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 eCommerce .
We have chosen, therefore, to open today's article of our blog, recalling this story.
According to a study published by McKinsey, up to 35% of Amazon sales are generated thanks to artificial intelligence algorithms that regulate product recommendations .
Jeff Wilke, director of the Consumer Division, comments on the role of this feature in the most famous eCommerce platform in the world:
“At Amazon.com, we use recommendation list of angola consumer email algorithms to personalize the online store for each customer.
The store changes radically based on customer interests, showing programming books to an engineer and baby toys to a new mom.”
Product Recommendation: But What If My Ecommerce Isn’t Amazon?
As you can easily imagine, in Amazon nothing is left to chance, but everything is governed by artificial intelligence and machine learning .
The engine that regulates dynamic product recommendations is made up of different parts that deal with the analysis of multiple data: in general, it selects the products to show to each user based on the purchases made, interactions and evaluations of items on display and combines the results with similar items viewed by users with similar interests.
Although there is only one Amazon and eCommerce platform with such a large budget to spend on research and development, dynamic product/content recommendation features can also be implemented on smaller eCommerce (and why not content sites), thanks to marketing automation solutions and platforms such as Blendee, with undoubted advantages:
