Suggestions to customers for products they may be interested in based on products they’ve already bought or viewed online. For example, if a customer bought the same tank top in 3 colors, there’s a good chance they’ll like the same tank in a new color. Personalized product recommendations, which mathematical calculations called algorithms find out on the back end, are a key feature of websites for cross-selling and upselling.
A customer who previously bought a camera might receive personalized recommendations for camera accessories like lenses, tripods, or camera bags. These recommendations are tailored based on the customer’s purchase history and browsing behavior, aiming to increase the likelihood of additional purchases and enhance the overall shopping experience.