Interaction Studio Classic Only
- This use case is intended for customers using Interaction Studio (formerly Evergage Classic) ONLY. For customers using the Interaction Studio 'Campaigns and Templates' application, refer to the Use Case Library instead.
- The Visual Editor Chrome Extension will no longer be available starting January 1, 2023. For more information, see this knowledge article.
Leverage truly 1:1 personalized recommendations on your homepage, but don’t limit product discovery to one row of five products. Instead, leveraging machine learning provides an opportunity to create more granular recommendations based on the individual and their affinities.
Example
You can incorporate multiple recommendations campaigns throughout your site; each utilizing a different algorithm to maximize the chances that visitors will convert.
For example, you can show trending items, boosting the visitor’s category affinity in one campaign, and in another campaign use collaborative filtering to boost brand affinity.
Segment
No segments are needed to execute this play as it relies on Einstein Recipes and machine learning algorithms to suggest categories and brands.
Measure
With Recommend on your homepage, you can measure success by an increase in the clickthrough rate.
Setup
Process
Here is a checklist of what you need to do in Interaction Studio to create this play on your own site:
- Create a Recommendations campaign
- Add ingredients, exclusions, and boosters
- Train and publish your recipe
- Create an Interaction Studio campaign and add the recipe in Message Settings
Reference Materials
The following articles from the Interaction Studio Knowledge Base will provide process steps to help you execute this play:
Overview
Content Tools