Scoring Your ICP

A binary ICP filter (in or out) is a good starting point. A weighted ICP score is what separates good prospecting from great prospecting. It lets you rank a list of 200 accounts by likelihood to buy — so your team works the highest-probability targets first.

The Scoring Model Structure

An ICP score assigns points to each attribute your target account has. The more attributes they match, and the more predictive each attribute is, the higher the score. A simple structure:

• Industry match: +25 points (primary attribute, highest weight)
• Employee count in range: +15 points
• Revenue in range: +15 points
• Technology stack match: +20 points
• Pricing/demo page visit: +30 points
• Return visit (2+ sessions): +15 points
• Funding event in last 6 months: +10 points
• Hiring relevant roles: +10 points

Total possible: 140 points. Threshold for outreach: 50+. Priority queue for same-day outreach: 80+.

Calibrating the Weights

The weights above are a starting point, not gospel. Calibrate them by looking at your last 20 closed-won deals and scoring them retroactively. If the model doesn't put most of your closed-won customers above 70 points, adjust the weights until it does.

Applying the Score in Kopimore

In Kopimore's filter configuration, you can combine multiple conditions using AND/OR logic to approximate a scoring system. Set a filter for: industry matches AND (employee range OR revenue range) AND (page visited is pricing OR return visit). This captures the high-score accounts without requiring a full scoring database.