Top 4 Computer Vision Applications in Retail Industry

Post by
Ghita EL Haitmy
Top 4 Computer Vision Applications in Retail Industry

Computer vision is one of the biggest buzzwords in the industry recently, on top of image annotation, object detection, face recognition, etc. In a report by Abhijith Nair Market Research, computer vision worth was $9.45 billion in 2020, expected to increase to $41.11 billion by 2030 with a compound annual growth rate (CAGR) of 16.0%. In fact, computer vision can be an incredible asset to the retail industry if applied properly. First, let’s find out what it is, though: 

What is computer vision?

Computer vision – a subset of machine vision – enables computers to extract information from images, videos, texts, and other data. From providing a real-world understanding of the environment and object properties to enabling automation of many parts of the supply chain, it has opened up new possibilities for streamlining business processes and algorithmic solutions.

Computer vision embarked on big data in many groundbreaking ways. However, it reached its popularity when Google Street View had introduced in 2007. The retail industry has been one of the first industries to make use of this incredible technology. Today, numerous applications of computer vision enhance business processes and provide better service to customers in the retail industry.

The connection between computer vision and retail. How to use computer vision in Retail?

Retail is entering a new era as computer vision comes to revolutionize it. Retailers that integrate computer vision into their business have seen significant gains in efficiency and improvements in customer experiences. Computer vision aids in monitoring the inventory in stores, identifying shoplifters, and s. That makes it critical for retailers to integrate computer vision into their inventory management processes. 

Amazon Grocery is the first Amazon customer's revolutionary grocery store technology. The new “Just Walk Out” experience is a first of its kind for grocery stores and will make shopping more convenient than ever. By leveraging the power of camera technology combined with computer vision, deep learning algorithms, and sensor fusion, Amazon has created a frictionless shopping experience that removes the need for dedicated cashiers and checkout lanes.

Computer vision use cases in retail

Computer vision is used in retail to improve business operations, provide capabilities that were not previously possible, and create new values for customers. In retail, computer vision systems could be used to identify a shopper in-store without checking for the shopper's membership card or swiping the credit card at checkout. These systems can also quickly detect items that have been misplaced on shelves through of properly annotated images, automatically identify products when shoppers take pictures, help employees find items faster via special apps, and send push notifications about sale items.

Computer vision technology has been used in a variety of ways. It is used to recognize faces, detect objects, and barcode them into the database. Here we will discuss some of the more specific computer vision applications in retail.

Computer vision’s impact on customer engagement

Computer vision’s impact on customer engagement can also be felt in ways that retailers may not initially expect. For example, once a retailer can identify a customer and track their movements within the store, they can begin sending those customers targeted offers. By sending these offers at specific times or locations, the retailer can encourage repeat visits while increasing sales.

Another benefit of computer vision is that it allows retailers to see which products are most popular with their customers, helping them make decisions about future inventory purchases. Once this information had collected and analyzed, retailers can use it to inform future marketing campaigns and product development efforts if needed.

In-store inventory management

In-store inventory management is one great example of where computer vision can provide immediate value for a retailer. You can also control exactly how much inventory your store has. Since computer vision makes it easy to recognize anything in the store, you can decide what products to keep, and those products are then correctly stored. Using this system will reduce cash flow since your store is supposed to hold only the stock needed right now. By automating your inventory management, you will get immediate updates on the number of products stocked. And if something goes wrong, you will know immediately. So, you can place another order for the same products or replenish the stock before other customers arrive. One benefit is that you don’t have to worry about keeping track of every item sold. Just update the system manually, and you will never lose sight of your inventory.

Targeted Advertising

Throughout the covid-19 pandemic, many businesses utilized computer vision in order to comply with government regulations. The technology helped them track who was coming and going in their stores so that they would know how many guests entered during a given day. One notable example of this is Target’s new store layout where cameras are set up throughout the building so that each customer entering will be captured as soon as they walk in. The information collected from these cameras can then be analyzed and used for targeted advertising purposes. Since customers are more likely to buy a product when it means something to them, Target can send personalized advertisements to those customers that were captured by the cameras at specific times on specific days

Other benefits include online analytics & performance tracking

The future of marketing is here. AI and automation are the key factors in designing digital experiences. When it comes to tracking performance, it's becoming difficult to predict with traditional tools. Even though the internet provides tons of data and statistical analysis, it cannot anticipate the actual picture. A solution can be provided by relying on self-service analytics that use multiple sources of data to provide deeper insights into your store's performance. Companies can predict the behavior of consumers to offer personalized suggestions and recommendations that can make a difference. This solution requires technical information and a thorough understanding to interpret results. On the other hand, a traditional solution will require constant human intervention. Thus, organizations should take advantage of both worlds.

Takeaways: Retailers can use computer vision to make shopping faster, easier, and more efficient

Computer vision can help save time and money, as well as make shopping more effective. These computer vision applications in retail highlight how to create unique stores with minimal effort. Whether you like to call them interactive or physical shops, you can choose to build these experiences by technological advancement and your current requirements. Use the power of computer vision, and give your business the edge over the competition.

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