What are the different pages of an e-commerce store?

Product recommendation as part of personalization

 

This unit will cover the different tactics that e-commerce stores have to set up on personalizing the different customer journey touchpoints on the key sub pages.

 

When breaking down the e-shopping experience to different pages we usually highlight the personalized product recommendations that could carry a huge added value, as long as we take the effort and apply different strategies on each sub pages of the store.

A mature recommendation engine - regarding the quantity and profoundness of available customer history -  vary at each page, deciding whether non-personalized or personalized offers convert better in the given moment and presentation layer.


Homepage


Returning visitors who already browsed or made basket events or purchases, are the perfect subjects to receive real time personalized recommendations or personalized offers:

 

 

Home Page recommendations: Typical personalized offers are the highlighted abandoned basket goods or alternatives to the abandoned goods:


Frequently used Home Page Recommendations tactics include:


Recently bought products’ cross-sells

Recently viewed products

Products in the same categories the customer has recently purchased from (or viewed)

Most popular (based on product view and purchase) and trending products

New arrivals / Products on sale

 

Category page and “listed products”- pages


After the home page the customer journey takes can typically continue on category pages, or by searching for specific terms a group of products will appear by the user’s search criteria.


For returning visitors there are ample capacities to provide personalized experience on the category page:


In visual appearance 2 types of tactics can be used here:


1. Recommendation widgets + products are presented separately from the category product list.

2. Recommendations appear within the re-ordered product list. No standalone widgets.


The importance of the second tactic: you can empower the listed products - container by reordering the thumbnail images of the products - based on what you already know about the given user.

Example: If a user is heavily interested in red T-shirts, but she is listing the shorts and breeches now, the personalized category page will present more red items to her than to other users. It does not mean that the red products will suppress the others, but the most relevant product appearing first and in the top rows must be red.

 

 

 

When your customer visits via mobile this ‘container-less’,  re-optimized category page - strategy can work with high conversion. This appearance is very often the only viable solution, because the limited mobile surface leaves no room for standalone recommendation widgets.

 

In both strategies you can use the following user preferences and user events:

 

  • preferred colors, brands, styles etc.,
  • the user’s abandoned products in that or in the adjoining categories,
  • recently viewed products,
  • complementary products for already bought or visited products
  • products from frequently viewed together categories

 

Product page

 

 

It’s important to define our goal here:  would we like our customers to change their minds? With using the collaborative filtering strategy we can offer alternatives to the currently viewed product.

 

 

Strategies of personalized product recommendations also could be, in solo or mixed with each other:

 

  • Recently viewed products
  • Most recently viewed products from the same category,
  • Associated products following the user’s taste,
  • Products that other customers also viewed
  • Complementary goods from other categories,
  • Frequently viewed & bought together products,
  • Products linked to the user’s past browsing experiences and purchases.


Cart page

 

With cart page recommendations we have to help the customers to complete their purchase frictionlessly, and we must not distract them with products unrelated to those that are already in the cart.

 

Continue reading?

Share this article

asds