Product Recommendation Engines bring forward a plethora of benefits such as an increase in average order value, fall in cart abandonment rate as well as help increase conversions. To know more visit : https://www.qwentic.com/blog/product-recommendation-engines

2. 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.

3. 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.

4. 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.

5. 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