Interpret and use predictive scores
The predictive score appears on the lead record and in lead views and grids, giving sellers visibility across their entire pipeline. Each score displays the numerical value, the grade, and lists of positive and negative influencing factors.
Positive factors show what’s driving the score up—for example, the lead works in a target industry or has engaged with multiple marketing emails. Negative factors reveal what’s pulling the score down, such as a lead source that historically converts poorly or a company size outside your typical customer profile.
Sellers use the grade to triage their queue efficiently. Grade A leads demand immediate attention—these represent the highest conversion probability and should be the first contacts each day. Grade B leads show strong potential and warrant scheduled follow-up soon. Grade C leads benefit from periodic review or automated nurturing campaigns. Grade D leads often indicate poor fit and may be candidates for disqualification or reassignment to marketing for longer-term nurturing.
The score is informational, not prescriptive. Sellers retain full judgment and can apply their experience alongside the AI recommendation. A rep who has built rapport with a Grade C lead can continue that relationship. Conversely, contextual factors might lead a seller to deprioritize a Grade A lead that doesn’t align with current territory focus.
As leads progress through the pipeline, their scores update automatically. A lead that initially scored low might jump to Grade A after attending a webinar and downloading a white paper. This dynamic scoring keeps sellers focused on leads with current buying signals rather than static data.
Predictive scoring provides the initial triage signal that helps sellers decide which leads warrant immediate personal attention. In the next unit, you explore how Copilot in Dynamics 365 Sales generates email content and meeting summaries to accelerate outreach to those prioritized leads.