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AI-Powered Lead Scoring

Machine learning model that scores leads based on historical conversion data

❌ The Problem

  • Traditional lead scoring uses arbitrary point values
  • Models don't learn from actual conversion data
  • Firmographic and behavioral signals not combined properly
  • Scoring doesn't improve over time
  • Best leads still get missed

✅ The Solution

  • ML model trained on your historical conversions
  • Learns what actually predicts closed-won deals
  • Combines firmographic and behavioral signals
  • Continuously improves with new data
  • Identify leads that look like your best customers

How It Works

1

Data Analysis

Analyze historical closed-won deals

2

Model Training

ML identifies conversion patterns

3

Scoring Applied

New leads scored in real-time

4

Enrichment

Clay adds additional signals

5

Continuous Learning

Model improves over time

Key Features

ML-powered scoring model
Historical conversion training
Firmographic + behavioral signals
Real-time scoring
Clay integration for enrichment
Continuous model improvement
Explainable scores
A/B testing against traditional
Conversion rate tracking
Score distribution analysis

Works With

Clay
HubSpot
Salesforce
Clearbit
6sense
Python/ML models
BigQuery
Snowflake

Don't see your tool? We integrate with 100+ platforms.

Perfect For

Data-Driven Teams

Beyond rule-based scoring

High-Volume Leads

Where ML impact is significant

Growth Teams

Optimizing conversion rates

Pricing

$2,497

One-time setup + configuration

Optional: $300/month ongoing maintenance & optimization

Includes updates, new rules, performance monitoring, and support

Custom configuration tailored to your workflows

Integration with your existing tools

Testing, training, and documentation

30 days post-launch support

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