Considerations for Setting Up Opportunity Score
Review important considerations before setting up Opportunity Scoring.
Required Editions
| Available in: Lightning Experience in Performance and Unlimited editions with Sales Cloud. In Enterprise Edition with Sales Cloud, this feature requires the Agentforce or Revenue Intelligence add-on. |
General Considerations
- Enable Data 360 in your org before you turn on this feature.
- You can't use Einstein Opportunity Scoring and Opportunity Score at the same time.
- When you turn on Opportunity Score, the system automatically disables Einstein Opportunity Scoring.
- Users with access to Pipeline Inspection or Pipeline Forecasting can view scores without needing new user permissions.
- If you clone the model and create multiple versions, all scores write back to the same opportunity object. The system simply gets the latest score.
- Turning off Opportunity Score removes the score column from list pages and the score component from opportunity record pages. Scoring-framework assets created for this feature are deleted. Data Cloud assets aren’t deleted, previously calculated scores aren’t deleted, and data streams aren’t removed.
Data Considerations
- Opportunity data and historical opportunity data are mandatory data sources for the model.
- Train the model only after you have at least 200 closed-won and 200 closed-lost opportunities. Training can start with any volume, but if volume is below the minimum, training fails, the model stays inactive, and related assets are deleted. You’ll need enough data and must restart the setup to try again.
- When a new opportunity has minimal information, the model relies on patterns learned during training to generate a score.
Credit Usage
- Transforms used for training consume Data 360 credits.
- Generating scores also consumes Data 360 credits, about 3,500 credits per 1 million opportunities.
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