Competitive Customer Health Framework
Gave customer success executives an objective, normalised benchmark for every account — so they could tell at a glance which accounts were onboarding well and which were not.
Fabriq's customer success team was managing accounts without a reliable way to answer the most important question in customer success: is this account performing as expected for where it is in its lifecycle? An account could look healthy in absolute terms while significantly underperforming relative to comparable accounts at the same stage. Without that context, interventions were reactive and prioritisation was largely intuitive.
Design a customer health framework that gave CS executives an objective, normalised benchmark for every account — making at-risk accounts identifiable at any lifecycle stage based on peer comparisons, not just absolute metrics.
The core methodological challenge was defining "comparable". A benchmark against all accounts is meaningless — a large enterprise at month 12 should not be compared against a small team at month 2. The framework controlled for four dimensions simultaneously: industry vertical, geography, time since sign-up (so accounts were always compared at the same lifecycle stage, not calendar date), and account size — with engagement metrics normalised to make them comparable across teams of different scales.
The result was a percentile-based health score for each account: not "how are they doing in absolute terms" but "how are they doing relative to accounts exactly like them, at this exact point in their journey."
- 01Defined the comparability dimensions with CS leadership: industry, geography, time since sign-up, and the normalisation approach for account size.
- 02Built the cohort definition model: for any account at any lifecycle stage, dynamically identify the set of comparable peer accounts against which to benchmark.
- 03Designed the normalised engagement metrics: raw usage metrics scaled by account size to produce comparable engagement rates across accounts of different scales.
- 04Built the percentile health score model: rankings within comparable cohorts at each lifecycle stage, surfacing which accounts were outperforming or underperforming their peer group.
- 05Surfaced the framework within the CS team's operating system, giving account executives percentile health alongside absolute metrics for every account.
- 06Worked with the CS team to calibrate thresholds and define the intervention playbooks triggered by different health score ranges.
- CS executives able to identify at-risk accounts objectively, at any lifecycle stage, against a normalised peer benchmark
- 20–30% increase in account coverage through more targeted, data-driven prioritisation
- Intervention playbooks tied directly to percentile health thresholds, replacing intuition-driven prioritisation
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