What is lead scoring? Definition and examples
On this page
Lead scoring gives each potential buyer a number based on who they are and what they have done, so sales and marketing know whom to contact first.
How it works
Most scoring models add up two kinds of points.
- Fit: how closely the person or company matches your ideal customer. Job title, company size, industry and country are typical inputs.
- Engagement: what they have done. Visiting the pricing page, opening emails, attending a webinar or asking a detailed question all count.
Points can also be subtracted: a student email domain, a competitor's company or a careers-page visit often lowers a score. When the total crosses a threshold, the lead is passed to sales or moved to a new stage.
HubSpot's scoring tool is a common example of how this works in a CRMA CRM (customer relationship management system) is software that keeps one record per contact, company and deal, with the history of every interaction, so a team can see where each relationship stands.. It offers fit, engagement and combined scores, labels fit and engagement as High, Medium or Low, and labels combined scores from A1 to C3, where the letter is fit and the number is engagement. Points can decay over time, at intervals of 1, 3, 6 or 12 months, so an old webinar visit stops counting as interest today. Its AI scoring needs a sample of at least 50 contacts, 25 converted and 25 not, before it can learn a score (HubSpot).
Scoring is not the same as lead qualificationLead qualification is deciding whether a potential buyer fits your offer and is ready to talk, so sales time goes to the leads most likely to become customers.. A score ranks leads continuously; qualification is the decision, often made by a person or by asking a few direct questions, that a lead is worth a sales conversation.
Why it matters for your website
Website conversations are one of the strongest engagement signals available, because visitors say what they want in their own words. "Do you integrate with NetSuite, and can we start in January?" says more than ten page views.
To use them well:
- Score what the visitor asked, not just that they chatted.
- Keep the model small enough to explain. If nobody on the team can say why a lead scored 85, nobody will trust the number.
- Check it against outcomes every quarter: do high scores actually become customers?
- Write the score and the reason to the CRM, so the person who calls knows why.
Example
A simple model for a B2B software site:
| Signal | Points |
|---|---|
| Company of 50 to 1,000 employees | +20 |
| Job title includes "Head of", "Director" or "VP" | +15 |
| Viewed the pricing page twice in a week | +10 |
| Asked about integrations, security review or contract terms in chat | +25 |
| Named a start date in the next 90 days | +20 |
| Personal email address | -10 |
| Asked about jobs | -40 |
A visitor from a 200-person company who asks about SSO and a January start scores 65 and is offered a meeting straight away. One who asks about open roles is routed to the careers page.
Related terms
- Lead qualification: deciding whether a lead is ready for sales.
- CRM: where scores are stored and acted on.
- AI SDR: an AI agent that qualifies and follows up on leads.
- Meeting booking: the next step for a high-scoring lead.
- Conversion rate: the outcome a score should predict.
Sources
- Understand the lead scoring tool (HubSpot Knowledge Base) — accessed October 21, 2026