--- schema_version: "1" id: 49d922379030c59549ecb5b8dc7b47f3905ceaa41af9ebbecb281cd6ddde91c3 title: Einstein Lead Scoring collection: admin version: current locale: en-us portal_url: https://docs.salesforce.com/admin/current/en-us/ai/264-0-0/einstein_sales_lead_insights.md canonical_url: https://help.salesforce.com/s/articleView?id=ai.einstein_sales_lead_insights.htm&release=264.0.0&type=5 source_site: help.salesforce.com content_type: documentation content_hash: e351bd792a2d2010aac88473f67a10ccacb2408e1f7ac8f58357093e5d7ad094 description: Use AI to score your leads by how well they fit your company’s successful conversion patterns. Let your sales team prioritize their leads by lead score. See which fields influence each lead score most. products: - Sales - Cross Cloud release: "264" --- # Einstein Lead Scoring Use AI to score your leads by how well they fit your company’s successful conversion patterns. Let your sales team prioritize their leads by lead score. See which fields influence each lead score most. ### Required Editions
Available in: Lightning Experience and Salesforce Classic
Available with Sales Cloud Einstein, which is available in Performance and Unlimited Editions, and available for an extra cost in Enterprise Edition
Einstein Lead Scoring uses data science and machine learning to discover your business’s patterns of lead conversion. Based on your patterns, Einstein predicts which of your current leads to prioritize. By using machine learning, Einstein Lead Scoring provides a simpler, faster, and more accurate solution than traditional rules-based lead scoring approaches. Einstein analyzes your past leads to determine which current leads have the most in common with leads that have previously converted. By default, Einstein scores your leads using most lead fields. If your admin is certain a field doesn’t affect lead quality, they can tell Einstein not to include the field. Einstein also creates internal categories for certain lead text fields that can contain different values with similar meaning. For example, different businesses sometimes use different job titles for the same job. Using the lead title, Einstein associates each lead with a Job Rank and a Department. If a lead’s title is CEO, Einstein assigns it the C-level job rank. By associating leads with a smaller list of job ranks and departments, Einstein can find patterns in your data more easily. Based on its data analysis, Einstein creates a predictive model for your organization. Einstein reanalyzes your lead data every 10 days and refreshes your scores. So if new trends emerge, Einstein won’t miss them. When you score all leads together without creating segments, and you don’t have enough lead conversion data to build your own predictive model, Einstein uses a global model. The global model uses anonymous data from many Salesforce customers. When you accumulate enough lead data, Einstein builds a scoring model with your data and uses the model with the better results. Einstein Lead Scoring adds a Lead Score field to leads. The Lead Score lets sales reps prioritize their work by ranking leads according to their similarities to prior converted leads. Leads with higher scores have more in common with leads that have converted in the past. The lead score appears in the Einstein Score component on lead detail pages. The component also shows sales reps which of the lead’s fields had the greatest influence on its score (1). Depending on the lead, fields with positive or negative influences can appear. Fields that aren’t listed in the Einstein Score component still influence the score, but less than the fields listed. ![The Einstein Component on a lead detail page.](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-ai-einstein_sales-264-0-0-production-enus/13c193d3-11a5-49f2-8dbf-542c62890274/einstein_sales/images/lead_detail_einstein_component.png) When you or your users add the Einstein Score field to list views, hovering over a score (1) displays the top factors (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. ![The Lead Insights hover on a lead list view.](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-ai-einstein_sales-264-0-0-production-enus/13c193d3-11a5-49f2-8dbf-542c62890274/einstein_sales/images/lead_insights_hover.png) Einstein Lead Scoring includes a dashboard with reports that show key lead score metrics for your org. - Average Lead Score by Lead Source - Conversion Rate by Lead Score - Lead Score Distribution: Converted and Lost Opportunities #### See Also - [Enable Einstein Lead Scoring](https://help.salesforce.com/s/articleView?id=ai.einstein_sales_setup_enable_lead_insights.htm&release=264.0.0&type=5 "Give your sales team access to scores that help them prioritize leads. Turn on Einstein Lead Scoring, and then select a lead conversion milestone to use, which leads to score, and which lead fields to consider during scoring.") - [Considerations for Setting Up Einstein Lead Scoring](https://help.salesforce.com/s/articleView?id=ai.einstein_sales_els_setup_considerations.htm&release=264.0.0&type=5 "Before you set up Einstein Lead Scoring, consider these requirements and limitations.") - [Understand How Einstein Scores Your Leads](https://help.salesforce.com/s/articleView?id=ai.einstein_sales_els_how_it_works.htm&release=264.0.0&type=5 "Learn about the process Einstein uses to determine which of your leads to prioritize.")