# When a health score treats unknowns as healthy > An account looks safe because absent inputs are silently ignored or defaulted. Diagnose the cause, choose a bounded correction and verify accounts with current interpretable health evidence. Source: https://saas-marketing.net/guides/customer-health-score-hides-missing-data/ Topic: SaaS Customer Marketing Type: guide Published: 2026-09-17 Last updated: 2026-09-17 Publisher: SaaS Marketing (saas-marketing.net) License: CC BY 4.0. Quote or republish with attribution and a link to https://saas-marketing.net/guides/customer-health-score-hides-missing-data/ ## Short answer An account looks safe because absent inputs are silently ignored or defaulted. Start with this check: Inspect the score's inputs, freshness and treatment of missing values. The corrective action is to expose unknown states and require investigation where material evidence is unavailable. ## Key takeaways - Inspect the score's inputs, freshness and treatment of missing values. - Expose unknown states and require investigation where material evidence is unavailable. - A composite score is an aid to judgment, not a prediction guaranteed to identify churn. - Review accounts with current interpretable health evidence. --- An account looks safe because absent inputs are silently ignored or defaulted. The useful response is a diagnosis that changes a decision, not another report describing the symptom. Use this play with the customer marketing owner and the account’s success or support owner. The working evidence should include current customer outcome, account context and requested participation, with private or sensitive details removed from any shared example. ## Confirm the problem in the actual workflow Inspect the score's inputs, freshness and treatment of missing values. Start with one representative case and follow it from the original action to the reported outcome. Identify where the observed behavior first differs from the intended process. A screenshot of a final dashboard can be useful, but it may hide the source record, a delayed update or a decision made elsewhere. Keep the unit of analysis explicit: an eligible customer account at a defined lifecycle moment. The same label can conceal different populations or stages. Before comparing two results, check that they describe the same kind of work and have had a comparable chance to complete it. ## Separate the visible symptom from the cause Start with the value the customer has actually achieved. Coordinate promotional, educational and service messages so they do not contradict the account’s current situation. Advocacy and expansion should follow appropriate evidence, not simply the passage of time since purchase. The symptom in this case is specific: an account looks safe because absent inputs are silently ignored or defaulted. Ask which piece of evidence would distinguish an operating failure from a measurement failure or a mismatch in the original plan. If the evidence is unavailable, record the missing source and its owner instead of treating the preferred explanation as established fact. ## A situation to work through A broken product-data sync can make a quiet account look stable if the score only flags known negative events. This is an illustrative situation, not a reported client case. Record the equivalent evidence and assumptions for your own workflow. ## Choose the smallest useful correction Expose unknown states and require investigation where material evidence is unavailable. Keep the change narrow enough that the responsible people can implement and inspect it. If a correction changes several things at once, describe it as a combined operating change; do not later claim that one small element caused the whole result. Assign the correction to the customer marketing owner and the account’s success or support owner. Agree which artifact will show that the work is complete. An owner without an observable acceptance condition can close a task while leaving the original problem unresolved. A detailed checklist without an owner creates the opposite problem: the evidence requirement exists, but nobody is accountable for producing it. ## Preserve the important limitation A composite score is an aid to judgment, not a prediction guaranteed to identify churn. This condition belongs beside the recommendation because it can change the decision. It should not disappear when the plan becomes a short presentation or a status update. A customer in an unresolved escalation may need a repair plan before an expansion offer. A customer with a verified outcome may be willing to share a story, but that participation should have a clear scope and remain voluntary. Treat the two situations differently. ## Verification worksheet | Review item | What to record for this issue | Owner | Evidence | | --- | --- | --- | --- | | Observed symptom | An account looks safe because absent inputs are silently ignored or defaulted. | | | | Diagnostic test | Inspect the score's inputs, freshness and treatment of missing values. | | | | Proposed correction | Expose unknown states and require investigation where material evidence is unavailable. | | | | Guardrail | A composite score is an aid to judgment, not a prediction guaranteed to identify churn. | | | | Review measure | Accounts with current interpretable health evidence | | | Download a working copy and follow the [worksheet instructions](/resources/#using-worksheets). Keep unknown facts visible rather than filling gaps with guesses. ## Decide whether to keep, revise or stop the change Review accounts with current interpretable health evidence after the agreed observation period. Keep the correction when the intended behavior is verified and the guardrail remains acceptable. Revise it when the diagnosis was useful but the intervention did not resolve the cause. Stop and reassess when new evidence shows that the original problem was framed incorrectly. Record what changed in current customer outcome, account context and requested participation. This gives the next review a stable starting point and prevents a definition change from being mistaken for a performance improvement. ## Related methods and next steps - [Customer health score: definition and SaaS example](/glossary/customer-health-score/) - [Customer Health Scores for Marketers: Targeting by Risk](/guides/customer-health-scores-for-marketers/) - [SaaS churn reasons: build a reliable evidence set](/research/saas-churn-reasons-study/) - [Churn rate calculator](/calculators/churn-rate/) Return to the [saas customer marketing topic guide](/saas-customer-marketing/), browse its [complete resource collection](/topics/saas-customer-marketing/), or use the [working resource library](/resources/). The [primary reference](https://www.gainsight.com/customer-success/) provides relevant platform or methodological context; the diagnosis and example here are original editorial guidance. ## Frequently asked questions ### What is the first diagnostic check? Inspect the score's inputs, freshness and treatment of missing values. Inspect the actual working record or customer path rather than relying only on a summary report. ### What should change after the diagnosis? Expose unknown states and require investigation where material evidence is unavailable. Record the owner and the evidence needed to verify the correction. ### What limit should the team keep visible? A composite score is an aid to judgment, not a prediction guaranteed to identify churn. A local improvement does not establish a universal benchmark or guarantee a commercial result. ### How should the correction be evaluated? Review accounts with current interpretable health evidence using a consistent unit and observation window. Keep the original evidence and record any measurement changes.