Personalized Email Recommendations

This app shows how to leverage Algolia Personalization to display product recommendations in emails

About

This sample app shows how to leverage Algolia Search and Algolia Recommend to display product recommendations in emails. Showing recommendations is a great way to engage your customers at various stages of their journey before and after visiting your site.

This sample app comes with the following recommendation models:

A customer browsed a category: recommend best rated products from that category. This recommendation model uses Algolia's Faceting feature.
A customer just bought a product: recommend products that are frequently bought together. This recommendation model uses Algolia Recommend to train a machine-learning algorithm based on which products users often buy together.
A customer just bought a product: recommend related products. This model also leverages Algolia Recommend to train a machine-learning algorithm to find products that are similar.
A customer has an existing user profile: recommend products that match their affinities. This model uses Algolia Recommend and Personalization.

This sample app comes with the following features:

A rock-solid base email template with Cerberus
A rich and powerful templating language with Nunjucks
Three different email templates for different moments of the customer's journey (pre-order, post-order, re-engagement)
Four different models for recommended products with Algolia Recommend and faceting