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Einstein Engagement Score Filters in Data 360 Segments
Here are some examples of common Einstein Engagement Score use cases.
Find Most Engaged Individuals Who Made a Previous Purchase
Filter for individuals who made a purchase greater than $500 this year and who are most likely to click an email.
- Sales Order | Count | At Least | 1
- Grand Total Amount | Is Greater Than | 500
- AND
- Order Start Date | This Year
AND
- Einstein Email Engagement Score | Count | At Least | 1
- Email Click Likelihood | Is Equal To | Most Likely
Find Individuals with High Engagement and Low Conversion for a Specific Brand
Filter for individuals who have a high engagement rate but low conversion rate from brand BU 829302. High engagement means an email click predictive score of 0.2 or more.
Low conversion means a conversion likelihood of least likely and no purchases from the brand.
- Einstein Email Engagement Score | Count | At Least | 1
- Email Click Score | Is Greater Than | 0.2
- AND
- Conversion Likelihood | Is Equal To | Least Likely
- AND
- Internal Organization | Is Equal To | 829302
Find Highly Engaged Individuals with Large Purchase Sums
Filter for individuals with a high engagement rate who have made at least 5 purchases each over $500. High engagement means a mobile open predictive score of 0.8 or more and conversion likelihood of most likely for BU 20392.
- Einstein Push Engagement Score | Count | At Least | 1
- Direct Open Score | Is Greater Than | 0.8
- AND
- Conversion Likelihood | Is Equal To | Most Likely
- AND Internal Organization | Is Equal To | 20392
- Sales Order | Count | At Least | 5
- Grand Total Amount | Is Greater Than | 500
