lead-scoring

The saved excerpt is a snapshot from when this skill was listed. The external source remains the complete and most current version.

---
name: lead-scoring
description: Design, validate, and recalibrate a lead scoring model - fit and engagement signals, weighting, negative scoring and exclusions, decay, MQL/PQL threshold and tier setting, backtesting against closed-won/closed-lost outcomes, and governance; also diagnoses an existing broken model. Use whenever the user mentions lead scoring, an MQL threshold, fit vs engagement scoring, product-qualified leads, score decay, "score my leads", "our lead scores are wrong", "sales rejects our MQLs", or "too many junk MQLs" - even if they never say "scoring model". Covers B2B sales-led and B2C/PLG, rules-based design and predictive readiness. Do NOT use for assigning scored leads to reps - use mbfinotti/revops-skills@lead-routing instead.
license: MIT
metadata:
  author: Maya-Beth Finotti
  version: "1.2.2"
---

# Lead Scoring

Design, validate, and maintain a model that ranks leads by likelihood to become revenue. The practitioner standard splits scoring into two separate axes:

- **Fit** (can they buy): firmographic, demographic, technographic.
- **Engagement** (are they about to buy): behavioral, in-product.

This two-axis model appears under several names: Marketo's A-D x 1-4 grade-and-score grid, MadKudu's Customer Fit x Likelihood to Buy, and OpenView's product-qualified lead (PQL) in PLG.

Scoring fails far more often from organizational neglect - no sales sign-off, no recalibration, MQL count treated as the goal - than from bad math, so validation and governance are part of the design here, not an afterthought. The finished score is an input to assignment: routing, territories, and rep matching belong to `mbfinotti/revops-skills@lead-routing`. Defining the account-fit criteria this skill's fit axis weights - firmographic and technographic ICP tiers - belongs to `mbfinotti/sales-skills@sales-icp-definition`; this skill owns turning that definition, plus behavioral engagement, into a working score.

The capture-score-route-nurture mechanics are structurally identical for B2B and B2C/PLG. What genuinely differs between B2C/PLG and B2B:

- Dominant signal source is in-product behavior, not forms and content.
- No buying committee - one user's behavior can qualify.
- Cycles run in days, not quarters.

Because of these differences, decay, thresholds, rescoring frequency, and recalibration all run faster in B2C/PLG.

## Interview

Ask before designing anything. One question per message; offer multiple-choice answers when possible. Skip a question only when the user already gave the answer.

- Which motion? (a) sales-led B2B, (b) PLG / self-serve with sales assist, (c) B2C transactional.
- Roughly how many new leads per month, and how many closed-won and closed-lost outcomes exist from the last 12-24 months? (Decides rules-based vs predictive, and how much backtesting is possible.)
- What is actually on a lead record at creation time - enrichment coverage per fit field, form fields, product events? (A score is downstream of data quality.)
- Does a model already exist? If yes: redesign, or diagnose first? (Diagnosis path: see Diagnosing a Broken Model.)
- How many leads can sales actually work per week? (The honest threshold constraint.)
- Who signs off - which sales leader, and what acceptance-rate floor will they hold the model to?
- Any EU or consent constraints? Behavioral scoring is profiling under GDPR; the lawful basis must be documented.
- By what date must the model be scoring live, and what is waiting on it? (A date inside two weeks rules out both enrichment procurement and the conversion-band threshold method; a quarter of runway makes both affordable.)
- One-off win or compounding asset? (A single campaign list to work stops at v1 weights and a capacity threshold; a compounding mandate is what justifies enrichment, the full backtest, and the recalibration cadence that keep the model honest after launch.)
- What is the effort ceiling - analyst hours, CRM/marketing-automation admin access, a procurement a