Please wait while we enable your Account


Contacting Amazon Web Services
Deploying Cloud Servers, Storage, Transcoding & Database Servers
Deploying Global CDN
Deploying Firewall & Enabling Security Measures
Deploying the CMS & Admin Module
Deploying Website, Mobile & TV Apps framework
Creating your FTP account
Finishing up all the modules
Preparing for launch

Applications and Examples of a Recommendation System

Ankit Jena Published on : 17 February 2022
Applications and examples of a recommendation system


You are at the right place to know the ABCs of a recommendation engine. Something that we take for granted, has so much going on behind, it’s impressive to say the least! Are you confused about what a recommendation system actually does? What are applications and examples of a recommendation system? 

Well, in layman terms, in this highly eventful world, each person looks for accurate information in order to complete his or her task without wasting a single moment. Whether it’s watching a movie, listening to music, buying clothes or home accessories from online sites, getting precise or relevant contents or products as per usage or relevancy, according to users’ preference, saves time and boosts user engagement. And that’s what a recommendation engine does. It suggests users with their favorite movies, music or products and services according to their likes and dislikes. 


What is a Recommendation System?

A recommendation system provides users with personalized experience in buying online products or services. It offers recommendations to handle the ever-increasing online information overload issues and boost customer relationship management.

Recommendation engine makes an effort to suggest the most suitable products, services or contents to any particular user or users by calculating their interest based on their behaviors. If I were to put it in marketing terms, the recommendation engine is a clever salesman who knows the customer’s taste, style, and thus wins the game by showcasing the perfect product or service to the customer that they would prefer to buy. 

Some of the great examples of recommendation engine usages are:

  • Facebook – It recommends you under the section – “People You May Know”
  • Netflix – It recommends you under the section – “Other Movies You May Enjoy”
  • LinkedIn – It helps you find right jobs under the section – “Jobs You May Be Interested In”
  • Amazon – it helps suggests products under the section – “Inspired by your shopping trends”
  • YouTube – It helps suggests videos under the section – “Recommended Videos”


What does a recommendation engine do?

With the ever evolving era of data explosion, it’s more relevant to scan through high quantity data. Recommendation System acts as a great tool for filtering and ensuring the consumer gets the recommendation according to his/her taste, style and preferences. The less time a customer spends searching for the right data on your website the more a customer stays at your website. A Good Recommendation Engine must be able to act in a very dynamic environment.


applications and examples of a recommendation system


Applications and Examples of a recommendation system in different industries


Streaming Media

The importance of AI-driven recommendation systems for streaming media is higher. OTT and VOD are winning millions of hearts in this modern era. Hence, leading OTT and VOD services are indulging recommendation systems to enhance the revenue cycle of their subscription-based business model.



e-commerce platforms use recommendation systems to suggest products that they would like to purchase to their customers. The products are suggested to the user based on the user’s behavior, interest, demographic, past buying behavior of the customer as a calculation for future buying.


News Platforms

Online news platforms also use recommendation systems to help users find the right and relevant content. The role of a recommendation engine in the News Industry is to reduce the information overload problem and suggest news items that might be of interest for the news readers. It studies user behavior and tries to suggest probable news that might help gain some insights to them.


Blogging Websites

Since the inception of the internet, articles and blogs have been there. It is safe to say that the biggest database of written text is probably on the internet. A good  recommendation engine helps users narrow down the large variety by presenting preferred options according to the user’s taste and search relevancy. It applies statistics and data science to offer solutions which most likely meet the expectations of the end user. The end user also tends to get to relevant content faster while researching as items related to the search keep showing up in the recommended tag.      


Audio Streaming Platforms

Music or audio recommendation systems have been the central to the operation of renowned audio streaming platforms in the marketplace. It helps users to find music that matches their preferences and suggests taking from the past listening events a playlist that they will like. 


Social Media Platforms  

While using your social media accounts, have you ever been suggested to add friends, follow someone or suggested people you may know? And adding to this, have you ever noticed that the reels, shorts or memes you consistently scroll through your social media accounts do match your taste or choice? This is what a recommendation engine does! It predicts your tendency and shows feeds on your social media wall as per your past behavior.


Boost User Engagement with Muvi’s AI-powered recommendation engine – Alie

Muvi’s AI-powered recommendation engine – Alie easily integrates with your websites and apps to provide real time recommendations to your end users and help boost a company’s sales by predicting the likes and dislikes of an end user. Its machine learning algorithms are designed to analyze user data and recommend personalized content based on their interest. Start a 14-days free trial to discover how it can engage users on your website by delivering them relevant contents.


applications and examples of a recommendation system

Written by: Ankit Jena

Ankit is Content Writer for Muvi’s Marketing unit. He is a passionate writer with 5+ Years of Experience in Content Creation And Development. In his past time, he likes to dance, play football and google various things to quench his thirst for knowledge.

Add your comment

Leave a Reply

Your email address will not be published.

Try Alie free for 14 days

No Credit Card Required

Upcoming Webinar
May 30

9:00AM PST

API Security in Video Streaming

While video streaming, we have to deal with a lot of data which is sensitive and confidential related mostly to users and content. In order to keep that…...

Event Language: English
30 Minutes