Machine learning helps businesses improve their cross-selling capabilities and increase customer loyalty. In fact, many companies nowadays deploy recommender systems, which infer their customers’ preferences to propose them personalized products or services. With such a system in place, an online groceries store can propose shopping baskets, a multimedia platform can recommend novel videos, or an investment platform can recommend custom portfolios to the customers.
But what if a regular shopper suddenly decided to try a vegan diet? What if a video consumer wants more sci-fi content? What if the investor wants to switch to long term and low-risk investments?
Download our free White Paper to know more about how to implement the recommender system that responds to the shifting preferences if its users.
In this paper, we demonstrate our implementation with a FinTech use case.