If you follow tech news, your feed is undoubtedly inundated with article after article about how AI or machine learning is set to revolutionize your field. Retail is no exception to this trend. From chatbots to supply chain to inventory management, the emerging technologies of AI and machine learning are helping retailers understand customers better while increasing efficiency. Before we dive into some specific explanations, let’s start with the basics.
Artificial Intelligence and Machine Learning
These two terms are bandied about almost interchangeably at times, but there’s a definite difference between these two technologies. To keep it simple, artificial intelligence is the broader construct of how machines become more intelligent. Machine learning falls under the AI umbrella — it’s a specific set of algorithms that help machines learn and anticipate. For a more detailed explanation, go deeper into the AI/machine learning distinction with Matroid founder Reza Zadah.
Examples of AI in Retail
As much as machine learning counts itself as one of AI’s segments, AI tackles some of the bigger, broader retail areas, while machine learning hones in on increasingly specific tasks. For example, Amazon and Alibaba are using AI to dial in on what customers are interested in to drive personalization in retail experiences. Fueling those recommendations? That’s AI.
AI can spot trends faster to provide customers with what they want just as they realize they want it. FINDMINE, for example, has an AI-powered engine that can recommend accessories to complete the look of an outfit almost instantaneously. This not only allows for an opportunity to upsell and to gather data on customer shopping habits; it leads to an adaptive, anticipatory, and satisfying experience for customers. And, with this growing ability to anticipate, AI can help the supply chain by automatically knowing what’s available and recommending those in-stock items. With AI’s ability to go over more variables more quickly than any human ever could, cost reductions and supply chain optimization go to the next level.
Machine Learning in Retail
Machine learning gets more into the nitty-gritty of improving efficiency and productivity in retail. Inventory efficiency skyrockets when powered by machine learning. It knows when you need to reorder and can automate price drops to stay competitive. It can even be used in robots like Tally, a mobile shelf auditing and analytics solution that literally surveys store shelves, then uses machine learning to optimize inventory.
Chatbots are among the most talked about machine learning advancements of late. They use automated responses and machine learning to start and hold conversations with customers. It’s a huge efficiency boost that’s expected to reduce business costs by $8 billion in the next five years. Imagine a world where customers can interact with a company immediately and get the answers they want quickly. That’s what machine learning delivers with chatbots.
Speaking of efficiency, labor is the second most expensive cost to any retailer. Machine learning can help drive efficient staffing and give your associates an edge. It can supply information at their fingertips and help them more quickly recognize when a customer needs help. By increasing efficiency and productivity at machine levels, associates and management are freed up to focus on adding extra value and creative input to customer experiences.
The Next Step in Retail AI
Where things really start to get fun is when we begin looking at the future of AI in retail. With the right data, AI can curate personalized, truly individualized experiences for each and every consumer. Imagine entering a coffee shop, donning a VR headset and having an in-store experience tailored to fit your exact interests. And after that, maybe an autonomous car service picks your kids up from school and brings them to you at your one-of-a-kind espresso bar. The possibilities are endless.
AI and machine learning, while different, are part of an undeniable tech revolution in retail, one that will benefit customers and businesses alike. Stay up to date on the retail future as it happens by reading our blogs on the IT Peer Network and following our feed of retail news on Twitter.