Overview: two different scores
There are two distinct scores you'll encounter in Segmentation, and it's important not to mix them up:
Company score & Tier badge (T1–T4): how well a specific company matches, as a score from 0 to 100, and which fixed band that score falls in
Signal weight (1x to 5x, positive or negative): how much a specific signal counts toward a company's score, when you're fine-tuning a model yourself in Context studio
Company score & Tier badges, what they actually mean
Each company gets a score from 0 to 100 reflecting its fit strength, and a Tier badge (T1–T4).
Important: the tier badge is a fixed quality band, not a rank within the list you're viewing. The tier depends only on the score, so the same score always gets the same tier, in any list or segment. Tiers use the whole number shown next to the badge:
T1: 80 and up
T2: 60 to 79
T3: 40 to 59
T4: below 40
This means two companies with very close scores can still land in different tiers, if they sit on either side of one of those lines. For example, a company with a score of 80 is T1 and a company with a score of 79 is T2. This is expected, not a scoring error.
In Discovery, the score blends two parts: company fit, which is how well the company matches your model, and the segment score, which rates the segment the company belongs to. The Score balance on the Models tab sets how much each part counts. Hover over or click a score to see what it is made of.
How to actually use this:
Trust the score number for how strong a company's fit genuinely is
Use the tier badge as a quick way to group companies by score: T1 is the highest band and T4 the lowest
Companies in the same tier can still have different scores, so use the score to sort within a tier
Signal weights: fine-tuning what matters
When you edit a model manually (in Context studio, duplicate the model and click Edit on the copy), you're setting signal weights, how much a specific signal value should count toward a company's score.
Each signal value you add has two settings:
Positive or negative: choose Add as positive for values that make a company a better fit, and Add as negative for values that make it a worse fit
Strength, from 1x to 5x: a higher level counts for more. 1x is the lowest level, and values above 1x show a badge such as 3x
Example: if you're weighting company size, and your ICP targets 5,000+ employees:
A small size range that is not part of your ICP might be added as negative at 4x, a strong negative signal
A range matching your ideal target closely might be added as positive at 5x, a strong positive signal
The closer a company aligns with your positive values, and the further it stays from your negative ones, the higher its overall company score will be, and the more likely it is to land in a top tier.
Signal weights ≠ company score, and neither is the same as the tier badge. Signal weights are the inputs you control, they define what your ICP model considers important. The company score is the output, the result of a company being evaluated against all your weighted signals combined. The tier badge is simply which fixed band that score falls into.
How the score is calculated
A company's score comes from two parts. Company fit measures how well the company matches the signals in a scoring model that you build in Context studio. The segment score rates the segment the company belongs to, and it comes from the segmentation you set up from a CRM sync, a CSV upload or a pasted domain list. A scoring model is optional: without one, companies are ranked by segment score alone. Each company ends up with a score from 0 to 100, and that score decides its tier. For the full definitions, see Score definitions.
How CRM data is used in segmentation
When segmentation is connected to your CRM, it uses all available data from the connected CRM dataset to build and refine your segmentation model. This includes all objects and fields that are part of the integration scope at the time of syncing.
You can't choose which CRM objects or fields are used, but when you set up a segmentation you can limit it to specific CRM pipelines.
Score distribution view
Discovery shows how companies are spread across tiers in a few places: the Tiers card in a segment's side panel, the tier chips above the Recommendations list, and the tier bar for each model on the Models tab. This helps you understand:
How concentrated your ICP is
Whether your input list defines a narrow or broad profile
How selective your segment results are
The cut-offs (80, 60 and 40) are the same everywhere, but each screen counts a different group of companies. The Tiers card of a segment counts the segment's own companies. The chips above Recommendations count the recommended companies. The Models tab counts a sample of up to 2,000 of your own companies. Compare tier counts only within one screen.
Why scores may change over time
Scores may shift when:
You update your input customer list
You change the signals or weights of a model (a model that a segmentation uses can't be edited, so duplicate it in Context studio, edit the copy, then make it active on the Models tab)
You change the Score balance on the Models tab
You rebuild the segmentation, which also resets the segment score
A company's tier only changes when its own score crosses 80, 60 or 40. Which other companies appear in the same list does not matter.
Key takeaway
The company score measures actual ICP fit strength, that number is what to trust. The tier badge (T1–T4) is a fixed band of that score (T1 is 80 and up, T2 is 60 to 79, T3 is 40 to 59, T4 is below 40), so the same score always gets the same tier. Signal weights are the tunable inputs behind the model, letting you define what a good fit actually looks like. Together, these let you rank companies by relevance, compare leads consistently, and identify strong ICP matches at scale.