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

Importance of Quality Products over Quantity in a Recommendation Engine

kritika Published on : 31 May 2021


We all are aware of the fact that the Recommendation Engine has taken the world by storm. As customers, we are sometimes not even familiar with the recommendations/suggestions we get while using some website or mobile application. We cannot blame it because, more often than not, we are on a website, but we don’t know what we want to do there. Don’t believe it? Try to remember the last time you wanted to listen to songs but didn’t know which one to hear, so you opened the music application Spotify and decided which song to listen to based on the options available. 

So, it is safe to say that the recommendation engine has become a part of our lives knowingly or unknowingly. However, have you ever noticed that there is one song on Spotify that you love, but not many people do; it never pops up in any of the lists made by Spotify. Why? Because recommendation engines thrive on feedback from users. If a product does not have a considerable amount of input from the users, the chances are that it might go unnoticed even if the product is extraordinary. This is where the quality products over quantity debates come into play. 



How does a Recommendation Engine Work?


To debate on anything related to recommendation engines, it is vital to understand how it works. There are mainly three steps that come under it – 


Data Acquisition

As mentioned above, recommendation engines thrive on data. So, data acquisition is the first step in the process of recommending. It is a process of storing, filtering, and removing data that are not necessary. It can only be obtained when you allow your website to integrate with the recommendation engine or give your storage access. 


Data Analysis 

Once the data is acquired, the next step is to analyze it and shelf it in clusters. It is done through various methods involving machine learning. Some of the standard techniques are collaborative filtering and content-based filtering.


Also read : How does a Recommendation Engine use Predictive Analysis?



The last step is to identify the customer’s needs and then give recommendations to them. Any website owner who cares about his/her work must be curious to know which products are being recommended to which user. You can see all the activities of a recommendation engine like the image below if you use Alie.



Quality over Quantity Products in a Recommendation Engine


When a recommendation engine analyzes the data, it usually does so based on the inputs given by a user. What a user is browsing, their likes and dislikes, and what they purchase. When the recommendation engine follows item-based collaborative filtering, even then it has to deal with the products with some user feedback.

For products that are new or do not have any user activity makes it challenging for the recommendation engine to track it and then eventually suggest it to users. So, it is essential to have products/services that your target audience will enjoy. 


Wrapping Up


However, there is one easy way to tackle this problem. It is to employ a recommendation engine where you can add your own algorithm. You can do this on Alie – a recommendation engine platform. Try its 14-day free trial to know more about it.


Written by: kritika

Kritika Verma is an Associate Content Writer and works with Muvi Marketing Team. She is an inbound marketing professional and ensures high-quality traffic on the Muvi website through her blogs, articles, and more. She has an engineering background but always had a knack for writing. In her free time, she is either on Quora or on (Mostly losing).

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
June 27

9:00AM PST

Leveraging Analytics for Success in the Streaming Industry

A streaming platform’s success is crucially dependent on data. In today’s competitive streaming landscape, data is king. This webinar will unlock the secrets of using analytics to gain…...

Event Language: English
30 Minutes