Product Recommendation


Personalized products, whether online content recommendations or customized periodic services, have become the typical need of every user nowadays. The commodities are now preprogrammed to render user-specific results. Even if the exact user requirements aren’t available, the AI (Artificial Intelligence) based product recommendation systems point to the most relevant product that is still suitable to the user requirements. Such intelligent systems also recommend the user’s products/content/services based on their previous interactions with the system. A product recommendation system is a new way of letting users explore and know what they like the most. Once the system can predict the user’s personalized requisites with high accuracy, the user only makes multiple comebacks to the same system owing to higher satisfaction. So, with AI-based recommendation systems, the number of regular users keeps increasing.

Challenges Faced by the Customers

In a nutshell:

Recommendations of irrelevant, repetitive, and misleading products can annoy users. The AI-based recommendation systems check for a proper monitoring system whereby it evaluates the user’s interaction with the plan to assess and filter out unnecessary content.