---
schema_version: "1"
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title: Einstein Engagement Scoring Personas
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version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/mktg/264-0-0/mc_anb_einstein_engagement_scoring_personas.md
canonical_url: https://help.salesforce.com/s/articleView?id=mktg.mc_anb_einstein_engagement_scoring_personas.htm&release=264.0.0&type=5
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content_type: documentation
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description: The Einstein Engagement Scoring heatmap groups subscribers into a customer persona based on predicted email engagement.
products:
  - Marketing
  - Marketing Cloud Intelligence
release: "264"
---
# Einstein Engagement Scoring Personas

The Einstein Engagement Scoring heatmap groups subscribers into a customer persona based on predicted email engagement.

- Loyalists: Subscribers with high engagement scores.
- Window Shoppers and Selective Subscribers: Subscribers with mid-range engagement scores.
- Winback/Dormant: Subscribers with low engagement scores.

Use personas to refine customer engagement campaigns and journeys. To show subscriber Persona predicted behavior changes over time, click **Time Comparison in Predicted Email Engagement**. Time comparisons are updated weekly.

Einstein Engagement Scoring still considers opens, but they’re weighted lower than clicks by Einstein’s AI models. Open data is important to determine who, for example, is a window shopper versus a selective subscriber, or what differentiates a loyalist from a selective subscriber.

![Note](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-mktg-mc_data_management_and_analytics-264-0-0-production-enus/7988f60d-cd94-4b42-8836-dc11773564b5/images/icon_note.png)

Note Some email client providers’ security updates can result in an email open without user engagement. See the [Einstein Updates for Email Client Privacy Changes](https://help.salesforce.com/s/articleView?id=mktg.mc_anb_mpp_overview.htm&release=264.0.0&type=5 "Some email client providers have privacy methods that impact open rate metrics and calculations. Einstein Metrics Guard provides more accurate predictions by discerning real opens from bot opens.") document for more information.