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Documentation Index

Fetch the complete documentation index at: https://docs.usecustory.com/llms.txt

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Metrics are the measurable signals that keep journey work grounded in outcomes. They help answer:
  • Is this problem real?
  • Is it getting better or worse?
  • Did the shipped solution change anything meaningful?

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What belongs in a metric

A strong metric should be understandable without opening another dashboard first. That means it should usually include:
  • What is being measured
  • The unit
  • The current value
  • The direction that indicates improvement

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Metric fields

Metrics support:
  • Description
  • Status
  • Owner
  • Metric type
  • Unit
  • Baseline
  • Current
  • Target
  • Direction

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Metric type

Available types:
  • Customer
  • Business
  • Operational
Use:
  • Customer for experience outcomes such as activation rate or time to first value
  • Business for commercial outcomes such as trial-to-paid conversion or refunds
  • Operational for internal execution signals such as response time or backlog age

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Unit

Available units:
  • %
  • Score
  • Count
  • Time
  • Currency
  • Other

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Baseline, current, and target

These three fields give the metric shape:
  • Baseline: where you started
  • Current: where the metric stands now
  • Target: where you want it to go

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Direction

Choose:
  • Higher is better
  • Lower is better
This matters because a low churn rate is good, but a low activation rate is not.

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Metric statuses

Metrics use these statuses:
  • Draft
  • Defined
  • Active
  • Broken
  • Deprecated
Recommended interpretation:
  • Draft: the team knows this metric should exist, but it is not ready yet
  • Defined: the metric is framed clearly, even if tracking is not fully operational
  • Active: the metric is in use
  • Broken: the metric is unreliable, stale, or currently not usable
  • Deprecated: the metric no longer reflects how the team should measure this area

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How metrics should connect

Metrics can link to: That lets you track:
  • Whether the problem is significant enough to prioritize
  • Whether the chosen solution changed the outcome

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Good metric examples

  • Activation rate within 7 days
  • Median time to first integration
  • Trial-to-paid conversion
  • Weekly billing failure recovery rate
Weak metric examples:
  • Growth
  • Revenue
  • Onboarding
Those are too broad without a defined measurement.

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How to leverage metrics well

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Use one metric to validate the problem, not just the solution

Some metrics help prove that an opportunity deserves attention before work starts.

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Pair outcome metrics with the relevant item chain

When a metric is linked to the opportunity and the solution, the team can review the full reasoning path quickly.

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Mark broken metrics honestly

If a metric is stale, mislabeled, or no longer trustworthy, mark it. Bad metrics create false confidence.

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Common mistakes

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Tracking numbers with no decision role

If the metric does not affect prioritization, validation, or follow-up, it may be dashboard noise rather than journey signal.

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Confusing activity with outcome

Number of tickets created may be useful operationally, but it is not always the best measure of customer improvement.

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Leaving direction implicit

Teams regularly misread metrics when the desired direction is not explicit. Always set it.