Einstein Opportunity Scoring
An AI feature in Sales Cloud that assigns a score (1-99) to each opportunity based on its likelihood to close, analyzing factors like activity history, stage duration, and related data.
Definition
An AI feature in Sales Cloud that assigns a score (1-99) to each opportunity based on its likelihood to close, analyzing factors like activity history, stage duration, and related data.
In plain English
“Einstein Opportunity Scoring assigns each opportunity a score from 1 to 99 predicting how likely it is to close. Reps and managers see the scores on opportunity records and can focus on the deals most likely to close.”
Worked example
Cottonbridge Software's Sales Cloud assigns every Opportunity an Einstein Opportunity Score from 1-99 - based on factors like activity history, stage duration, related Contact engagement, and historical patterns from closed deals. Reps see the score on every Opportunity record; the team's dashboards rank pipeline by score. The 12% of Opportunities scoring 80+ close at 5x the rate of unscored opportunities, focusing rep effort on the highest-likelihood deals. Einstein Opportunity Scoring is what turns the same pipeline into prioritized work without subjective triage.
Why Einstein Opportunity Scoring matters
Einstein Opportunity Scoring is a Sales Cloud AI feature that assigns a score (1-99) to each opportunity based on its likelihood to close. The model analyzes factors like activity history, stage duration, deal size, related contacts, and other signals from historical opportunities, learning which patterns correlate with wins. The score appears on Opportunity records and in reports, giving sales teams a quick signal of which deals are most promising.
Opportunity Scoring complements Lead Scoring (for top-of-funnel) and Deal Insights (for explanations). Together, they form a complete AI-driven view of the sales pipeline. Opportunity scores are most useful when combined with stage duration and activity patterns: a high-scoring opportunity that's been stuck in stage for weeks may need a different intervention than a high-scoring opportunity that's progressing normally. Sales managers use scores in pipeline reviews to focus discussion on the deals most likely to win and the deals that need rescue.
How to set up Einstein Opportunity Scoring
Einstein Opportunity Scoring assigns each Opportunity a 1-99 score based on likelihood to close — analyzes activity history, stage duration, related data, deal velocity. Helps sales managers focus pipeline reviews on at-risk deals and gives reps a sanity check on their own forecast confidence. Paid Einstein for Sales feature.
- Confirm Einstein for Sales licensing
Setup → Einstein Setup. Opportunity Scoring is part of Einstein for Sales.
- Open Setup → Einstein Opportunity Scoring
Setup gear → Quick Find: Einstein Opportunity → Einstein Opportunity Scoring.
- Tick Enable Einstein Opportunity Scoring
Foundational toggle. Activates training.
- Wait for initial training
Same multi-hour first-time training as Lead Scoring.
- Add the Einstein Opportunity Scoring component to Opportunity layouts
Lightning App Builder → drop the component. Reps see the score inline.
- Build pipeline reviews around the score
Sort Opp list views by Einstein Score; surface low-scoring high-Amount deals for manager review.
- Monitor model accuracy
Setup → Einstein Opportunity Scoring → Model Card. Track accuracy over time and watch for drift.
Default: all closed Opps. Restrict to specific record types / time windows.
Inline display of score.
Weekly default.
- Score doesn't replace human judgment. A high score on a deal that's actually dead still shows high — Einstein doesn't know about the customer's surprise budget freeze. Use as a signal, not gospel.
- Manager-led pipeline reviews are where Opportunity Scoring shines. Without integration into your pipeline review process, scores are just numbers nobody acts on.
- Score updates lag activity. New activity logged today doesn't update score immediately — score recalc runs on a schedule. Don't expect real-time score changes from new activity.
How organizations use Einstein Opportunity Scoring
Uses Opportunity Scoring as a key signal in their weekly pipeline reviews. Managers focus on high-scoring deals at risk of slipping and low-scoring deals that need re-qualification.
Built dashboards comparing Opportunity Scores against actual win rates to verify model accuracy and identify segments where the model needs retraining.
Trains reps to read both the score and the underlying activity patterns. A high score with low recent activity is a warning sign worth addressing proactively.
Test your knowledge
Q1. What range does Einstein Opportunity Scoring use?
Q2. What does the model analyze?
Q3. How does Opportunity Scoring complement other Einstein sales features?
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