How Company AI Insights Work

This article explains how the AI-generated scores and insights on a company record are calculated.

Fit Score

What it measures: How well a company matches the ideal customer profile.

How it's filled:

Until an ICP is configured, Fit Score is calculated using default parameters:

• Industry or domain
• Company size (employees)
• Revenue
• Geography — same country or region as the user
• Segment — SMB, Midmarket, or Enterprise

The first time a company is scored, a tooltip prompts teams to customize their ICP in Settings for more accurate scoring.

Once configured, teams can define their own attributes, apply operators and rules, and assign High, Mid, or Low priority to each attribute. Priority determines how much each field impacts the overall score. If a field is missing on a company, the score is normalized based on the available fields.

Engagement Score (Max.)

What it measures: The highest engagement score among all contacts associated with the company.

How it's filled:

Rather than averaging engagement across contacts or picking the senior-most title, the score displays the maximum engagement score found on any associated contact. This avoids ambiguity around whose engagement to represent at the account level.

The score itself is displayed without naming the contact it belongs to.

Buying Intent

What it measures: Purchase intent across the account, shown at the contact level rather than aggregated.

How it's filled:

Every activity logged against any associated contact — emails, calls, meetings, and deal activity — is analyzed and classified as a High, Mid, or Low intent signal. Each signal is displayed with the contact who generated it, that contact's designation, their buyer profile (if available), and the intent level.

A single contact may show multiple signals. The insight lists all of them.

Competitor Mentions

What it measures: References to competitors detected in communications across the account.

How it's filled:

The AI scans emails, call transcripts, and meeting transcripts for competitor names. Each mention is logged with:

• Which competitor was mentioned
• When it was mentioned
• The source (email, call, or meeting)
• The relevant excerpt or quote

Company Signals

What it measures: Recent organizational changes that may affect the account.

How it's filled:

The AI monitors public and enrichment data sources for:

• Recent hires
• Leadership changes
• Investments or funding rounds
• Layoffs
• Role changes among associated contacts — including promotions, internal moves, or job switches to other companies

Each signal is displayed with the contact name (if a specific person is involved) and the source of the news. If no changes are detected, the insight shows NA.

Buying Committee Analysis

What it measures: The composition of the buying committee across the account.

How it's filled:

Each associated contact is classified along three dimensions based on their designation, title, and meeting transcript signals.

Buyer type:

• Finance — controls budget, approves final decisions
• Technical — reviews technical fit, integration, and compliance
• Legal — responsible for security and legal compliance
• Decision Maker — highest hierarchy or most engaged
• Influencer — provides recommendations without final say
• Gatekeeper — controls access to decision-makers

Decision-making power: High, Mid, Low, or NA — based on role.

Focus area:

• Legal or Compliance
• Technical or IT
• Procurement or Finance
• Operations or Process
• Marketing or Sales Enablement
• Product or Innovation
• Executive or Strategic

Similar Customers

What it measures: Existing customers with attributes comparable to this company.

How it's filled:

The AI matches the company against existing customer accounts on:

• Industry
• Region
• Sub-industry
• Parent company
• Shared problems — inferred from meeting transcripts and notes

Each match is displayed with the company name, logo, similarity dimension, associated deal name, and deal status (Closed Won or Closed Lost).