HubSpot's Lead Scoring: Fit, Engagement & Combined Models for CMOs

64% of CMOs now carry direct responsibility for profits, not lead volume alone (IBM CMO Study 2025).

This shift changes what scoring must deliver: forecast accuracy, resource efficiency, and CFO confidence.

Your legacy scoring model lumps ICP fit with behavior into one number.

When a competitor's intern downloads ten whitepapers, they score higher than your ideal customer who visited once. Sales ignores the leads. Marketing defends the volume.

HubSpot sunset the legacy model on August 31, 2025, and back in the day, we had to use complex workflows (we wrote about it here) to achieve what is now a native feature. Here is also a great webinar by HubSpot User Groups on the topic.

 
If you haven't migrated, your scores are frozen and workflows depending on them no longer function.

Why the Single-Score Model Failed

The legacy HubSpot lead scoring model mixed two dimensions into one score.

Fit measures who they are—company size, industry, job title, revenue.

Engagement measures what they've done—form fills, email clicks, page visits.

Mixing these creates predictable problems.

The False Positive Trap

A junior worker at a wrong-fit company downloads your entire resource library. Score rises.

Sales wastes a week chasing someone who can't buy.

The Missed Opportunity Gap

A VP at your perfect-fit account visits your pricing page once. Score stays low.

Single-score models reward volume over signal quality.

65% of sales and marketing pros report team misalignment (Forrester 2024).

Much of that friction traces to lead scoring that can't explain why a lead qualified.

When you can't split fit from engagement, you can't forecast deals. CFOs notice.

The Three-Model Framework: Fit, Engagement, and Combined

HubSpot's new scoring splits concerns into three models.

Fit Scoring

• Measures ICP match
• Based on static traits (company and contact data)
• Stays stable over time
• Use for: Account targeting, list building

Engagement Scoring

• Measures buying signals
• Based on actions (forms, emails, meetings, page visits)
• Changes with activity
• Use for: Sales timing, nurture triggers

Combined Scoring

• Creates a 3x3 matrix (A1 through C3)
• Keeps separate fit and engagement values
• Use for: Routing, priority ranking

[Diagram: Three-model setup showing Fit Score, Engagement Score, and Combined Score feeding into routing]

The matrix labels work as coordinates. Letters (A/B/C) = Fit tier. Numbers (1/2/3) = Engagement tier.

A1 means high fit, high engagement. C3 means low fit, low engagement.

Fit Scoring: Building Your ICP Into the Model

Lead scoring for fit needs a step most teams skip: ICP definition.

Before setting fit scores:

• Study won deals for patterns
• Find traits that disqualify prospects
• Write criteria both sales and marketing accept
• Set thresholds from conversion data

Common fit criteria:

• Annual revenue range
• Industry type
  • SaaS
  • Services
  • Manufacturing
• Company size
• Job title patterns
  • Director level
  • VP level
  • C-suite
• Operating geography

Award points for ICP matches. Deduct points for disqualifiers.

Example scoring weights:

Set thresholds that create clear tiers:

• High fit (A): 70-100 points
• Medium fit (B): 40-69 points
• Low fit (C): 0-39 points

Test against historical win rates. If B-tier leads convert like A-tier, adjust your thresholds.

Engagement Scoring: Measuring Purchase Intent

Engagement scoring tracks actions that signal buying intent.

Weight events by conversion impact:

• Demo request = 25 points
• Pricing page visit = 15 points
• Case study download = 10 points
• Email click = 3 points
• Blog visit = 0.5 points

Score Decay Matters

Six-month-old actions shouldn't count like last week's. Apply decay rates (10-20% monthly) to prevent "zombie leads" from appearing hot.

Event Grouping Plan

• Awareness group (40-point cap)
  • Blog visits
  • Email opens
• Consideration group (30-point cap)
  • Content downloads
  • Webinar registrations
• Decision group (30-point cap)
  • Demo requests
  • Pricing page views

Caps prevent any single action from dominating the score.

[Screenshot: HubSpot engagement score setup showing event groups and decay settings]

Machine learning models rank sales-ready leads 77% more accurately than manual scoring (Martal Group 2025). Well-designed manual rules compete with AI when data is limited.

Combined Scoring: The Matrix Model for Routing

The 3x3 matrix creates nine routing categories:

The B1 Problem

Medium fit + high engagement creates ambiguity. The prospect shows interest but doesn't match ICP.

Route to SDR for qualification—not direct to AEs.

The C1 Trap

Low fit + high engagement often indicates:

• Competitors researching you
• Students downloading resources
• Consultants gathering intel

High activity doesn't compensate for wrong fit.

AI-Powered Scoring Option

Enterprise tier unlocks AI scoring that identifies patterns across hundreds of data points.

Requirements:

• Minimum 50 contacts (25 closed-won, 25 closed-lost)
• Historical conversion data
• Clean data quality

Organizations using AI scoring platforms see 138% greater ROI on lead efforts versus 78% without scoring (Martal Group 2025).

Start with manual scoring. Add AI after 6-12 months of conversion data.

Migration Plan from Legacy Scoring

HubSpot sunset legacy lead scoring on August 31, 2025. Historical scores remain as static data—they no longer update, and workflows depending on them stopped functioning. HubSpot may delete unused legacy properties in Q4 2025.

Migration timeline (if you haven't switched yet):

• Weeks 1-2: Audit legacy rules
• Weeks 3-4: Map rules to Fit vs Engagement
• Weeks 5-10: Build and test new system
  • Compare new scores against historical data
  • Validate routing logic
• Weeks 11-12: Update workflows, train teams

Common migration mistakes:

• Copying legacy scores exactly (improve, don't replicate)
• Skipping historical validation (compare against past conversions)
• Missing dependent workflows (breaks automation)
• Rushing threshold selection (produces poor qualification)

[Screenshot: HubSpot new lead scoring setup with fit and engagement models]

This isn't about meeting a deadline. It's about resolving years of scoring debt.

The migration forces the ICP definition work you've deferred.

Conclusion

HubSpot lead scoring works when you separate concerns and align your teams.

Your path forward:

• Separate what matters
  • Fit measures ICP match
  • Engagement measures buying signals
  • Combined creates routing logic
• Configure for reality
  • Define ICP before scoring setup
  • Set thresholds from conversion data
  • Apply decay to engagement only
• Align the organization
  • Run joint sales-marketing workshops
  • Agree on routing rules per category
  • Review weekly

The August 31, 2025 deadline has passed. If you're still on legacy scoring, migrate now—your data is already frozen.

Lead scoring tools don't solve scoring problems. Process design does.

The best model fails if sales doesn't trust it and marketing doesn't maintain it.