Machine learning technologies and artificial intelligence (AI) are steadily integrating into our day-to-day life. From AI in retail sector — chatbots that offer 24/7 customer support and IKEA’s augmented reality app that allows you to place true-to-scale digital models of IKEA products in your home with a smartphone — to implementation of AI across all other industries, these solutions are already essential for the world.
AI and ML markets are projected to hit over $38.4 billion and $96.7 billion with compound annual growth rates (CAGR) of 39.18% and 43.8% by 2025, respectively. Being relatively new, these markets showcase some of the most incredible growth in terms of yearly revenue. For comparison, the entertainment and media market is expected to have only an 8.9% CAGR by 2030. A few questions may arise:
In this article, we’ll talk about the most popular use cases of AI in retail 2022 and how it can bring financial benefits to your business venture. Let’s get into AI trends that shape e-commerce standards in 2022.
Statistics show that 71% of users won’t even read an email if it’s not personalized. Furthermore, businesses report that personalized campaigns increased their mail revenue by 760%. With machine learning, e-commerce and retail companies promote relevant products to customers, based on their interests, searches, and purchase history. By presenting consumers with personalized recommendations, businesses create unique experiences and increase customer satisfaction.
Autocomplete and search suggestions are primary examples of machine learning implementation. Specifically tailored to the preferences of each customer and their search history, such algorithms make it easier for visitors to find a service or product they need, cutting off the time spent on browsing through irrelevant options.
Talking about finding what you need — chatbots are an excellent example of AI-powered tech. They help customers buy what they need with no need for staff to get involved. Chatbots offer 24/7 support to users that have questions and help generate insights on customers’ pain points and ways of communication for businesses. Businesses also install chatbots to cut costs of hiring customer support specialists on night shifts and paying them.
Another example of AI-based personalized search is North Face’s implementation of cognitive computing technology. The company uses it to ask customers questions about what they’ll do and where they’ll wear the coat. Based on customers’ responses, the algorithm creates personalized recommendations to help them find the perfect coat.
A quick audit of goods provided by AI in retail supply chain and warehouses identifies pricing errors and out-of-stock items. In massive warehouses like Amazon’s, it can take a long time to notice if a product has been sold out. An AI-based inventory management system uses smart shelves that alert staff about shortages of goods or misplaced items in the inventory.
Furthermore, kiosks extension for shelves lets visitors see all products available in the retail network’s warehouses, which is essential if some products are out-of-stock in the location a consumer came to shop in. It’s great for increasing customer satisfaction: not finding something they want to buy is in the second place of big frustrations for them.
There are virtual fitting rooms for jewelry, sneakers, glasses, and even bras. AR solutions like virtual try-on for rings use AI and machine learning techniques, so the ring you choose is perfectly placed onto your finger. Apparel brands like Old Navy, Levis, Brooks Brother, and Gap already use AI scanners — with virtual try-on rooms, they’ve managed to increase their online sales by 33%.
Some applications like IKEA’s Place app enable customers to see how furniture from the shop will look in their apartments via AR. Customers aim their camera to where they want to place the table, and AI calculates whether the table’s legs will fit right. They also select a color or material and can try different options.
The digital technology implementation requires time, financial resources, and abandoning an old-fashioned way of working. However, the pros of taking a modern approach will almost always outweigh the cons in the long run. Every retailer can find a solution to boost customer loyalty, increase employees’ productivity, and grow brand awareness with so many digital technologies to choose from. Here are some examples of cutting-edge use cases of AI in retail sector:
High-tech solutions like service robots that interact with customers and AI technology that recognize speech and gestures can revolutionize the retail and e-commerce market. Robots can help customers minimize contact with objects and other people. When almost 3.8 million get infected, and over 10 thousand people die from COVID-19 daily, AI-based solutions can help eliminate human contact and reduce the spread of the disease.
By using speech and image recognition systems, robots learn how to detect and interpret smile, angry, sad, or happy changes in voice. Machines with this kind of emotional intelligence can understand cognitive and emotive channels of human communication. For instance, Walmart uses AI-powered cameras that scan people’s faces to recognize shoplifters. The cameras also can detect aggravation and instantly notify the security.
New AI and machine learning solutions constantly appear on the market. Retail and e-commerce giants such as Amazon, IKEA, Walmart, and GAP are already implementing them in their 2022 shopping cycles. E-commerce and retail markets are highly competitive. If you want your business to survive this high-tech competition — 2022 is the year to make a change. Our company provides custom AI software development services to fulfill your business needs. To stay on the verge of innovation, contact us.
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