How to score HubSpot leads based on firmographic and technographic fit
Build a lead scoring model that combines company size, industry, job title seniority, and tech stack data to automatically prioritize the best-fit leads in HubSpot.
Why score leads on fit?
Not all leads are equal. A VP of Sales at a 200-person SaaS company is a much better prospect than an intern at a 5-person agency — but HubSpot treats them the same until you score them.
Firmographic and technographic scoring automatically ranks leads by:
- Company size and revenue (does this company match your ICP?)
- Industry fit (are they in a vertical you serve?)
- Title and seniority (are they a decision maker?)
- Tech stack fit (do they use complementary or competitor tools?)
What you'll need
- HubSpot account with API access
- Enriched contact data (job title, company size, industry — see the Apollo enrichment recipe)
- A custom HubSpot contact property for your fit score (number type)
- A defined ICP with scoring criteria and weights
Choose your approach
Select an approach below to see the full step-by-step guide.
n8n
mediumTrigger on enrichment → Code node to calculate score → HubSpot Update
Zapier
mediumContact updated trigger → Code by Zapier scoring logic → Update Contact
Make
mediumWatch Contacts → Router for scoring criteria → Math functions → Update
Agent Skill
lowAgent skill to score or re-score a batch of contacts on demand
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Frequently Asked Questions
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