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AI in Retail


Retail is going through a period of change. Much of the innovation is coming from new technology and artificial intelligence (AI). As customers become more demanding in an exponentially growing digital world, billions of devices are connected, collating vast amounts of data leaving retail ripe for disruption. AI and its applications like machine learning and natural language processing are able to answer many of the questions for retail businesses. At a time where there is demand for personalised experiences, fast customer service, intelligent analytics and smarter shops, AI platforms are primed to drive society into the future. Although many are favouring e-commerce over traditional retail stores, understanding the usefulness of AI and data could be critical to the future if businesses don’t want to be swamped by the likes of Amazon for example. In fact, a report by EuroMonitor International predicted that over 80% of goods are still being purchased in brick and mortar stores. AI is the ideal way to bridge the experience gap between virtual and physical stores if they want to keep it that way. This article looks at the key use cases in retail and how AI has helped them keep up with their customers.

In Store Experience

Retailers are making use of AI for shoppers whilst they are in the store. For example, Macy’s On Call app helps shoppers whilst they navigate their way around the store. Customers input questions into the app such as asking where they can find a specific product, department or brand. The app will reply with a customised and relevant response to the user questions. It is the power of digital technology it a physical setting. The idea is based on research that showed consumers are more likely to use their phone in store to find information rather than approach a member of floor staff. Using machine learning, the app becomes more intelligent through very interaction. If it doesn’t know the answer to a question, it remembers the result for the next time a customer asks. In time, the hope would be that the machine can answer any question thrown at it in the store. Luxury fashion e-tailer Farfetch has come up with a solution to change the in-store experience for fashion retailers with its Store of the Future platform. The platform, in a similar way to the Macy’s solution looks to bring the digital and physical worlds together for an optimised customer experience. Businesses can collect data in-store such as in the fitting room where smart mirror technology allows customers to choose different sizes or colours of goods they are trying on. Information and shopping habits are stored for later so brands can learn about the specific styling requirements of their customers.

Image Recognition

Customers like engaging with different types of content and the popularity of social media platforms such as Instagram and Youtube show how images and video are the preferred choice right now. The department store Neiman Marcus has taken steps to take advantage of the trend through their app called ‘Snap.Find.Shop’. The AI-based app allows users to take photos they see whilst they are out shopping. It will then search the Neiman Marcus inventory to show all similar items. The more photos that get added to the database, the smarter the app becomes. Think of the solution as being similar to how Amazon are able to recommend products to customers based on what they have previously purchased. Recommendation engines are a great way to improve revenue. Amazon have reported as much as 40% of their sales coming via recommended products that the consumer may not have bought otherwise.


The hardware stores Lowes successfully deployed in-store robotics back in 2016. The LoweBot is able to show products where to find products and answer simple questions in multiple languages. The objective was to free up employees, so they had more time to answer complex queries from customers and show their expertise. As well as this, the robots monitor stock levels so the inventory can be kept up-to-date automatically without relying on staff to carry out the repetitive and monotonous task. Walmart have also used robotics to scan store shelves. The bots roam the aisles and check for missing items or areas that are low on stock. It can even check if price tags need changing by using AI sensors. Like the Lowes solution, employees are given more time to spend with customers and improve the experience rather than worry about stocking shelves. Fashion brand Zara are also using robots in the warehouse to quickly get items as a customer comes into store for a pick-up.

Amazon Go

We all know that Amazon is primarily an e-commerce retailer but they have ventured into traditional retail (of sorts) with their Amazon Go stores. Sensors and cameras in the store allow customers to pick up what they need, put it in a bag and walk out. There are no cashiers or cash. Instead of this, their Amazon account is charged as they leave. AI creates a seamless shopping experience without the need for lots of staff. The stores have not become mainstream where there are still a few glitches e.g. in a busy store, it doesn’t always interpret properly what people pick up. In time however, it is expected similar retail outlets will pop-up.


Clothing store Uniqlo have been using the power of in-store emotion. When customers look at images of products on screen, their reaction is tracked via neurotransmitters as a view to how much they like the style or colour. Based on that reaction, the customer is recommended products that are most likely to suit them. This is a great example of AI creating an experience without virtually zero input required from the customer.


Popular clothing brand H&M had the novel idea of using in-store receipts to work out when shelves need to be re-stocked. For example, instead of supplying every store with the same items, if the data shows that one store outperforms another with a certain line, algorithms adjust the levels accordingly. There is a clear cost saving exercise in monitoring stock levels as well as ensuring customers in-store only see the products they are going to be interested.

Removing Efforts

Buying make-up has traditionally been quite a stressful experience in stores. If a customer doesn’t know what shade or brand they want, it can put them off shopping. Brands like Sephora are making the experience better with their Color IQ platform. In the store, the AI-based system will scan the customers face and make recommendations for concealers or foundation shades that suit them best. It is a huge help to customers who would normally try to find the right product via trial and error.


To keep customers coming into store, retail outlets are using AI to enhance the customer experience, improve staff productivity and utilisation and reduce customer effort whilst shopping. With e-commerce causing major disruptions to traditional brick and mortar stores, creating an environment that attracts and excites customers is becoming fundamental rather than optional. In the future, retailers will continue to deploy this cutting-edge technology to keep up with their digital counterparts. Personalised and engaging environments will keep retail alive.