ML Is Redefining Product Recommendations for eCommerce

© Franco Folini

ML (Machine Learning) and AI (Artificial Intelligence) tools are becoming more and more affordable and approachable. The complexity and cost thresholds a problem has to touch to qualify for an ML treatment quickly go down. Many small tasks, such as providing product recommendations to eCommerce website visitors, can now be approached with ML solutions. The benefits are significant.

For years the big eCommerce players have leveraged ML to provide individualized, dynamic, and practical recommendations. But, unfortunately, small and medium eCommerce players didn’t have the budget, resources, and volume to integrate ML solutions into their systems. But now, the landscape is changing. New companies are coming to the market proposing affordable ML solutions that can be quickly and effectively integrated with almost any eCommerce platform.

Old Product Recommendation Systems

A classic way to generate product recommendations is to analyze the collection of converted carts (orders) and use an algorithm to create a prediction about the product a customer is more likely to purchase. When the number of orders is too small, companies can include in the analysis also the abandoned carts. One of the most popular algorithms to analyze the recent collective purchase history of the customers of an…