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Top Applications of Computer Vision in the Retail Sector

  • Last Updated : 07 Jan, 2021

Ecommerce is becoming more and more popular these days! After all, there’s nothing more convenient than ordering something online and just getting it at your home in a few days. And if you don’t like it, you can always return it. While online shopping has all these advantages, it doesn’t mean that shopping at real-world stores has become any less popular. There’s nothing better than seeing what you are buying first hand, and getting a real-life human experience of shopping. In fact, there is some satisfaction in shopping at a large store that is just not there online. However, the retail sector can be improved a lot than its current form to provide a better experience for customers. And what better way than to use Computer Vision for this?!!

Top-Applications-of-Computer-Vision-in-the-Retail-Sector

Computer vision is a very complex field that allows computers to obtain information from images or videos. This is a multidisciplinary field that combines Artificial Intelligence and Machine Learning to analyze images and obtain insights. Now imagine the applications of computer vision in retail. There are already a lot of cameras in a retail store and using them along with machine learning can enhance the customer experience in ways that were not possible until now. So let’s see some of these applications of computer vision in the retail sector.

1. Automated Payments

What if you could enter a store, pick up something you want to buy, and just leave?!! You don’t need to pay at the till and you don’t need to stand in line to wait for the cashier. And don’t worry, you are not stealing the item either. The amount for whatever you have picked will be automatically deducted from your bank account. This sounds impossible and far-fetched but it could actually become a reality using computer vision. Stores could monitor all their products using a combination of sensors and computer vision so that they know when a product is picked up. They can also recognize the customer who has selected the product and automatically deduct the money from the customer after they leave the store. This seems to be a hi-tech fantasy than reality but it is already available in the AmazonGo stores in America. Automated payments will help in reducing the customer bottlenecks and lines at cashiers, especially during busy times like the holiday season.



2. Customer Data Management

When you go to a store where you have previously gone, chances are that they have your information like purchase history. And if you are an exclusive member, then obviously they have more details about you. Most retailers collect extensive customer data to make sure that they know their customers and what they want so that they can have targeted advertisements, more stock in the inventory for popular products, etc. But this collection of customer data can be much enhanced using computer vision. Retailers can use it to identify different customer demographics and their distinct purchase patterns and then provide targeted advertising to gain more insights. Retailers can also understand the products in their stores that catch the customer’s eyes more often and then create the stores in such a way to provide maximum visibility to these products. For example, they could provide the popular items at eye level in the store and shove the other items at the highest or lowest shelves.

3. In-Store Advertising

The world is filled with advertising these days! Anywhere you go, where it be hoardings or metro pillars, all you see are ads. In fact, this is true for the online world as well, whether it be Facebook, Instagram, YouTube, etc. But what about in-store advertising? That’s right, retailers also advertise themselves in-store but it is much more subtle. For example, you may enter a certain store and automatically get a message with a 15% discount from that store? How did that happen? Magic?!! No, it’s a technology called geofencing where retailers mark a geographical boundary and customers automatically get some messages when they enter this boundary. Computer vision can be used to enhance geofencing so that certain customers are identified when they enter a store and they get special discounts. Or they can also get suggestions about what products to buy depending on their previous purchase history. The options really are endless!

4. Personalized Service

Suppose that you are a regular customer at a store. It would be great if you could get special discounts or some perks. Wouldn’t that make it more likely that you would visit the store again? This brand loyalty is a great idea for stores to retain their customers and help improve their bottom line! But how to do this easily? Computer vision can help a lot with this. It can help stores to instantly identify their regular customers using facial recognition and provide them discounts or free items. After all, there are so many cameras already in a store so why not put them to good use! In addition to this, computer vision can also help a store to understand the type of customers they service and what each demographic of customers actually want. Then they can provide discounts or lucrative offers on popular products and gain even more loyal customer following. And this will increase their long term profit as well.

5. Theft Prevention

What is a major concern for retail stores that is not faced so often by Ecommerce sites? It’s theft of course! There are hundreds of cases of shoplifting in stores all over the world, a problem that is easily avoided online. After all, thieves cannot exactly walk out of an eCommerce site without paying for the product! Most retail stores are monitored by cameras as well as security personnel to ensure that nothing is stolen. But these are not full proof methods especially during busier times when it is easy to shoplift. Computer vision can be a big help here. Machine Learning algorithms can automatically monitor a store via the cameras with computer vision and alert a security guard if there is any theft occurring. These algorithms can also be trained to identify repeat offenders and keep an eye on them so they don’t steal anything again. All in all, they can greatly reduce the number of thefts that occur in retail stores all over the world.

6. Shelf Management

It is very important for retailers to know what they have on their shelves and what products are selling out the fastest. After all, it’s never a good idea when a customer wants a product and they see the shelves are empty and the product is sold out! This can be prevented using computer vision. Retails can keep a real-time eye on their products and immediately be notified if any products are running low or they are out of stock. In this way, shelf management is much easier and faster than if employees were occasionally checking the shelves and manually restocking any products that were running low. Apart from just checking the stock levels on the shelves, computer vision in shelf management can even help retailers understand how they should organize their shelves. Which brands of similar products they should keep next to each other and so on. All these things don’t sound important but they make a big difference in the psyche of the customers and can ultimately increase the profits for the retailers.

7. Employee Performance

Whatever advances are possible because of machines, there is no doubt that employees are a critical factor in the retail sector. After all, customer service is the most important thing and it can make or break the business of any retailer. This is the reason that computer vision can also play a very important role in employee performance to understand how the employees are providing customer service. Machine Learning Algorithms can be used in conjugation with security cameras to understand the level of satisfaction of the customers in response to the employee performance and the wrestling feedback can help improve the employees. Which will only help in improving the overall reputation of the store.

Conclusion

All of these applications of computer vision in the retail sector show the advantages of integrating technology in fields that it was never used in. After all, who would have thought that shopping might require sophisticated techs like machine learning and computer vision but it can help in many ways like automating payments, in-store advertising, theft prevention, customer data management, etc? In turn, all these advancements allow companies to provide a better retail experience to their customers and also increase their profits. It’s a win-win situation for all!




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