Only reach the leads that actually fit

ICP Scoring lets you define your ideal customer profile as a set of weighted attributes, then has AI score every lead against it from 0–100. You can gate any campaign so only leads that clear a minimum score get enrolled, keeping your outreach focused on the accounts most likely to convert.

Job title, seniority, department, industry, company type, company size, location and language out of the box, plus custom attributes like tech stack, team size or an ice-breaker signal. Each attribute can be an exact or lenient match and weighted low, medium or high.

The AI normalises each lead's messy real-world data into a match level per attribute (exact, strong, partial, weak or none), and a deterministic engine turns those weighted matches into a 0–100 score. Because the AI grades and the code does the maths, the same lead against the same ICP always scores the same.

Yes. Every score opens into a per-attribute breakdown showing the match level and a plain-English reason for each, so it's never a black box. Hard-filter attributes (like region or company type) can exclude a lead outright regardless of the rest.

When you add leads to a campaign, turn on “Check ICP score before enrolling,” pick an ICP group, and set a minimum score with a slider. Leads that score below your threshold are skipped automatically, they never receive a message or consume credits.

As many as you like. Create a separate ICP group for each segment you sell to, reuse groups across campaigns, and version or archive them as your targeting evolves.