Answer honestly, if you are a customer, wouldn’t you enjoy your experience on a website to be exclusive to only you? A website that understands your wants and needs and recommends your product based on this information. If you can still not comprehend what we are trying to say, then think about Netflix or Amazon. Every time you open your Netflix homepage, you can see the recommendations being made to you are different from that of your friends and family. Let us make it easier for you to understand. There are four people who can access a Netflix account; now, if you visit all these four profiles (provided four different people are using this account who have different tastes), then you can see the difference in recommendations. This is an example of personalized recommendations.
What are Personalized Recommendations?
Personalized Recommendations are based on a user’s past behavior. What do these users browse, like, leave comments on, and even how much time they spend on a product; all of these are noted by a recommendation system, and then by using algorithms, personalized recommendations are given to the user.
For example, Jenny watched Avengers last night. Today, when she logged in on the same website, her homepage was filled with Marvel movies.
In this case, the recommendation system noticed that Jenny likes to watch superhero movies, and based on the trends and tags associated with it, and the recommendation system recommended Marvel Movies to Jenny.
What is the Difference between Personalization and Recommendations?
As mentioned above, with personalization, the recommendation system takes notice of what users want, their past behavior and also takes into consideration what other people with similar tastes like.
On the other hand, recommendations are nothing but suggesting products without taking into consideration what a user may like.
So basically, personalization engine means taking into consideration what a user may like, while recommendations mean merely suggesting products or services without any considerations.
Example of Personalization – The list that you can see on Amazon is‘ Products similar to your last buy’.
Example of Recommendations – The list that you can see on Amazon is‘ Most buy Products’.
Conclusion
It is a well-known fact that any user will enjoy a homepage that is personalized to them. There are mainly two ways of giving personalized recommendations to customers: by building a recommendation engine or buying a recommendation engine. Read this blog: Build Vs. Buy – AI-based recommendation engine to understand what your organization needs.
Explore Alie – an AI-based recommendation engine that can help you in creating personalized homepages for your customers. Try its 14-day free trial without paying anything. Note – No credit card required.
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