Lead Scoring Calculator

Build a weighted lead score from fit and behaviour criteria, and see where a lead falls against your qualification thresholds.

🎯 Marketing📐 Score = fit score × fit weight + behaviour score × behaviour weight💼 Business
Company size fit
Industry fit
Job title / seniority
Website engagement
Content downloads
Pricing page visit
Demo or trial request
Please enter valid values.

Formula & Reference

VariableSymbolFormulaUnits
Lead Scoring CalculatorScore = fit score × fit weight + behaviour score × behaviour weightpoints out of 100

Step-by-Step Examples

Example 1
Sales Qualified

Ideal company size, target industry, decision maker, deep engagement, multiple downloads, pricing page, demo requested.

  • Fit = 25 + 15 + 15 = 55
  • Behaviour = 10 + 10 + 10 + 15 = 45
  • Total = 100
✓ 100/100 — route to sales immediately
Example 2
Good Fit, Low Engagement

Ideal size, target industry, decision maker, single visit only, no downloads.

  • Fit = 55, behaviour = 0
  • Total = 55 — marketing qualified band
  • Strong fit warrants proactive outreach rather than waiting for engagement
✓ 55/100 — worth proactive outreach
Example 3
Engaged but Poor Fit

Outside target industry, no influence, but repeated visits, downloads, pricing page and demo request.

  • Fit = 0 + 0 + 0 = 0
  • Behaviour = 45
  • Total = 45
  • High interest but no fit — unlikely to convert or retain
✓ 45/100 — engagement without fit

Real-World Applications

Common Mistakes to Avoid

⚠️
Scoring behaviour without fit

A highly engaged lead outside your target market will consume sales time and rarely convert. Fit should gate behaviour, not sit alongside it equally.

⚠️
Setting thresholds by intuition

Score thresholds should be derived from historical conversion rates by score band, not chosen because they look reasonable.

⚠️
Never recalibrating the model

As the product and ideal customer profile evolve, scoring weights drift out of alignment with what actually converts.

Frequently Asked Questions

What is lead scoring?
Assigning points across fit criteria such as company size and industry, and behaviour criteria such as engagement, to prioritise which leads sales should work.
What is the difference between fit and behaviour scoring?
Fit measures how well the lead matches your ideal customer profile. Behaviour measures demonstrated interest. Both are needed — either alone misleads.
How do I set score thresholds?
Analyse historical conversion rates by score band and set thresholds where conversion probability justifies sales time.
Should negative scoring be used?
Yes. Disqualifying signals such as competitor domains, student email addresses, or explicitly out-of-scope industries should subtract points.
How often should the model be recalibrated?
At least annually, and whenever the product, pricing, or ideal customer profile changes materially.

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