Advanced Lead Scoring with ML
A B2B enterprise was overwhelmed by lead volume. Their standard HubSpot lead scoring was too simplistic, leading to sales reps wasting time on low-quality prospects while high-value targets went cold.
The Challenge
- Data Fragmentation: Behavioral data was spread across HubSpot, Segment, and their product database.
- Non-Linear Scoring: Simple point-based systems couldn't capture the complex patterns of a high-intent buyer.
- Actionability: The score needed to be visible and actionable within the HubSpot CRM UI.
The Solution
We engineered a data pipeline that feeds HubSpot data into a custom Machine Learning model.
- Data Warehouse Integration: Synced HubSpot data to BigQuery for model training.
- Predictive API: Built a Python-based microservice that generates a "Propensity to Buy" score for every new lead.
- CRM Cards: Created a custom CRM extension that shows the ML score and the "Top 3 Reasons" for that score directly on the contact record.
The Result
- 25% Increase in Conversion: Sales reps focused on the top 10% of leads.
- Reduced CAC: Marketing spend was optimized towards channels producing high-scoring leads.
- Better Alignment: Marketing and Sales now agree on what constitutes a "Sales Ready" lead.
Ready to bring AI to your HubSpot instance? Get in touch.