An ideal customer profile describes the companies you most want to sell to. Fit scoring applies it to real prospects: each candidate is checked against the profile’s attributes and gets a score or grade reflecting how well it matches.
A simple version works like this:
- List the attributes that define the ICP: industry, size, geography, business model, tools in use, trigger events, and the role you want to reach.
- Weight them. Some are requirements (wrong country, no deal), some are strong signals, some are nice to have.
- Check each prospect against each attribute, from public information or data providers.
- Show the reasons alongside the score. “Strong fit: right size, uses the tool you integrate with, hiring a security lead” is something you can check and use in the first message. “82” is not.
The reasons matter for two practical reasons. They let you catch scoring mistakes at a glance, because a wrong reason is obvious in a way a wrong number is not. And they are the raw material of the first message, since the reason a company fits your profile is usually the reason you are writing to them.
Fit scoring improves most from the prospects you reject. When you review a list and turn down a well-scored candidate, the reason (“they outsource this entirely”, “they are an agency, not an end customer”) is usually an attribute missing from the ICP. Feed those reasons back into the profile and the next list is better.
If you run several motions, each has its own ICP and therefore its own scoring. The same company can be a strong fit for one motion and a poor fit for another.