4 Ways Retailers Are Using Machine Learning
Machine learning and artificial intelligence are changing the world as we know it. From our online search engines to the way we do healthcare, machine learning is behind the scenes reshaping how our world works. Retail is no exception; machine learning has revolutionized retail both behind the scenes and how consumers shop at their favorite stories. Here are four major ways that machine learning is currently being used in the retail industry to the fullest extent.
1. Product Recommendation
Many stores such as Northface have purchased advanced AI-powered bots to help their shoppers navigate their online stores, recommending products and helping customers find the items they need. Amazon’s product recommendation engine may be the best-known use of machine learning-powered software in this regard. Statistics show that machine learning-based product recommendation engines work really well for shoppers and retailers alike—up to 35% of shoppers purchase items recommended to them by Amazon’s product recommendation algorithms. The potential revenue generated by these machine learning-based engines is notable, and why we can expect to see more retailers adopting similar product recommendation algorithms for their online stores in the future—assuming they haven’t already.
2. Understanding Customer Behavior/Customer Interaction
Whether you realize it or not, you and all shoppers are constantly leaving behind a digital footprint every time you enter a large retail store in person or online. The amount of data created at any given moment is massive, and retailers are using machine learning-powered algorithms to collect and analyze this data to understand their customers better. From personalized ads to forecasting demand for certain products, retailers can thank machine learning and artificial intelligence for this new way of recognizing and perceiving their own customer base. In regards to demand and sales forecasting, machine learning is expected to play a larger and more advanced role in the future as this technology has more data to collect and becomes more fine-tuned to the ebbs and flows of customer behavior.
3. In-Store and Online Smart Shopping
Have you ever wondered just how those Amazon Go stores really work? Machine learning and artificial intelligence play huge roles in just how different in-store shopping has become in the past few years. As soon as you enter one of these stories, a combination of cameras, sensors and AI-powered recognition bots are working at full speed to collect data about you, your location and the products your purchasing.
Amazon isn’t the only in-store retailer using these machine learning-based technologies in their stores either; many grocery outlets and large retailers like Target use similar technologies to help personalize their specific store locations (e.g. according to the needs of various neighborhoods) based on the personal information collected about each shopper and the products they buy.
Similarly, machine learning-powered software is behind the cashierless checkouts that are becoming more and more common in stores. Though most cashierless checkouts still require you to take out your wallet, we can expect deep learning technology like the ones Amazon Go uses to identify us quickly enough to grab our products and leave without ever opening our purses.
4. Pricing Optimization/Dynamic Pricing
Machine learning-based software is making retailers completely rethink how and when they price their products. Dynamic pricing has become a more common practice, especially for ecommerce, as the market is extremely fast-paced. With profit margins often as low as 1-2%, retailers stand to gain a lot of revenue from changing their prices multiple times a day by monitoring competitor prices and demand analysis. Dynamic pricing is easier said than done, though, and without the help of machine learning-based pricing software, retailers would be making these price changes at high risk of failure and profit loss without the vast amounts of pricing data they need.
Advanced pricing software has proven itself to increase revenue for retailers of all sizes without sacrificing their sales, and machine learning-based price optimization software is becoming more and more available to retailers of all sizes as time goes on. This means that Amazon and Walmart won’t be the only major players dominating the market using dynamic pricing; soon all retailers will have the potential to optimize their prices using machine learning-based software.
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