retail industry. Both physical retail and eCommerce are increasing their investments into computer vision solutions to meet changing customer expectations and market needs.

Of course, the solution is still nascent in adoption. The global market for computer vision technology is projected to grow at over 300% to cross $41 billion by 2030. This is up from $9 billion in 2020. It’s fair to assume that only a fraction of that went into the retail sector. But things look set to change.

By integrating AI with in-store cameras, computer vision (CV) could well transform the retail sector across various focus areas. In the long run, CV technology can build customer loyalty through improved in-store experience. Besides that, CV solutions can also improve operational efficiency.

Here are seven real-life applications where AI-powered computer vision is making a notable difference:

1. Customer Self-Checkouts

With the emergence of online shopping, in-store customers also expect the same level of convenience and a seamless checkout experience. Self-checkouts (or machine-assisted checkouts) enable customers to pay for their products (through barcode scanning) without waiting at the payment counter. Among the latest retail trends, CV-powered cameras can identify store products without barcode scanning.

For retailers, self-checkouts mean a cashier-less or automated store. This, in turn, means lower overhead costs and faster customer service. An example of automated retail stores is Amazon Go, where AI and CV technologies can fully automate the customer checkout process. With powerful CV solutions integrated into backend systems like billing and inventory through a robust CV platform, retail stores can ensure appropriate billing, tighter control over inventory and stocking, and reduce revenue leakages due to inaccurate billing.

2. Inventory Management 

Many experts have suggested that if the order picking accuracy for inventory for any traditional or automated solution is lower than 98%, there is scope for improvement. That’s because higher values invariably affirm quality control standards, reduced cycle times, high shipment accuracy, etc. Anything that deviates from that calls for an adverse impact on end-user satisfaction.

As it stands, most inaccuracies are attributed to human errors. According to an industry study, 64% of retailers plan to deploy data-backed solutions like computer vision for inventory management over the next few years. 

Consider this; smart cameras and sensors can track inventory levels and even on-shelf products. This technology can then notify the staff about low stock levels or products placed incorrectly on store shelves.

For instance, the American retail company Sam’s Club is deploying robots to scan, track, and share information about product inventory and locations.

3. Barcode Scanning

As elucidated above, self-checkouts allow customers to use barcode scanning to pay for their purchases without waiting in queues. Besides this application, retail shoppers can use CV-enabled barcode scanning to learn more about in-store products and their reviews. For instance, smartphone apps (fitted with computer vision) enable shoppers to read product information using the smartphone camera.

Through computer vision, customers can finally view online product reviews and ratings all within a physical retail store. An interesting case study is that of Samsung’s Family Hub solution, which leverages CV technology to automatically “label” stored items in the user’s fridge.

4. Theft Prevention

Statistically, retail store theft reached a high of $61.7 billion in 2019 (up from $50.6 billion in 2018). This was equal to nearly 1.62% of the retail industry revenues. 

Computer vision technology provides a retail security system with “eyes” to track any suspicious in-store behavior and prevent losses. Based on machine learning algorithms, CV-enabled devices can monitor in-store consumer behavior and make the right decisions to prevent shoplifting and other thefts.

One prominent case study is that of American retail giant Walmart, which uses AI-powered surveillance cameras to reduce shoplifting in its stores.

5. Store Layouts

CV-enabled in-store cameras can track the physical movement of shoppers around the store. This is useful in determining their purchase patterns and marking the “hot areas” where shoppers make most of their purchases. With this information, retail companies are better informed to plan (or change) their store layout and product placements.

Among the recent trends, retail heat map technology uses real-time images to detect shoppers’ movements and high-traffic areas within the store. For example, Serbia-based fashion retailer Legend World Wide has designed a connected store with CV-equipped cameras and sensors.

6. Virtual Mirrors

Virtual mirrors represent the next-level customer experience and personalization in the modern retail space. They enable shoppers to connect with a fashion brand with a range of contextual information. With face detection, CV-enabled virtual mirrors can transform the shopper’s image into a virtual avatar.

Unsurprisingly, virtual mirrors have been adopted by multiple brands like H&M, Lacoste, and Ralph Lauren. In fact, US-based luxury menswear brand John Varvatos increased its average order value by 74% after creating a virtual store experience.

7. Crowd Analysis

With computer vision technology, retail stores can accurately perform crowd analysis along with consumer behavior analytics. For example, retailers can:

• Track consumer movement across the store.
• Track the products that they are most interested in.
• Calculate the time they spend on deciding each product.

CV-enabled advanced cameras can also track “eye movement” to determine the products customers look at most times. Retail marketers can use crowd analysis to optimize product displays and in-store advertisements. Similarly, in-store cameras can track facial expressions to evaluate how consumers “feel” about specific products.

How the KamerAI Platform Is Leveraging Computer Vision

KamerAI is a real-time CV-enabled automation platform that can connect a variety of business applications with highly functional CV applications. Along with computer vision, KamerAI ties together capabilities like AI, deep learning, and artificial neural networks.

Our CV-enabled visual analytics provides real-time insights from visual data. Here are some of our KamerAI-based solutions:

• Time-keeping automation uses facial recognition technology, thus reducing the dependence on biometric scanning or access cards.
• Barcode Scanning extracts and analyzes product barcodes from CCTV-captured visual data.
• Object dimensioning automatically captures the dimensions of shipping products, used in properly tracking customer deliveries.
• Optical code recognition (OCR) automatically detects alphabets, numbers, and shapes from visual data.

Here are four ways retail companies are leveraging the capabilities of KamerAI’s CV solutions:

• “Touchless” dimension is used by retailers to measure volumetric dimensions. It can read package tracking numbers (barcode) and serial numbers (OCR) on the package as it moves along a conveyor. This helps in optimizing their shipping costs and cartonization process.

For instance, a leading supply chain company used KamerAI-driven barcode and OCR capabilities to validate outbound deliveries against the customer order. Previously, the company was incurring major losses due to large volumes of deliveries returned by the customer.

• “Anomaly Detection” capability is used to visually inspect the products and packages before getting shipped to the customers. This helps improve the end customer satisfaction and save millions of dollars owing to labor costs & product returns.

Another case study is a fashion retailer that optimized shipping costs using our CV-enabled box measurement solution. By feeding shipping-related data into their billing and accounting system, they optimized their incurred expenses successfully.

• “Employee Productivity and Safety Compliance” capability enables retailers to track workforce safety in warehouses and stores by ergonomic poster study and PPE compliance. With KamerAI solutions, retail manufacturers can provide a safe working environment for their frontline workers and perform predictive maintenance.

• “Perimeter Scanning & Loss Prevention” capability helps prevent trespassing and maintain perimeter security through facial recognition technology. 

The Final Word

The use of computer vision can transform the retail industry in areas like customer experience and in-store operations. As such, retail companies must take a holistic approach to tap into the capabilities of AI-driven computer vision.

At KamerAI, we provide an end-to-end automation platform for our customers to derive business benefits from CV technology. With our range of products, we ensure that you remain ahead in your digital transformation journey.

Get in touch and speak to our KamerAI consultant today!