While today’s retail industry mainly consists of typical brick-and-mortar stores, smart stores are on the rise. Amazon Go revolutionized the way customers purchase items while also smartly analyzing customer behavior, all through artificial intelligence and machine learning. By solving inefficiencies, smart stores powered by AI and ML can alter retail dramatically.
AI-driven smart stores completely eliminate the need for cashiers. Amazon Go uses a pay-and-go method for its stores: customers scan the Amazon Go app to enter the items they want, which will automatically be added to their cart. After the customer is done, they leave the store and all of the items are billed to their Amazon account. The store utilizes similar AI technology to self-driving cars, such as computer vision, deep learning algorithms, and sensor fusion, in order to accomplish their Just Walk Out shopping experience.
Another non-cashier method of payment is the Electronic Shelf Label model; customers scan the items they want, scan their credit card (if not already registered), and check out. The AI technology permits a completely contactless experience for both employees and customers, while also increasing overall efficiency. There are no frustrating wait times to get through lines, and employees can attend to other customer service tasks.
AI technology in retail is unique in that it can track and analyze consumer behavior, and subsequently use that data to improve its services. According to an IBM study, 45 percent of customers expect the personalization they receive when shopping online to translate to shopping in-stores, which AI can help with. AI cameras and sensors can detect when an item is placed back after a customer picks it up to inspect it. Based on this data, stores can decide if they should place the item elsewhere, and it generally helps them see why this missed sale occurred.
AI-driven POS can help determine who the consumers are and which types of offers and deals they respond to, giving the business valuable insight into customer demographics, peak operation hours, and inventory. In order to learn what influences customers’ purchasing habits, data can be collected from their previous shopping habits and purchase history. Ultimately, integrative automation from AI-driven POS systems connect multiple payment locations, such as online, in-store, apps, and more. These connected channels will then update in real-time, providing the business with many touchpoints that help them understand customers’ experiences.
AI-driven smart stores have benefits for marketing and security as well. Customer targeting can become more accurate, individualized, and function in real-time when algorithms comb through the growing amounts of customer data. Products, services, and deals can be generated from the AI understanding customers’ preferences and needs. In terms of security, algorithms can recognize frequent customers and quickly accept their payments, while also detecting and preventing potentially fraudulent payments.
AI and ML are powerful tools that can change the way retail operates. Certain smart stores today utilize these tools extensively to create a more personalized, enjoyable customer experience and to significantly improve how their businesses operate. We’ll surely see even more smart stores in the near future.