What Is Demographic vs. Behavioral Scoring?
Learn how fit (demographic/firmographic) and interest (behavioral) scores work together in Marketo to prioritize the right people, route faster, and accelerate revenue—without muddying intent signals.
Demographic (or firmographic) scoring measures fit—are they in your ICP by role, company size, industry, tech, region? Behavioral scoring measures intent—what have they done: visits, content, forms, events, product use. A modern model keeps these as two separate scores and combines them for routing and SLAs (e.g., Fit A–D × Intent 0–100) instead of one blended number that hides meaning.
Key Differences at a Glance
How the Two-Score Model Works in Marketo
Use parallel scores—Fit and Intent—then gate sales SLAs on the combination (e.g., “Only A/B Fit with Intent ≥ 70 route to Sales”).
Blueprint: Fit × Intent Scoring
- Define Fit tiers (A–D): Title/function, company size, industry, territory, tech—weighted by ICP. Use enrichment and normalization early.
- Instrument Behavior: Page depth, high-intent assets (pricing, product docs), email engagement, webinar/demo events, trial/product signals.
- Score rules: + points for intent milestones (e.g., pricing view +25), – points for inactivity; cap totals; avoid stacking duplicates.
- Bot/Internal filtering: Exclude internal IPs, QA/test users, and suspicious velocity.
- Decay & resets: Auto-decrease intent after X days; reset on role change, bounce, or unsubscribe.
- Combine for routing: Route when
Fit ∈ {A,B}ANDIntent ≥ Threshold; else nurture by segment. - Feedback loop: Quarterly recalibration using conversion by band (e.g., A/80+ → SQL 32%).
Scoring Governance & Maturity Matrix
| Capability | From (Ad Hoc) | To (Operationalized) | Owner | Primary KPI |
|---|---|---|---|---|
| Fit Definition | Loose ICP, manual titles | Standardized ICP tiers (A–D) with enrichment & normalization | RevOps/Marketing Ops | % A/B Fit Leads |
| Behavior Catalog | One-off scores | Taxonomy of low/med/high-intent actions with caps & decay | MOPs/Demand Gen | Leads w/ Intent ≥ Threshold |
| Quality Controls | Bot noise | Bot/internal filtering, QA roles, IP excludes | Analytics/IT | False-Positive Rate |
| Routing & SLAs | Single blended score | AND-gated Fit×Intent with Sales accept/decline reasons | Sales Ops | Speed-to-Lead, SAL% |
| Optimization | Annual tweaks | Quarterly calibration by band vs. SQL/Win | RevOps | SQL Rate by Band |
Client Snapshot: Two Scores, Cleaner Pipeline
Separating Fit (A–D) from Intent (0–100) cut false positives, raised Sales acceptance, and improved pipeline predictability. See how we mature revenue marketing programs: Comcast Business · Broadridge
For a deeper primer on taxonomy, decay, and thresholds, grab the Revenue Marketing eGuide.
Frequently Asked Questions: Demographic vs. Behavioral Scoring
Operationalize Fit × Intent Scoring in Marketo
We’ll design ICP tiers, instrument high-intent signals, add decay and filters, and wire routing/SLA thresholds to create signal you can trust.
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