Marketing Automation & Workflows:
How Do I Implement Lead Scoring That Actually Works?
Blend fit (who they are) and intent (what they do), wire it to routing & SLAs, and iterate with closed-won feedback. This guide shows a practical, 90-day path to a scoring model sales trusts.
Lead scoring that works is a two-factor system: a Fit score (ICP attributes like company size, industry, role) plus an Intent score (behavioral signals like pricing views, demo requests, product usage). Use threshold tiers (A/B/C for Fit × 1/2/3 for Intent) to route and prioritize, apply decay to old actions, and refresh weights monthly using closed-won correlations. The output must trigger MQL → SDR SLA, not just a higher number.
Principles for Reliable Lead Scoring
Which Scoring Approach Fits Your Team?
Match complexity to data quality and sales process. Upgrade as hygiene and volume improve.
Rules vs. Points vs. Predictive vs. Hybrid
| Model | How It Works | Best For | Pros | Watchouts |
|---|---|---|---|---|
| Simple Rules | Binary triggers (e.g., demo request → route) | Early-stage teams, low data quality | Fast to launch, transparent | No prioritization gradient; brittle |
| Points-Based | Weights for actions & attributes with thresholds | Most B2B teams with MAP/CRM | Granular, tunable, auditable | Drift without decay & periodic re-fit |
| Predictive (ML) | Model predicts conversion probability | High volume, rich history | Finds non-obvious patterns | Requires data science & monitoring; opaque |
| Hybrid (Fit×Intent tiers + ML assist) | Tiers drive routing; ML refines weights | Scaling orgs seeking trust + lift | Explainable yet adaptive | Needs governance & change control |
Your 90-Day Lead Scoring Implementation
Stand up a trustworthy model in three sprints—then tune with sales feedback and win data.
Phase 1 → Phase 2 → Phase 3
- Days 1–30: Define & Draft — Align ICP and disqualification rules with sales; list top 10 Fit fields (industry, employee band, role, tech stack) and top 10 Intent signals (pricing, demo, high-intent pages, repeat product visits). Draft Fit tiers (A/B/C) and Intent bands (1/2/3). Set negative scoring rules and consent gates.
- Days 31–60: Build & Route — Implement points and decay (e.g., 25% weekly decay for behavior). Create tier matrix (A3/A2/B3 = MQL; others to nurture). Wire CRM routing, SDR queues, and a 15–30 minute first-touch SLA. Launch audit dashboard (score breakdown, acceptance, opp rate).
- Days 61–90: Validate & Optimize — Compare MQL cohorts vs. holdout for opp rate and win rate. Re-weight top signals by lift. Add model exclusions (current customers under CSM, competitors). Publish playbook for SDR talk tracks by tier.
Scoring Governance Matrix (Phases, Owners, Outputs)
| Phase | Primary Focus | Owner(s) | Key Outputs | Primary KPI |
|---|---|---|---|---|
| 1. Define | ICP, signals, thresholds | MOps + Sales + RevOps | Fit/Intent catalogs, A/B/C × 1/2/3 tiers, negative rules | Sales Alignment Score |
| 2. Build | MAP/CRM logic, routing, decay | MOps + IT | Score fields, workflows, SLA timers, dashboards | MQL Acceptance % & Time-to-First-Touch |
| 3. Optimize | Back-test, reweight, documentation | MOps + Analytics | Lift analysis, weight updates, SDR playbook | Opp Rate & Win-Rate Lift vs. Baseline |
Client Snapshot: From “Noisy” MQLs to Sales-Ready
A B2B SaaS team swapped a single blended score for Fit×Intent tiers with behavior decay and negative scoring. MQL acceptance rose from 58% to 86%, opportunity rate improved by 31%, and SDR first-touch time dropped below 25 minutes through clear routing & SLAs.
Tie your scoring design to RM6™ and map thresholds to The Loop™ so Fit×Intent tiers align with journey stage and sales motions.
Frequently Asked Questions on Lead Scoring
Clear, practical answers to get your model adopted.
Build a Scoring System Sales Trusts
We’ll define ICP & signals, wire Fit×Intent tiers with decay and routing, and tune by closed-won data—so your MQLs convert.
Start Your Scoring Build Assess Scoring Maturity