lead-scoringlisted

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.
mbfinotti/revops-skills · ★ 0 · AI & Automation · score 73

Install: claude install-skill mbfinotti/revops-skills

# 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 recali