Lead Scoring
Lead scoring is a method of ranking leads by assigning points for how well they fit the ideal customer profile and how they engage, so sales can work the most promising leads first.
Also called: lead score, lead grading
Why it matters
Most models have two parts. Fit scoring rates who the lead is: title, seniority, company size, industry and region. Engagement scoring rates what the lead does: email clicks, website visits, demo requests and event attendance. Negative points for signals such as student emails or competitor domains, and decay for old activity, keep scores from creeping upward forever.
Scores trigger actions, such as routing a lead to a rep, marking it as an MQL or enrolling it in a nurture track. Rules-based scoring is simple to explain, while predictive scoring uses a model trained on past closed deals. Either way, the score needs regular review against real outcomes, because a score that does not predict which leads close only adds noise.
Example
A software company gives 25 points for a director title or higher, 20 points for a company with 100 to 1,000 employees, 15 points for a pricing page visit and 30 points for a demo request. It subtracts 20 points for a personal email address. A director at a 300 person company who visits the pricing page scores 60 and enters a nurture sequence.
Questions people ask
How is lead score calculated?
Points are assigned for fit, such as company size, industry and job title, and for engagement, such as page visits, email replies and content downloads, sometimes with points removed for negative signals or inactivity. Many teams keep fit and engagement as separate scores rather than one blended number.
Why is lead scoring important?
It tells sales which leads to work first, keeps poor-fit leads from taking up time, and gives marketing and sales a shared, written definition of when a lead is ready to hand over.
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