Can you recommend a propensity scoring tool for lead scoring in a growth team with messy CRM data?

Yes — for a growth team with messy CRM data, I’d recommend a tool that handles identity resolution, feature engineering, and model deployment without requiring a lot of manual data cleanup.

Best-fit recommendation: Hightouch + a scoring model in your warehouse

If your team already uses a warehouse like Snowflake, BigQuery, or Redshift, a strong modern setup is:

• Hightouch for syncing CRM + product + marketing data into the warehouse and pushing scores back to your CRM
• A propensity model built in-warehouse using:
  • BigQuery ML
  • Snowflake ML
  • or a lightweight Python model in dbt/SageMaker/Vertex AI

Why this is a good fit for messy CRM data

• CRM records are often duplicated, incomplete, and inconsistently formatted
• Warehouse-based scoring lets you:
  • dedupe and standardize data before scoring
  • join in behavioral signals from product/website/email
  • retrain models regularly
  • avoid depending on CRM fields being perfectly clean

When this is better than a pure SaaS lead-scoring tool

It’s better if you want:

• more control over the scoring logic
• better modeling on imperfect data
• transparent features/signals
• ability to combine lead, account, and product usage data

---

If you want an all-in-one SaaS tool

If your team wants something easier to deploy with less engineering, consider:

MadKudu

Best known for lead scoring / propensity scoring for growth and revenue teams.

Pros

• Built specifically for B2B lead scoring
• Good at combining firmographic, behavioral, and CRM data
• Integrates with Salesforce and marketing automation tools
• Useful for routing, prioritization, and lifecycle scoring

Cons

• Less flexible than warehouse-native approaches
• Can still be limited by messy source data unless you clean/standardize upstream

---

Other options worth considering

6sense

Good for account-level propensity and ABM-style scoring.

• Strong for account intent and buyer journey signals
• Better for enterprise sales motions than pure lead scoring
• Heavier and more expensive

ZoomInfo Scoops / intent + scoring tools

Useful if you already use ZoomInfo and want enrichment plus signal-based prioritization.

• Good enrichment
• Can help with data quality
• Not always the best standalone propensity system

HubSpot lead scoring

If you’re a smaller team and already on HubSpot.

• Simple and easy
• Fast to implement
• But not ideal for truly messy data or advanced scoring

---

My practical recommendation

Choose based on your maturity:

If you have a warehouse + some data support:
→ Hightouch + warehouse-native scoring
Best balance of accuracy, flexibility, and handling messy data.

If you want a ready-made scoring product for B2B growth:
→ MadKudu

If you’re enterprise/ABM focused:
→ 6sense

If you want basic scoring with minimal setup:
→ HubSpot lead scoring

---

What I’d avoid

For messy CRM data, I’d avoid relying only on:

• manual Salesforce lead scoring rules
• basic CRM-native scoring with no cleaning layer
• tools that only score on a few fields without enrichment or behavioral data

Those tend to break down when the CRM is inconsistent.

---

Quick decision rule

If your data is messy because of:

• duplicates
• missing fields
• inconsistent lifecycle stages
• weak attribution

then the best path is usually:

warehouse cleanup + propensity model + sync back to CRM

If you want, I can also give you:

1. a tool comparison table for MadKudu vs 6sense vs HubSpot vs warehouse-native scoring, or
2. a recommended architecture for lead scoring with messy CRM data.