Product Recommendation Engines for Ecommerce


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Product Recommendation Engines are a must have for every e-commerce platform to ensure Customer Loyalty and Customer Engagement. To know more visit :


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Product Recommendation Engines for Ecommerce.:

Product Recommendation Engines for Ecommerce.

What is a Product Recommendations Engine?:

What is a Product Recommendations Engine? It is a filtering tool which runs on technologies such as machine learning, data analytics and deep learning to provide purchase suggestions that match the prospective clients' tastes and interests as accurately as possible. Simply put it is the counterpart of a salesman on an e-commerce platform. It gently urges shoppers towards the right products by making personalized recommendations after analyzing and studying the shopper and the product he is interested in buying.

Types of Product Recommendation Engine:

Types of Product Recommendation Engine These filtering systems or Recommendation engines almost always work on any one of the following three algorithms: Collaborative Filtering : An algorithm that considers users interactions with products , with the assumption that other users will behave in similar ways. This records user-product interaction and tries to segment different types of users or products together.

Types of Product Recommendation Engine:

Types of Product Recommendation Engine Content-Based Filtering: It considers similarities between products and categories of products . It focusses on accurately categorizing products. It considers that if you buy an item, you will also need other things that are of the same category. Hybrid Filtering : It is a combination of both Content and Collaborative filtering . If product recommendation filtering systems were to be represented on a straight line Content filtering would make up one extreme while collaborative filtering would make up the other.

Benefits of Product Recommendation Engine:

Benefits of Product Recommendation Engine “ According to Mckinsey 35% of what customers purchase on Amazon and 75% of what they watch on Netflix come from Product Recommendation.” Improve Traffic Customized Content Engage Shoppers Increase conversions Reports Work Automation Increase average order value

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