It was in 1994 that Jeff Bezos left a secure job at a hedge fund and, in the basement of his rented house, founded Amazon.
>In its first month, the eCommerce company was selling books in every state in the United States and in over 45 different countries around the world, generating a net profit of $20,000 per week, the rest is history.
Behind Amazon’s success, in addition to the revolutionary business model, there is a constant improvement of the platform and the continuous search for innovative solutions.
>Among these, we cannot forget the product recommendation engine , the “engine” of dynamic product recommendations that made Amazon successful and revolutionized the entire world of e-commerce .
So we chose to open macedonia phone number data today’s blog post by remembering this story.
>Jeff Wilke, Director of the Consumer Division, comments on the role of this functionality in the world’s most famous e-commerce platform:
“At Amazon.com, we use recommendation the higher the ranking, the more likely it is to be seen by more people, generating more traffic. algorithms to personalize the online store for each customer.
>The store changes dramatically based on customer interests, presenting programming books to an engineer and baby toys to a new mother.”
Product Recommendation : But What If My E-Commerce Isn’t Amazon?
As you can easily guess, at Amazon nothing is bf leads left to chance. But everything is governed by artificial intelligence and machine learning.
- increase in sales;
- improve users’ shopping and browsing experience;
- increased customer loyalty;
- Customer loyalty .
Product recommendation with Blendee: how to do it?
This is why the use of dynamic product recommendations becomes essential. Not only to make the products in your catalog known to users but. Also to show them at the most appropriate time.
