Introduction to AI in Retail
While the shopping experience hasn’t changed drastically over the years, artificial intelligence is revolutionizing traditional experiences with automation, personalization and increased efficiency.
Retailers that make the shift to omni-channel retail operations will find themselves with incredible opportunities: streamlined customer experiences, fast revenue growth and smart innovation. These are all great ways to empower businesses with high-level data and information leveraged with AI.
The market for global AI in retail is expected to grow from $5 billion in 2021 to more than $31 billion by 2028. If you haven’t started using AI, your competitors most likely have—and they’re going to amp up their businesses with its benefits while cutting costs at yours!
How is AI transforming the retail industry? This article mentions some of the many ways AI can help clothing retailers, including examples of how you can use AI to enhance your customer experience.
The rise of automated stores has been fueled by Amazon’s pioneering checkout-free shopping experience, which it introduced in its first store Amazon Go. Shoppers place items from shelves into their baskets and pay when they leave the store. Amazon then deducts money from your account to cover those purchases almost immediately. The result of this streamlining and reorganization is a wider market with fewer staff. The widespread implementation of automation in stores with Just Walk Out shopping technology is here to stay, and robots are cheaper than human labor. Similarly, McDonald’s recently announced plans to replace cashiers with digital ordering kiosks in 2,500 of its restaurants.
Price Regulation Strategies
To accommodate evolving customer tastes, retailers need agile supply chains that respond quickly to changing market demands. Retailers are using artificial intelligence to improve demand forecasting by mining insights from marketplace, consumer, and competitor data. AI business intelligence tools make proactive changes to a company’s marketing, merchandising and other strategies in order to reduce the risk of shifts happening that could hurt profits. From these changes, it brings an efficient solution to supply chain planning, as well as pricing and promotional planning.
Chatbot based Solutions
Interactive AI chatbots are a fantastic way to improve customer service in the retail industry. Bots that use AI and machine learning algorithms can converse with customers to answer common questions, direct them to helpful information and collect valuable customer data in the process.
Virtual Trial Rooms
Rebecca Minkoff, who has three stores around the country and is one of the first brands to create AI-powered smart mirrors, recently unveiled a new line of clothing that allows customers to see how an outfit looks on their body type before making purchases.
Shoppers can try them on in an interactive fitting room with custom lighting options. The dressing rooms use RFID technology to automatically know what customers are trying on and suggest other colors and sizes.
American Eagle is also creating interactive dressing rooms. Customers can scan items they like, and the store’s computer system notifies employees if customers need a certain item brought to them in fitting rooms. The technology even makes product recommendations based on past preferences.
Smart Inventory Management
Retailers today face new challenges maintaining an accurate inventory. By connecting parts of their operations and applying artificial intelligence, they gain a comprehensive view—from stores to shoppers’ homes—that helps them manage inventories more efficiently. AI can analyze historical demand data from suppliers to forecast future orders, which allows planning for fluctuations in stock levels and predict how much inventory is best. For example, if you knew other distributors were about to make the same order for a new product, you could get ahead by ordering it much sooner.
Another type of AI inventory management identifies out-of-stock items and pricing errors using smart shelves. Inventory robots can help staff monitor stock levels and spot misplaced items. Retailers can use computer vision-enabled checkout systems to mitigate product loss in real-time, freeing up associates’ time to help them improve the shopping experience.
Automated product recommendation engine
Digital and mobile portals are increasingly taking into account the preferences of individual customers, tailoring offerings based on past purchases. AI systems help these digital marketplaces evolve with every interaction to match users’ needs as quickly as possible. Automated assistants can help customers narrow down their selection of products by making recommendations based on shoppers’ needs, preferences, and fit, helping them build confidence in a purchase.
Success stories/case studies
Fusemachines has worked for the retail industry, with a privately owned global e-commerce platform focused on outdoor sports goods with more than 7 million active customers and close to 500 million annual webshop visitors. Similar to how AI was used for demand forecasting explained above in this article, Fusemachines successfully deployed models to forecast the sales of their top 50 products in the two countries with the most sales. To learn more about how we worked on this, discover this case study.
Future of Retail with AI
To succeed in today’s marketplace, retailers must respond to their customers with unprecedented speed and accuracy while cutting waste and increasing productivity. With the evolution of AI and machine learning, companies will continue to come up with more creative products and applications that transform businesses in the foreseeable future.
Implementing an AI system in a retail environment can seem like an overwhelming task, but it doesn’t have to be. With Fusemachines, an experienced technology solutions partner, you get the support and guidance needed to implement AI-powered technologies in your retail organization.
Reach out to one of our experts to learn more about our Case Study on Retail business.