Lead Qualification System

Overview

Designed a decision intelligence system that scores leads based on firmographic data, engagement signals, and historical conversion patterns. Surfaces the top 20% of leads that drive 80% of revenue...

The Problem

A B2B SaaS company had sales reps spending 60% of their time chasing leads that never converted. No clear qualification criteria. No data-driven prioritization. Just gut feeling and wasted effort.

The Solution

Designed a decision intelligence system that scores leads based on firmographic data, engagement signals, and historical conversion patterns. Surfaces the top 20% of leads that drive 80% of revenue.

Architecture

• Data enrichment pipeline pulling from 6 sources
• Feature engineering for behavioral signals
• Gradient boosted model with SHAP explanations
• Real-time scoring API with sub-100ms latency
• CRM integration with automated lead routing
• Feedback loop for continuous model improvement

Business Impact

• 35% increase in lead-to-opportunity conversion
• Sales reps now focus on qualified leads only
• Average deal size increased 22%
• Sales cycle shortened by 18 days

Lessons Learned

• Explainability matters more than marginal accuracy gains
• Sales teams need to trust the scores - build confidence gradually
• Historical data quality is usually worse than expected
• Quick wins build stakeholder buy-in

Next Steps

• Account-level scoring
• Churn prediction integration
• Marketing attribution