---
schema_version: "1"
id: e4f63eb760820dab4ebf3f3df465522d8ff84c4bda064c86f6db1a9c33c3f201
title: Integration with Audience Builder
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/mktg/264-0-0/mc_pb_integration_with_audience_builder.md
canonical_url: https://help.salesforce.com/s/articleView?id=mktg.mc_pb_integration_with_audience_builder.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: fde50b1a3b629ab410b05dba34b1ec2d11fa73ff701f32378c33696210347da7
description: Learn how the data from Einstein Recommendations integrates with Audience Builder. You can use this data to filter and segment subscribers.
products:
  - Marketing
  - Marketing Cloud Intelligence
release: "264"
---
# Integration with Audience Builder

Learn how the data from Einstein Recommendations integrates with Audience Builder. You can use this data to filter and segment subscribers.

The Einstein Recommendations integration with Audience Builder provides a set of standard ecommerce dimensions based on these data points:

- Products Purchased
- Products Browsed
- Search Term
- Visits and User Affinity

Each dimension provides filter categories used to segment an audience that you can export into Email Studio for targeted campaigns. These filter categories are included.

   
| Products Purchased | Products Browsed | Search Term | Visits and User Affinity |
| --- | --- | --- | --- |
| Product Name (LTD) | Browse Event Count (LTD) | Search Browse Event Count | Days Since Last Visit |
| Product Name (30, 60, 90 days) | Name | Term | Average Days between Visits |
| Purchased Date | SKU | Date | Average Time on Site |
| Purchased Days (date range) | Date | Days | Behavioral User Affinity |
| Product SKU | Days |   |   |
| Product SKU (30, 60, 90 days) | Attribute |   |   |
| Attribute |   |   |   |
| Days Since Last Purchase |   |   |   |
| Average Order Value |   |   |   |
| Average Days Between Purchases |   |   |   |