Glossary
Lead scoring
Lead scoring assigns each lead a number based on how well they fit your ideal customer profile and how much interest they show, such as email replies or pricing page visits, so sales works the most promising leads first.
What Is Lead Scoring?
In short Most models combine two kinds of points.
Fit points come from who the lead is: title, company size, industry, location. Engagement points come from what they did: clicked an email, replied, visited the pricing page, booked a meeting. Points can be negative too, for a competitor's domain or 90 days without activity. HubSpot's tool, for example, keeps separate fit and engagement scores and combines them into labels from A1 to C3.
When a lead crosses a threshold, it goes to sales, often as a marketing qualified lead. There is no standard number. Adobe's Marketo guide suggests starting at 100 and setting the bar high enough that a person has to engage several times, since one email open is unlikely to qualify anyone.
Lead Scoring Example
Lead score = fit points + engagement points - negative pointsExample: a team gives +20 for a VP or director title, +15 for 100 to 1,000 employees, +10 for a US location, +25 for a reply, +15 for a pricing page visit and -30 for a competitor's domain. A director at a 300-person US company who replied scores 70 and passes the 60-point threshold for a sales call.
Lead Scoring in Practice
Rule-based scores are easy to explain and easy to get wrong, because teams guess the weights and never check them. Predictive scoring trains a model on past leads that did and did not convert. For outbound, the useful version is simple: score accounts on fit before you contact them, and treat a reply as the engagement signal that counts.
FAQ
What is lead scoring?
Giving each lead a number based on fit and engagement so sales knows who to contact first. Leads above a set threshold go to sales, and the rest stay with marketing or wait for more activity.
What is the difference between explicit and implicit lead scoring?
Explicit scoring uses information provided by or about the lead, such as job title or company size. Implicit scoring uses behavior, such as email clicks, page visits and downloads. Salesforce calls the explicit part grading and the implicit part scoring.
What lead score makes an MQL?
There is no standard. Adobe suggests starting with a threshold of 100 in Marketo before a lead goes to sales. Pick a number that takes several actions to reach, then adjust it by checking which scored leads became deals.
What is predictive lead scoring?
Scoring set by a machine learning model trained on your past leads that did and did not convert, instead of points you assign by hand. It needs history: HubSpot's AI scoring asks for at least 25 converted and 25 non-converted contacts.
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Related
- GTM Glossary
Every GTM term, grouped by topic.
- Ideal customer profile (ICP)
- Lead qualification
- Intent data
- Lead generation
- BANT
- Sales pipeline
- Ken MCP server
Sources
| Source | Checked |
|---|---|
| HubSpot Knowledge Base: Overview of the lead scoring tool | |
| Salesforce Trailhead: Lead grading essentials | |
| Adobe Experience League: Build person scoring models for Marketo Engage |
Changelog
- Page published.