Updated
Each person gets a score from 0 to 100 for each ideal customer profile in your workspace. Next to the score you see every criterion, whether the person matched it, and how many points it added. Nothing in the score is hidden.
What is scored
| Criterion | Matches when |
|---|---|
| Job function | Their title points to a function you chose, such as engineering or marketing. |
| Seniority | Their title points to a seniority you chose, such as founder or director. |
| Country | They, or their company, are based in one of your countries. |
| Company size | Their company's employee count is inside your range. |
| Keywords | One of your keywords appears in their title, their company name or the public posts we found. |
| Recent activity | They showed a signal in the last 30 days. Asking for a tool like yours, complaining about a competitor or changing jobs earns full points; describing the problem you solve earns two thirds; other activity, such as a like or a follow, earns a third. |
A criterion you leave empty isn't counted at all, so it can't pull scores down.
How the points add up
Each criterion has a weight: the points it is worth. A person earns the full weight for a criterion they match and nothing for one they don't. The score is the points earned as a share of the points possible.
Say your profile targets engineering leaders at companies of 10 to 200 people in the US and Canada, with the keyword “kubernetes”. A head of engineering at a 40-person company in Toronto liked your launch post two days ago:
| Criterion | Weight | Result | Points |
|---|---|---|---|
| Job function | 30 | Engineering, matched | 30 |
| Seniority | 20 | Head of, matched | 20 |
| Country | 10 | Canada, matched | 10 |
| Company size | 20 | 40 employees, matched | 20 |
| Keywords | 10 | None found | 0 |
| Recent activity | 10 | Liked your post, matched | 10 |
They earn 90 of 100 possible points, so their score is 90.
Missing data scores zero
If we don't know someone's title or company size, that criterion earns no points, and the breakdown says “Company size unknown” instead of guessing. Finding a verified email or company details often raises a score, and you can see exactly which criterion moved.
Change the weights
Open your ideal customer profile and change any weight. Set a weight to zero to ignore that criterion. People are rescored with the new weights, and the breakdown shows the new numbers.
What the score doesn't do
It only uses the public data and the criteria shown in the breakdown. It ranks people so you can decide who to contact first; it doesn't contact anyone.