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Beyond pixels: Harnessing the power of Computer Vision in Retail

Beyond pixels Harnessing the power of Computer Vision in Retail

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Today’s retail landscape is highly dynamic. It is teeming with cut-throat competition. Retailers constantly seek innovative strategies to stay ahead of the curve, streamline operations, increase efficiency, and enhance the customer experience. Whether a physical brick-and-mortar store or an online store, the technology that is making strides in retail is computer vision. When boosted by the power of AI with hyperscalers such as Microsoft Azure, it can unlock several opportunities for retailers. Microsoft Azure AI Vision is a comprehensive suite of services offering innovative computer vision capabilities that can skyrocket your retail business. In this blog, we will explore the various ways you can leverage Azure AI Vision in retail, regardless of the retail experience you offer.

Computer Vision solutions in Retail with Azure AI Vision

With Azure AI Vision, you can give applications the power to analyze images, read text, and recognize faces easily. It comes packed with features such as prebuilt image tagging, text extraction with OCR, and responsible facial recognition that enhance the intelligence of your projects. Another advanced feature of Azure AI Vision is spatial analysis, which allows retailers to understand people’s physical movements and presence in real-time. How are these features going to benefit retail owners? Let us find out now.

Retail Heat Maps

Spatial analysis is a critical asset. Retailers can use it to create heat maps for their stores. By harnessing real-time imaging to detect movements, retailers can understand the traffic volume on their floor, comprehend the store’s functionality, and pinpoint customer behavior. 

For instance, Sephora, Samsonite, and ATU Duty-Free use heat maps within their stores to gauge customers’ activities, test new merchandising strategies, and experiment with layout strategies. Previously, retailers could only rely on educated guesses to make these decisions. But now, with precise data available, they can make data-driven decisions to optimize store configurations, refine product placement, and enhance the overall shopping experience.

Analyzing customer assistance demands

Furthermore, computer vision can also provide insights into peak-hour customer demand requirements and optimal shift assignments. In this area, retailers would make decisions based on assumptions without the support of data about peak hours and customers’ assistance demands.

It is not surprising that real-time spatial analysis and heat maps are gaining rapid popularity among retail companies. Using Azure AI Vision, you can integrate spatial analysis into your retail applications and get real-time data. 

Enhancing Retail Security with Computer Vision 

Shoplifting is a persistent issue that has been bothering retailers over the years. The BRC Crime Survey highlights the severity of the problem, as $1.2 billion was lost to shoplifting in 2022 in the UK alone. Many businesses have realized the need for an effective way to prevent theft and shoplifting in stores. Computer vision is a powerful technology that can enhance the store’s security. It becomes the ‘eyes’ that are efficient in watching, leaving no loopholes for shoplifters to take advantage of. 

Furthermore, it uses ML algorithms to observe customer behavior, identify patterns, and make informed decisions. Among the various computer vision use cases, a critical application is to detect suspicious behavior linked with fraud and theft. The technology is already effective in combating employee theft and ‘sweethearting’ where cashiers miss scanning items or bill incorrect prices. Computer vision can identify each product in the checkout area and correlate them with transactions, preventing theft and fraud.

Measuring shopper’s interaction- crowd analysis

Retailers can leverage Azure AI Vision and build customer analysis applications connected with sensors and cameras. These apps can detect patterns and behaviors, capture metrics such as pass-by traffic rates, map the buyer’s journey throughout the store, and more. They can also find out which promotions garner engagement and which don’t. 

Besides observing buyer behavior, it observes customer and staff interaction, giving real-time insights into in-store service engagements. With Azure AI Vision’s advanced image and video analysis capabilities, retailers can process videos and give insights on footfall, people counting, pass-by traffic, engagement, and more.

Quality assurance in retail

Maintaining top-notch quality is paramount, especially in fashion, electronics, or visually appealing products. Retailers can use computer vision to do a thorough visual inspection of the products. They can conduct it at the manufacturing unit, distribution stage, and in-store. You can harness Azure AI Vision to detect defects or imperfections in products. The algorithms can compare each product against the standard to ensure it meets the design criteria covering size, color, and quality benchmarks. This step ensures that products meet quality standards and results in customer satisfaction, lower churn rates, and more trust in the brand.

Inventory management with Computer Vision

Maintaining optimal inventory levels is critical for retailers to meet customer needs and streamline sales. Retailers can integrate Azure AI Vision with inventory management systems and analyze the visual data from cameras mounted on shelves. This can swiftly identify low inventory levels and notify the store staff for prompt action.

This approach is beneficial in providing a seamless shopping experience and minimizing missed sales opportunities. With inventory management automation, retailers can streamline product replenishment workflows, ensuring that popular products are stocked and available to customers.

Image recognition in retail

Focusing on marketing analytics and augmented reality (AR), there is a buzz around image recognition in retail. Retailers can use image recognition to add services to the products customers see in physical stores. Imagine a shopper entering a store and scanning a product with an app. The app displays the product and pulls up the present inventory. It can also suggest similar products and encourage the customer to buy the product by having a sales executive bring it to them. Although full-fledged adoption is expected soon, this technique allows personalized suggestions and boosts in-store engagement, retaining sales amidst online price comparisons.

In-store advertising

Retailers can harness computer vision to improve their geofencing capabilities. It can result in stores being able to identify specific customers on their entry and send them tailored discounts. Additionally, these shoppers can also receive personalized recommendations based on their purchase history.

Virtual mirrors and recommendations

Virtual mirrors, an upcoming retail trend, can transform personalization and enhance the customer experience. Essentially, the mirrors house a traditional mirror with a display behind the glass. The display is powered by computer vision cameras and AR capabilities. They can display a wide range of contextual information, which enhances the shopper’s experience and helps them connect better with the brand. 

For example, FindMe is an in-store virtual fitting room solution that helps to ‘complete the look’. The ML engines give real-time fashion recommendations based on the shopper’s current outfits.

Cashier-less checking out

A long queue at the checkout process often affects the shopping experience. Many customers even abandon their carts, which results in customers seeking other alternatives and shopping locations. 

Self-checkout or cashier-less stores have gained immense popularity recently. Using computer vision and deep learning technology to track and identify products and automatically charge the amount when leaving the store, the process eliminates the physical cashier, queues, and even checkout machines. 

Conclusion

Computer vision is not just a trend; it is a game changer. It is actively reshaping the retail industry landscape. From enriching customer experiences and streamlining inventory management to making data-driven decisions on store layout, marketing campaigns, and bolstering security, the real applications are impactful. Retailers can leverage these benefits to trigger their business growth and gain a competitive advantage.

Azure AI Vision can seamlessly integrate with existing business apps and enterprise systems, providing advanced computer vision capabilities. If you are a retail business owner with a computer vision use case, Azure AI Vision is the best solution for you. And if you are searching for a trusted technology partner to guide you through implementation and maximize the potential of Azure AI Vision, look no further than Saxon. With two decades of rich experience in empowering businesses to achieve their objectives, we are well-equipped to handle your journey. Schedule a call, and our experts will help you identify the use case and jumpstart your retail journey with Azure AI Vision.

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