Comparison
Lead Scoring Tools Compared: 2026 Buyer's Guide
Feb 10, 2026
The Lead Scoring Market in 2026
The lead scoring landscape has changed dramatically. Five years ago, rule-based scoring inside your CRM was the only option. Today, there are dedicated platforms using AI, intent data, and similarity matching to help B2B teams prioritize leads.
But more options means more confusion. This guide breaks down the major categories of lead scoring tools, compares the top players in each, and helps you choose the right approach for your team size and budget.
Three Categories of Lead Scoring
Before comparing specific tools, understand that lead scoring falls into three fundamentally different approaches:
1. Rule-Based Scoring
You manually define scoring rules based on lead attributes and behavior. Points are assigned for matching criteria (VP title = +10, visited pricing = +15). Simple to understand, but fragile and subjective.
Best for: Teams with a simple, well-defined ICP and fewer than 500 leads per month.
2. Predictive Scoring
Machine learning analyzes historical data to predict which leads will convert. Often uses intent data, firmographics, and behavioral signals. Powerful but typically opaque.
Best for: Enterprise teams with large datasets and dedicated data science or RevOps support.
3. Similarity Scoring
Analyzes your existing customers and scores new leads by how closely they resemble your best accounts. Transparent and data-driven without requiring massive datasets.
Best for: Mid-market teams that want data-driven scoring with full explainability.
Tool-by-Tool Breakdown
HubSpot Lead Scoring
Category: Rule-based (all plans) + Predictive (Enterprise only)
How it works: Manual point-based rules on contact and company properties. Enterprise adds ML-based predictive scoring.
Strengths: Native to HubSpot CRM. No additional tool needed. Behavioral scoring for email and web activity.
Weaknesses: Manual rules are arbitrary and require constant maintenance. Predictive scoring is a black box with no explainability. Enterprise-only for AI features ($3,600/mo+).
Price: Included in HubSpot Professional ($800/mo+) for manual. Enterprise ($3,600/mo+) for predictive.
Salesforce Einstein Lead Scoring
Category: Predictive
How it works: Salesforce's AI analyzes your CRM data to predict conversion probability. Assigns a score from 1-99 on each lead.
Strengths: Native to Salesforce. Considers all CRM fields automatically. Updates scores regularly.
Weaknesses: Requires significant historical data (1,000+ leads with outcomes). Black-box scoring with limited explainability. Only available on Salesforce Enterprise+ plans.
Price: Included in Salesforce Enterprise ($165/user/mo+).
6sense
Category: Predictive + Intent
How it works: Combines intent signals from its publisher network with firmographic and technographic data to predict buying likelihood and buying stage.
Strengths: Powerful intent data. Buying stage identification. Full ABM orchestration platform.
Weaknesses: Expensive ($60K-150K+/year). Complex implementation (4-12 weeks). Scoring is largely opaque. Privacy concerns with third-party tracking.
Price: $60,000-$150,000+/year. Annual contracts.
MadKudu
Category: Predictive
How it works: Pre-built AI models score leads based on firmographic data, behavioral signals, and product usage patterns (for PLG companies).
Strengths: Good for product-led growth companies. Integrates with major CRMs and marketing tools. Supports both MQL and PQL scoring.
Weaknesses: Limited explainability. Best suited for PLG models specifically. Pricing not transparent.
Price: Custom pricing. Typically $20,000-$60,000/year.
Clearbit (now Breeze Intelligence by HubSpot)
Category: Enrichment + Rule-based scoring
How it works: Enriches lead data with firmographic and technographic information. Uses enriched data to power scoring rules in your CRM.
Strengths: Excellent data enrichment. Provides the raw data that makes rule-based scoring more accurate. Now integrated into HubSpot.
Weaknesses: Enrichment tool, not a scoring platform. You still need to build scoring rules manually. Credit-based pricing for lookups.
Price: Integrated into HubSpot plans. Standalone pricing varies.
Conturs
Category: Similarity scoring
How it works: Analyzes your closed-won customers across hundreds of attributes and scores new leads by similarity to your best accounts. Every score includes full explanation.
Strengths: Fully transparent scoring with similar customer references. Self-updating model. Works with small datasets (20+ customers). Minutes to set up. Privacy-first (no third-party data).
Weaknesses: No intent data. No behavioral scoring. Best for ICP fit scoring specifically.
Price: Starts at $49/month. No annual commitment.
Comparison Matrix
Explainability
HubSpot Manual: High (you built the rules)
HubSpot Predictive: Low
Salesforce Einstein: Low
6sense: Low-Medium
MadKudu: Medium
Conturs: High (full breakdown + similar customers)
Setup Time
HubSpot: Hours-Days
Salesforce Einstein: Days-Weeks
6sense: 4-12 Weeks
MadKudu: 2-4 Weeks
Conturs: Minutes
Minimum Data Required
HubSpot Manual: None (you define rules)
HubSpot Predictive: 1,000+ contacts with outcomes
Salesforce Einstein: 1,000+ leads with outcomes
6sense: Account list + CRM history
MadKudu: Product usage data + CRM
Conturs: 20+ closed-won customers
Annual Cost (Mid-Market)
HubSpot Manual: $9,600+ (Professional plan)
HubSpot Predictive: $43,200+ (Enterprise plan)
Salesforce Einstein: $23,760+ (Enterprise, 12 users)
6sense: $60,000-$150,000+
MadKudu: $20,000-$60,000
Conturs: $588-$2,388
How to Choose: Decision Framework
Start With Your Primary Question
"Who is interested right now?" You need intent data. Look at 6sense or Bombora.
"Who fits our ICP best?" You need similarity or predictive scoring. Look at Conturs, MadKudu, or Einstein.
"Who is both interested AND a good fit?" You need a combination. Layer intent (6sense) with fit scoring (Conturs) for maximum precision.
Consider Your Resources
No dedicated RevOps: Choose tools that work out of the box (Conturs, HubSpot manual)
1-2 RevOps people: Can manage moderate complexity (MadKudu, Conturs + enrichment)
Full RevOps team: Can handle enterprise platforms (6sense, custom Einstein setup)
Match Your Budget
Under $5K/year: Conturs or HubSpot manual scoring
$5K-$25K/year: Conturs + enrichment tools, or Salesforce Einstein
$25K-$75K/year: MadKudu or 6sense (lower tier)
$75K+/year: 6sense full platform or custom stack
The Emerging Best Practice: Layered Scoring
The most sophisticated RevOps teams in 2026 don't rely on a single scoring tool. They layer multiple signals:
Layer 1 — Fit (Conturs): Does this lead match our ICP?
Layer 2 — Engagement (CRM native): Is this lead engaging with our content?
Layer 3 — Intent (optional): Is this account researching our category?
Each layer answers a different question. Combined, they give you the complete picture: who is a good fit, who is engaged, and who is ready to buy.
The Bottom Line
There is no single best lead scoring tool. The right choice depends on your team size, budget, technical resources, and primary scoring question. For mid-market teams that want transparent, affordable, fast-to-deploy scoring, similarity-based tools like Conturs offer the best value. For enterprise ABM programs with large budgets, platforms like 6sense provide the most comprehensive solution. And for teams already invested in HubSpot or Salesforce, starting with native scoring and layering additional tools as needed is the most practical path.
