Improving a customer’s experience and personalization is based on data. There is a need to filter, prioritize and efficiently deliver relevant information and product selection. Recommendation engines can improve a customer’s engagement and the purchase decisions. But these benefits are hard to get if a company does not have a good understanding of their data or how to use it efficiently.
THE AI APPROACH
An efficient recommender engine can help an organization maximize their ROI based on the information gathered on their customers’ preferences and purchases. Recommendation systems based on AI and Machine Learning models have the benefit of continuously updating and calibrating to the preferences of the user. There are many different types of recommendation systems, each with advantages for the organization using them.