Neural Network, Face Pay & VR. What Technologies Are Shaping Retail ?


Mobile payment is being replaced by FacePay payment, and electronic price tags are beginning to monitor price adjustments. By 2030, generation Z will make up one third of the entire workforce, which means they will be able to fully realize their purchasing power.

The habit of buzzers to make purchases through applications and voice assistants will create the prerequisites for changing the usual patterns at points of sale. 

In order to retain customers, stores will have to adapt to the new model preferred by the target audience. 

What new customer convenience solutions are being implemented in retail? 

Over the past year, we have seen an increase in demand for AI solutions for retail. 

To simplify the usual processes, AI promotes the personalization of marketing, optimizes offline and online shopping, helps the visitor to make purchases at the point of sale, and makes the interaction process through the digital platform simple and secure. According to Juniper Research, by 2023, retailers' spending on AI technologies will increase by $8.4 billion compared to 2019 and reach $12 billion. It is predicted that by this time more than 325 thousand outlets will implement AI technologies. The artificial intelligence market is growing, and retail is one of the active drivers of its growth.  

Among the main technological trends in retail for 2022, according to Gartner  is Generative AI (generative artificial intelligence). It works well with photo, video, sound and text, allows users to create new forms of creative content that can be used, for example, for a product advertising campaign. FacePay, IoT, VR and In-Store Robotics technologies, ESL system, Neural network, which can be found in stores, will be discussed below. 

FacePay. Face recognition 


The development and creation of a barrier-free environment is the trend of our time. In China, there have long been stores where you can pay using Face ID and similar identification systems. The best results in the face recognition process were achieved by neural networks.  

FacePay, cashless payment technology was developed in the context of a biometric password for a virtual bank card.  FacePay can recognize faces with over 70% accuracy even when wearing a medical mask. The development of a face recognition system will lead to stores without cash registers. Stores of a new type will become more convenient and safe for both business and consumers.  

IoT: Smart Shelves and Surveillance Cameras  

Stores will combine the work of the entire store according to the “smart home” principle. Based on the architecture of the Internet of things, it fully functions without sellers. The store's cameras are connected to a self-learning neural network. When a buyers take or return a product to the shelf, the system captures their action. Entry and exit from the store happens using the app. The buyers scans a QR code, and the technology identifies them and opens the door. If payment has not been made, the visitor will only be able to exit by pressing the emergency exit button. 

VR: research in a virtual store  

To determine the best position of products on the shelf, the American company Kellog conducted marketing research in virtual reality. An innovative VR solution based on eye tracker technology allowed the user wearing special glasses to enter the store and see digitized 3D models of goods on the shelves.  

The development opens up new opportunities for trade marketing and merchandising. With eye-tracking technology, you can test new packaging designs and determine the most successful product display in a "real" store.  

By the way, the results of the aforementioned study showed that the placement of the company's products on the lower shelves is 18% more effective than on the upper ones.  

In-Store Robotics: robots-advisers

It can be difficult for a buyer to navigate in large retail outlets. This problem was solved by Lowe's, which owns a chain of stores selling home improvement products. The LoweBot robot helps visitors find the right products. He asks the customer simple questions to understand what to find and accompanies him to the shelf. The robot replaces the sales assistant. It can also monitor inventory availability and provide information on items that need to be replenished. 

Neural network: search for similar products by images  

According to slyce research, 74% of users do not find the products they need using a traditional search engine. Visual search allows customers to make less effort to make the necessary purchase, and businesses to increase the number of product views and repeat visits, increasing the average check volume. The technology works on the basis of a neural network that has been trained on a set of data corresponding to the overall picture of the uploaded image. The neural network selects objects in the picture and analyzes their characteristics: color, shape and other important components. The comparison of the original image with the available products on the site occurs instantly, after which the user is prompted to select relevant options for purchase. 

ESL system: electronic price tags with automatic price adjustment  

It can be difficult to keep track of price changes in large retail stores. That is why customers continue to find themselves in situations where the cost of a product at the checkout differs from the price on the counter. The technology of digital price tags allows buyers to automatically adjust the cost of products after changing the price in the back office, promptly inform customers about discounts and special offers, and also reduce labor resources for sticking price tags on shelves.  

Online retailers have gone a little further. In addition to electronic price tags, for example, Amazon uses AI to optimize pricing. AI analyzes demand and competitive offers, taking into account situational marketing: holidays, weather conditions and other factors that affect the cost of the product, and then generates a fair price. U.S.-based Wise Athena has created a solution based on a transformative AI and machine learning platform that predicts demand with high confidence and determines the best value proposition.  

In combination with electronic price tags, cost optimization and demand forecasting technologies, retailers will be able to determine the elasticity of demand, quickly adjust promotions and, as a result, increase revenue. Nielsen analysts claim that even a 5% price difference can increase demand growth in a category by up to 75% compared to competitors. 


Digitalization of online and offline retail is gradually becoming not a competitive advantage, but a necessity. Reducing the checkout time has a positive effect on shopping habits. It also creates a request for stores of a new format, which, thanks to technological solutions, will make it faster and more convenient to receive the necessary goods and services.  All this gives impetus to the digital development of the environment, bringing it closer to the concept of "smart city".