Each recommendation is built from a type, which controls how products are selected, for example, best sellers or most viewed, and an optional filter, which narrows those results by criteria such as category, price, or gender.
If you're an ecommerce retailer, you can use product recommendations to add dynamic product content to your campaigns.
Before you start
Things you need to know:
You must connect your ecommerce store to your account. You can do this using one of our integrations or through our API.
Types of product recommendations
Depending on the Insight data you have synced to your account, you can use these recommendation types:
Type | Description |
Uses only the filters you define to select a single product set from your catalog, with no extra statistics being considered. | |
Calculates the best selling products in your catalog. | |
Calculates the most viewed products in your catalog. | |
Calculates trending products in your catalog by analysing data from best sellers and most viewed products. | |
Machine learning powered to predict and suggest optimal product sets based on your contacts' past purchase and browsing behaviour. | |
Machine learning powered to predict the next products in the customer journey by matching to similar shoppers. | |
Machine learning powered to predict the next products in the customer journey by combining similar shoppers and item affinities. | |
Shows the latest products added to your store. | |
Shows the most popular products that customers also bought alongside other products. | |
Shows the products your customers last browsed. | |
Shows the most popular pairs of products customers purchase at the same time. |
Use product recommendations
To access product recommendations, go to Content > Products > Recommendations.
Here, you can choose a type, and, depending on the type, add additional filters in the recommendation builder. Once you have created a product recommendation, it is available as a block inside your account’s EasyEditor.
Drag product recommendation blocks into your campaigns just like other building blocks. Once added, change its basic layout and preview it.
Product recommendation refresh intervals
Product recommendations can be refreshed both manually and automatically.
The Product recommendation list view and previews in the product recommendation builder must be refreshed manually.
In addition, we refresh your product recommendations automatically at the following intervals:
General and personalised recommendations: every one day
Machine learning recommendations: every seven days