When a new song is released by Zayn Malik or The Weekend, the whole world knows about it. However, when someone relatively new in the industry releases their music, it might even go unnoticed. This is because people didn’t get a chance to ‘discover’ this new song. This is precisely what happens when a new product is added to your e-commerce website. However good the product might be, your customers won’t buy it because they wouldn’t get a chance to look at it.
Now, the question is what to do in such a situation? The answer is relatively more straightforward: adopt a recommendation engine for your e-commerce website.
A recommendation engine is a filtering system that analyzes the behavior of customers and recommends the most appropriate products based on the algorithms that are taught to it.
As mentioned above, the recommendation engine analyzes the preferences of a user on the website and recommends products accordingly. To know more about the algorithms or filtering used in recommendation engines, read: What is an AI-based recommendation engine?
Steps that a recommendation engine follows that helps in product discovery –
Recommendation Engine analyzes a user’s activity on the website. Which product are they browsing, and for how long? Which product are they clicking on next? This helps in knowing customers’ likes and dislikes and their preferences.
Until and unless the recommendation engine knows the features of a product, it is hard for it to recommend the product to anyone. This is why when a new product is added, if the correct algorithm is used, then the recommendation engine fills it and clusters the product.
Once the recommendation engine has the data of customers and products, all it has to do is recommend the product.
To know more about how AI-based recommendation systems help in product discovery, try the 14-day free trial of Alie. You will get to explore its features and also see how you can track everything on a dashboard.
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 chess.com (Mostly losing).
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