What is lead scoring?

Written by Madalena Rugeroni, founder of Mazo · Updated 10 November 2026

Lead scoring assigns each lead a number based on how closely it matches your ideal customer profile (fit) and how much buying intent it shows (engagement), so sales talks to the most promising people first.

A simple lead scoring model

Lead score = fit points + engagement points − decay for inactivity

Fit (who they are): industry, company size, role, tech stack. Fit changes rarely.
Engagement (what they do): pricing page visits, demo requests, product usage, email replies. Engagement fades, so subtract points after a few quiet weeks.

Keep fit and engagement as two separate scores if you can. A perfect-fit company that hasn't engaged needs outreach; a highly engaged student needs nothing from sales.

Worked example

A fictional SaaS scores leads out of 100 and routes anything above 60 to sales.

Target industry +20, 50–500 employees +15, head of operations or above +15 (fit, max 50).
Visited pricing +10, requested a demo +30, invited a teammate in the trial +20 (engagement, capped at 50).
An operations director at a 120-person target company who visited pricing scores 20 + 15 + 15 + 10 = 60: route to sales today.

Every quarter, compare scores against which leads actually became customers, and adjust the points.

Why it matters from €0 to €1M ARR

Fewer than ~100 leads a month: skip scoring. Read every lead and decide by hand.
Inbound outpacing the founder: a three-rule version ("target industry + right size + demo request = call today") beats a complex model.
With a sales team: scoring decides who an SDR calls first, so test it against closed-won data.

Mazo's rule of thumb: build your first scoring model from your last 10 customers, never from guesses. Whatever they had in common at the moment they signed up is worth the most points.

Common lead scoring mistakes

Scoring before you have enough data. The points reflect assumptions.
Rewarding activity over fit. Ten blog visits from a non-buyer outscore one demo request from your ICP.
No decay. A lead who was active last year still looks hot.
Setting it and forgetting it. Recalibrate against won and lost deals each quarter.

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FAQ

What is the difference between fit and engagement scoring?

Fit scoring measures how closely a lead matches your ideal customer profile, using data like industry, size and role. Engagement scoring measures buying intent from behaviour, such as pricing visits, demo requests and product usage.

Does an early-stage startup need lead scoring?

Usually not until lead volume is more than the founder or sales team can review by hand. Before that, reading every lead teaches you more than a points model.

What is predictive lead scoring?

Predictive lead scoring uses a statistical model trained on past won and lost deals to rank new leads. It needs a large history of closed deals, so it suits later-stage companies.

Who wrote this

Madalena Rugeroni built Mazo. She's an ex-Googler, a startup advisor and investor, and runs a portfolio of internet companies. Before that, as Head of Growth at Amplemarket, she scaled a B2B SaaS to $10M ARR. LinkedIn

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