How to score HubSpot leads based on firmographic and technographic fit

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. Without scoring, reps waste 30-50% of their time working leads that will never close, while high-fit prospects sit in the queue unnoticed.

Firmographic and technographic scoring automatically ranks leads by how closely they match your ideal customer profile:

• 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?

Teams that implement fit-based scoring typically see 20-30% higher conversion rates from MQL to opportunity because reps focus on the best-fit leads first.

How it works

Regardless of which tool you use, every approach follows the same pattern:

1. Trigger on enrichment — when a contact's firmographic or technographic data is updated (via Apollo, Clearbit, or manual entry), trigger the scoring workflow
2. Calculate a weighted score — evaluate the contact against your ICP criteria: company size (0-30 pts), industry match (0-25 pts), seniority (0-30 pts), and tech stack or source (0-15 pts), capped at 100
3. Write the score to HubSpot — update a custom icp_fit_score property on the contact record so reps can sort and filter by fit

The approaches below differ in trigger mechanism (event-driven vs. batch), flexibility (fixed weights vs. conversational adjustment), and cost.

Which approach should I use?

• n8n (Recommended) — triggers on contact property changes and scores immediately. Visual workflow builder makes the scoring logic transparent. Free when self-hosted; $24/mo on n8n Cloud.
• Zapier — similar trigger-based scoring with a Code by Zapier step for the scoring logic. Best if you already use Zapier. $20-50/mo.
• Make — visual scenario with Router modules for scoring criteria. Best if you prefer Make's UI. $10-29/mo.
• Code + Cron — Python script running on a schedule. Most control over the scoring model, but you maintain the code and hosting. Free.
• Claude Code — a guided Claude Code skill for on-demand scoring. Best when you're testing scoring models, need to re-score after changing weights, or want to analyze scoring distribution conversationally.

What you'll need

Choose your approach

Select an approach below to see the full step-by-step guide.