Predictive Scoring & Analytics Beginner

Einstein Engagement Scoring predicts how likely each subscriber is to engage with your emails. By scoring subscribers on open and click likelihood, marketers can target the most receptive audiences, suppress unengaged contacts, and optimize send frequency for each individual.

Einstein Engagement Scores

Score TypeWhat It PredictsHow to Use It
Open LikelihoodProbability a subscriber will open the next emailPrioritize sends to high-open-likelihood subscribers
Click LikelihoodProbability a subscriber will click in the next emailTarget engaged audiences for conversion-focused campaigns
Unsubscribe LikelihoodRisk of unsubscribe on next sendReduce frequency or improve content for at-risk subscribers
Web ConversionLikelihood of converting after email engagementFocus high-value offers on high-conversion subscribers

Using Engagement Scores in Campaigns

  1. Segment by Score

    Create data extensions or filters based on engagement scores. For example, target only subscribers with high open and click likelihood for important campaigns.

  2. Personalize Frequency

    Send more frequently to highly engaged subscribers and reduce frequency for those with lower scores to prevent fatigue and unsubscribes.

  3. Optimize Suppression

    Suppress very low-scoring subscribers from sends to improve deliverability metrics and reduce costs without losing future re-engagement potential.

  4. Power Journey Decisions

    Use Einstein scores as decision criteria in Journey Builder to route subscribers through different paths based on predicted engagement.

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Score interpretation: Engagement scores are relative within your subscriber base. A "high" score means the subscriber is more likely to engage than most of your other subscribers. Actual open and click rates still depend on content quality and relevance.

Einstein Analytics for Marketing

Beyond individual scoring, Einstein provides aggregate analytics that help identify trends, anomalies, and opportunities across your marketing programs. Key analytics features include campaign performance anomaly detection, engagement trend analysis, and audience composition insights.

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Test the value: Send your next campaign to two groups: one using your normal targeting and another filtered to only high-engagement-score subscribers. Compare open rates, click rates, and conversions to quantify the value of Einstein scoring.
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