Why people recommend recommendation engines?
- Have you ever wondered that after uploading your picture with friends on Facebook, it automatically suggests you to tag them?
- Or while surfing Netflix if you have watched let’s say Batman, it suggests you watch Superman too?
- Or you are trying to buy a pair of jeans on Amazon of Levis, and they start telling you option about Pepe Jeans as “people who bought this, also bought this”.
It’s all possible because of Recommendation Engines.
So what is a Recommendation Engine?
A Recommendation Engine is an algorithm that analyzes user behavior to suggest items that are most relevant and accurate to the users. It discovers data patterns from a huge pool of customer information base i.e, data containing consumer choices. Different data analysis techniques are used to figure out the items which match a particular user’s taste and preference. The outcome is then generated, co-relating to the user’s need and interest.
In today’s data-centric world, users generate a huge pile of data and have access to different customer-centric services online. It is therefore important for companies, especially in the Retail and CPG sector, to get relevant user information to arrive at their preference and taste.
Most companies today work towards making better and robust recommendation engines, by studying the past behavior and data activity of the users. And the end goal? To provide a better recommendation, choices, personalized suggestions to buyers, and better product visibility. In a recently conducted online poll, 44% of consumers strongly agree with wanting a product on recommendations based on past purchases.
Just like the way we take advice from our friends and family before buying a shirt or say, a pair of shoes, recommendation Engines can provide personalized suggestion on your fingertips. A Recommendation Engine serves more purpose than just telling which product is good, but it also comes in handy in providing a recommendation regarding relevant jobs posting, new games, suggested videos, movies of interest, suggested users follow on Instagram, and many more.
If you like talking about numbers then here some example!
- The algorithms in Netflix make the company a $1 Billion a year company, by keeping viewers watching so that they don’t cancel their account subscription.
- Amazon, yet another billion dollar company, saw a rise of over $20 billion in 2017 after using recommendation engine.
- And more recently, the company which came in limelight because of the data theft, Facebook, uses a recommendation engine to match ads to user activity, which is in fact 80% of the company’s ad revenue in 2015.
Recommendation Engine is the new go-to-thing if you want to drive traffic, deliver relevant content and products to your customers, keep your user engaged and provide more compelling shopping experience and convert shoppers to customers. Recommendation engine does all that for you and enables you to have an engaging experience not only for the business but for customers as well.