Einstein Predictive Lead Scoring uses a combination of data science and machine learning to discover the patterns of lead conversion in your business, and predict which leads to prioritize. By using machine learning, Predictive Lead Scoring provides a simpler, faster, and more accurate solution than traditional rules-based lead-scoring approaches.
The lead score field is available in list views in Salesforce Classic. In Lightning Experience, the lead score field is available in list views, reports, dashboards, and lead detail pages. On detail pages in Lightning Experience, the lead score appears in the Einstein component. The component also shows sales reps which lead fields have the greatest positive (1) or negative (2) influence on its score. Fields that aren’t listed in the Einstein component still influence the score, but less than the fields listed. The Einstein component also lets reps send an email to the lead and, if you have Lightning Voice set up, call the lead.
When you or your users add the Score field to list views, hovering over a score (1) displays the insights (2) behind the score. When sales reps focus on leads with higher scores, they’re likely to convert more of them to opportunities. The lock (3) indicates that the score is read-only.
Predictive Lead Scoring periodically reanalyzes your historical leads and updates the scores for your current leads accordingly.
- Average Lead Score by Lead Source
- Conversion Rate by Lead Score
- Lead Score Distribution: Converted and Lost Opportunities
To assign leads to sales reps based on lead score, create APEX lead assignment rules using lead score as a criteria.
In Salesforce Classic, the Score field is available in lead list views and page layouts. To set up Predictive Lead Scoring, enter Lead Insights in the Quick Find box and then select Lead Insights.