Recommendation Engines

Our information filtering system seeks to predict a user’s preferences and ratings through both collaborative and content based filtering.

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How you make sure that your product or services are
getting to the right people?


Our information filtering system seeks to predict a user’s preferences and ratings through both collaborative and content based filtering.
Recommendation Engines are a useful alternative to search algorithms since they help users discover items they might not have found otherwise and they are proven to reduce customer “churn” while driving revenue.

Right now, customers have never had so much choice… so how do we make sure that your product or services are getting to the right people? Through Recommendation Engines we can solve this problem and deliver increased customer engagement and loyalty.
In simple terms a Recommendation Engine is a really good “sales assistant” – there job is to identify cross-sell and up-sell opportunities. Your customers may ask for a product and the engine will not only show them the product they requested, but also related one’s based on things like similarities, complimentary and other items customers have purchased also.

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Introduction to Recommendation Engines - DataScience.com Published on Jun 26, 2017
Data Scientist Tuck Ngun explains how recommendation engines work and how they bring value to businesses like Netflix and Amazon.