Segmentation uses a unified scoring system to measure how closely each company matches your Ideal Customer Profile (ICP).
This page explains how the score is calculated, what the ranges mean, and how to interpret results correctly.
🔢 Overview of the scoring system
Every company in Segmentation receives a fit score between ~200 and ~760.
This score represents how closely the company matches the profile learned from your uploaded customers.
The scoring system is:
Globally consistent across all users and datasets
Standardized, meaning the same score always represents the same level of ICP fit
Comparable, allowing you to benchmark companies across different segments
📊 Score interpretation
Scores are grouped into fixed tiers to make interpretation easier:
Excellent: ≥ 657
Good: 551–657
Fair: 445–551
Poor: 339–445
Very Poor: < 339
What this means in practice
A score of 657+ indicates a strong ICP-level match
A score around 500 indicates a moderate or partial match
Lower scores indicate weaker alignment with your ideal customer profile
These thresholds are fixed and apply across all segments and users.
🧠 How the score is calculated
The score is based on how closely a company matches patterns learned from your uploaded customer list.
When you create a segment, the system builds a model of your ICP using multiple signals, including:
Industry and business model
Company size and growth stage
Keywords and positioning
Technology usage
Hiring and growth indicators (when available)
Geographic and market signals
Each company is then evaluated against this model and assigned a similarity score.
🧠 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.
At the moment:
The system does not support selective field or dataset scoping
The full connected CRM dataset is used as input for segmentation
This ensures the model has a complete view of your customer base when building your ICP.
⚖️ Trait weights vs. company score
It’s important to distinguish between two concepts you may see in the interface:
Trait weights
Trait weights (e.g. 60, 43, 38) represent how important or common a characteristic is within your uploaded customer set.
They help define your ICP model by identifying:
Which attributes your best customers share
Which signals matter most in your segment
Company score
The company score (200–760) shows how well a specific company matches that ICP model.
In short:
Trait weights = what defines your ICP
Company score = how closely a company fits that ICP
📐 Global vs. segment-relative scoring
Segmentation uses a global scoring system, not a per-segment ranking.
This means:
Scores are consistent across all segments
A “657” represents the same level of ICP fit everywhere
Scores are not recalculated or re-normalized per upload
This ensures that results are comparable and stable over time.
📌 How to use scores effectively
Scores are designed to support prioritization, not strict filtering.
Recommended usage:
657+ (Excellent): prioritize for outreach or targeting
551–657 (Good): strong candidates worth reviewing
445–551 (Fair): secondary or exploratory leads
Below 445: lower relevance for most ICP-based campaigns
Rather than using hard cutoffs, we recommend combining score tiers with your own sales or marketing strategy.
📊 Score distribution view
Segmentation also provides a score distribution panel that shows how companies in your results are spread across score ranges.
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
🔄 Why scores may change over time
Scores may shift when:
You update your input customer list
You adjust trait weights or signals
New data is added to the underlying company database
The model improves with better signal extraction
This ensures segmentation stays aligned with the most up-to-date company data.
🧩 Key takeaway
The Segmentation score is a standardized measure of ICP fit, built from multiple company signals and calibrated globally across all data.
It allows you to:
Rank companies by relevance
Compare leads consistently
Identify strong ICP matches at scale