Product Recommendation for Fashion E-Commerce: Yes, But Which Ones?
Posted: Thu Feb 13, 2025 4:55 am
We have a good understanding of the effectiveness of product recommendations and their value as part of an effective fashion e-commerce marketing automation strategy , but during the implementation phase, we need to carefully evaluate which ones to use and how.
There are indeed different types of product recommendations that vary depending on the type of algorithm they use.
Let’s take a look at the main ones:
Trending recommendation : the most popular products in the catalog are displayed gansu mobile number database by click and view;
Personalized recommendation : the user has the possibility to see the products selected based on his recent browsing history on the site;
Personalized trending recommendation : in this case, the algorithm suggests products by mixing the previous two, that is, suggesting products based on the user's browsing history but more popular in terms of clicks and views;
Browsing history recommendation : in this case, products are displayed starting with those the user has viewed;
Personalized recommendation by sales : the algorithm allows you to display product suggestions based on those that the user has recently purchased;
Cart recommendation : with this typology, recommended products are displayed based on those that the user has placed in the cart;
Remarketing recommendation : Products that the user has viewed in the last few days but has not purchased are displayed.
These are just the main types: they can be customized and the displayed products filtered, depending on the segment the user belongs to (eg: spending thresholds, preferred categories, reach size).
There are indeed different types of product recommendations that vary depending on the type of algorithm they use.
Let’s take a look at the main ones:
Trending recommendation : the most popular products in the catalog are displayed gansu mobile number database by click and view;
Personalized recommendation : the user has the possibility to see the products selected based on his recent browsing history on the site;
Personalized trending recommendation : in this case, the algorithm suggests products by mixing the previous two, that is, suggesting products based on the user's browsing history but more popular in terms of clicks and views;
Browsing history recommendation : in this case, products are displayed starting with those the user has viewed;
Personalized recommendation by sales : the algorithm allows you to display product suggestions based on those that the user has recently purchased;
Cart recommendation : with this typology, recommended products are displayed based on those that the user has placed in the cart;
Remarketing recommendation : Products that the user has viewed in the last few days but has not purchased are displayed.
These are just the main types: they can be customized and the displayed products filtered, depending on the segment the user belongs to (eg: spending thresholds, preferred categories, reach size).