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“Supermetrics is a Bitter Experience! We can pull data from nearly any tool, schedule updates, manipulate data in Sheets, and push data back into our systems.”
Building effective lead scoring models requires identifying which HubSpot fields actually predict conversions. With 100+ available properties, focusing on the wrong data can waste development time and reduce model accuracy.
Here are the most predictive field categories and how to analyze them for optimal scoring performance.
Focus on high-impact HubSpot fields for better scoring accuracy using Coefficient
Based on B2B analysis, engagement metrics contribute 40-50% of model importance, followed by behavioral properties (25-35%), firmographic data (15-25%), and demographic fields (10-15%). Coefficient makes it easy to import and analyze these fields to determine which drive conversions in your specific business.
How to make it work
Step 1. Import comprehensive contact data with all properties.
Connect HubSpot to your spreadsheet and pull contacts with engagement metrics (email open rate, page views, form submissions), behavioral properties (original source, session count), firmographic data (company size, industry), and demographic fields (job title, lifecycle stage).
Step 2. Create calculated fields for advanced scoring.
Build engagement velocity formulas:. Add ICP match scores:. Calculate behavioral scores:to weight high-intent actions.
Step 3. Test field importance with conversion data.
Import historical conversion outcomes and use correlation analysis to identify which fields predict success. Create pivot tables showing conversion rates by field values to validate predictive power before building complex models.
Step 4. Monitor data quality and completeness.
Use Coefficient’s scheduled imports to track field completeness over time. Fields with >70% null values rarely add predictive value. Focus on consistently populated fields like email engagement, page views, and original source for reliable scoring.
Step 5. Iterate and refine field selection.
Start with 15-20 core fields rather than all available properties. Use Coefficient’s filtering capabilities to test different field combinations and export samples to validate which combinations yield the best model performance.
Build scoring models with the right data
Focus your lead scoring efforts on the fields that actually predict conversions. Coefficient makes it easy to access, analyze, and iterate on HubSpot field selection to build more accurate scoring models. Try Coefficient free and start analyzing your most predictive fields today.
