Skip to main content

Scoring Overview

GTM Clarity uses a two-axis scoring model to evaluate every entity in your pipeline. Each entity receives two independent scores, which combine to determine a tier and prescriptive action.

The Two Axes​

AxisWhat It MeasuresRangeSource
Fit ScoreHow well the entity matches your ICP0--100Account firmographics
Engagement ScoreHow actively the entity interacts with you0--100Multi-channel behavioral signals

These two scores are independent --- a perfect-fit account with zero engagement scores 100 on fit and 0 on engagement. This separation is intentional: it lets you distinguish between accounts that are a great match but have not engaged yet (nurture targets) versus accounts that are actively engaging but may not be a good fit (investigate targets).

Entity Hierarchy​

Scoring flows through a three-level hierarchy:

  1. People are scored individually on both fit and engagement
  2. Accounts aggregate people scores using a configurable rollup strategy (champion, weighted-average, or max-breadth)
  3. Opportunities inherit fit from their parent account and aggregate contact engagement with stage velocity adjustments
Fit Is Account-Level

Fit scoring is based on firmographic data (industry, size, revenue), which belongs to the account. All people at the same account share the same fit score.

Scoring Pipeline​

The complete scoring pipeline runs in this order:

Step-by-Step​

  1. Fit scoring: Each person is scored on four dimensions (industry, company size, revenue, custom attributes) weighted and summed to produce a fit score 0--100. See Fit Scoring.

  2. Engagement scoring: Each person's activity history is processed through the engagement engine, which applies signal quality multipliers, exponential decay for recency, and per-channel caps. See Engagement Scoring.

  3. Account rollup: Person scores are aggregated to the account level using the configured strategy. See Account Scoring.

  4. Opportunity rollup: Opportunity scores inherit account fit and aggregate contact engagement, with a stage velocity bonus or penalty. See Opportunity Scoring.

  5. Tier assignment: The fit and engagement scores are mapped to a quadrant (fast-track, investigate, nurture, deprioritize) with hysteresis to prevent oscillation. See Tier Assignment.

Combined Score​

In addition to the individual fit and engagement scores, a combined score is computed as a weighted blend:

combinedScore = (fitScore * fitWeight + engagementScore * engagementWeight)
                / (fitWeight + engagementWeight)

The default weights are equal (fitWeight: 1, engagementWeight: 1), meaning the combined score is a simple average. You can adjust these weights in your scoring configuration to bias toward fit or engagement.

Score Characteristics​

All scores in GTM Clarity share these properties:

PropertyDescription
Range0 to 100, inclusive
PrecisionOne decimal place (e.g., 72.3)
DeterministicSame input always produces the same output
PureNo side effects --- scoring functions do not read from or write to the database
Tenant-scopedEvery scored entity is tagged with a tenantId
Why Pure Functions?

The scoring engine is implemented as pure functions with zero side effects. This makes scores fully reproducible, testable without a database, and auditable --- you can always explain exactly why an entity received a particular score.