Lead Scoring Calculator
Score leads based on demographic fit and behavioural signals to prioritise sales outreach and predict conversion likelihood.
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How to use this calculator
Demographic points come from job title, company size, and industry fit. Behavioural points come from email opens (×2 each), page visits (×1 each), form submissions (×5 each), and demo requests (20 points). The total determines grade and recommended action.
- 1
Select the lead's job title seniority, company size, and how well their industry matches your ICP.
- 2
Enter behavioural data from your CRM or marketing automation: email opens, page visits, and form submissions in the last 30 days.
- 3
Mark whether the lead has requested a demo or booked a call — this carries the highest weight.
- 4
Use the grade and recommended action to decide whether to route to sales, inside sales, or continue nurturing.
Frequently asked questions
How is the total score calculated?
Total = demographic + behavioural. Demographic is the points for seniority, company size and industry fit added together. Behavioural is email opens × 2, plus page visits × 1, plus form submissions × 5, plus 20 if a demo or call was requested. The default lead scores 19 + 21 = 40.
What score does each grade need?
A needs 80 or more, B needs 60 to 79, C needs 40 to 59 and anything below 40 is a D. Each grade comes with a fixed recommended action, from immediate outreach for A to automated nurturing for D. These cut-offs are the tool’s settings and are not derived from your own conversion history.
Is there a maximum score?
The demographic side tops out at 30, but the behavioural side has no ceiling because opens, visits and form submissions are not capped. A lead with 12 opens, 25 visits, 3 forms and a demo request, plus perfect fit, scored 114. One person clicking around heavily can therefore outweigh a perfect fit.
Can a demo request alone make a lead a good prospect?
Not under these weights. A lead with unknown title, size and industry and no other activity, but a demo request, scores 20 and lands in grade D. If your team treats every demo request as a priority, route those leads by that rule directly and use the score for everything else.
Can fit alone reach a high grade?
No. The best possible fit is 30 points, which is a D. To reach an A with perfect fit a lead needs at least 50 behavioural points. To reach a C it needs at least 10. A well-matched account that has not engaged therefore stays in nurture.
Does the score fade over time or go negative?
No. The calculator has no time decay and no negative points for things such as unsubscribes or a competitor’s domain. The 30-day wording on the inputs is a prompt for you: enter only activity from that window. Re-score regularly and subtract engagement that has gone cold.
Should I use these weights in my own CRM?
Use them as a starting model and adjust. Look at the leads that became customers and ask which signals they showed first. If page visits matter more than email opens in your data, change the multipliers. A scoring model is only worth keeping if the leads it ranks highly really do convert more often.
Lead scoring calculator — fit points plus engagement points, graded A to D
How points are awarded
The model has two halves. The fit half rewards who the lead is: seniority, company size and industry match, each worth up to 10 points. The activity half rewards what the lead has done recently, with form submissions weighted most among the countable actions and a demo request worth a flat 20. The two halves are simply added.
| Signal | Points |
|---|---|
| Seniority | C-suite, VP or founder 10 · Director 8 · Manager 6 · Individual contributor 3 · Unknown 0 |
| Company size | 500+ employees 10 · 50–499 7 · 1–49 4 · Unknown 0 |
| Industry fit | Perfect 10 · Good 6 · Neutral 3 · Poor 0 |
| Email opens | 2 per open |
| Page visits | 1 per visit |
| Form submissions | 5 per submission |
| Demo or call requested | 20 |
Five leads, five outcomes
These results were produced by the calculator.
| Lead | Fit | Activity | Total | Grade |
|---|---|---|---|---|
| Manager, mid-market, good fit; 4 opens, 8 visits, 1 form | 19 | 21 | 40 | C |
| VP at enterprise, perfect fit; 12 opens, 25 visits, 3 forms, demo | 30 | 84 | 114 | A |
| Director, mid-market, good fit; 10 opens, 12 visits, 2 forms | 21 | 42 | 63 | B |
| Individual contributor, SMB, neutral; 2 opens, 3 visits | 10 | 7 | 17 | D |
| Nothing known; demo request only | 0 | 20 | 20 | D |
Why the third lead is a B
The director has 21 fit points, and the activity adds 20 for opens, 12 for visits and 10 for two forms, giving 42. Together that is 63, which clears the 60 line for outreach within 24 hours. Dropping the forms to zero would leave 53 and move the lead to a C, so the example shows how much one conversion action changes the grade.
Where fixed weights fall short
Opens and visits are uncapped, so a lead who refreshes a pricing page twenty-five times is treated as twenty-five times more interested. Nothing checks whether the visits were to useful pages, and nothing removes points for silence. If you adopt this model, add caps or decay in your own system, and review the leads that scored high but never replied.
Calibrating against your own results
Pull a list of recent customers and a list of leads that went nowhere, then score both. If many customers land in C or D, lower the cut-offs or raise the weight on the signals they showed. If the A group is full of leads that never buy, the weights are rewarding the wrong behaviour. The grades are only useful once they match how your pipeline really behaves. Revisit the weights every quarter, write down why each one changed, and keep the old version for comparison. A model that nobody can explain to the sales team tends to be ignored, so favour a handful of signals that everyone understands over a long list of small adjustments.
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Results are estimates for informational purposes only and do not constitute professional financial, medical, legal, or technical advice. Read full disclaimer →