Customer Impact Analysis with SQL
An internal error rate does not establish customer impact. Incident response needs a documented product outcome: checkout failed, export delayed, data unavailable, or another controlled effect that a customer could experience.
Define one impact row
Emit or derive one bounded row per incident and approved reporting unit. Useful fields include incident_id, pseudonymous account_id, plan or service tier, controlled impact_type, affected, impact_duration_ms, environment, and UTC time.
Keep the assessed population as well as the affected population. If a join finds only affected accounts, the resulting percentage has no trustworthy denominator. Avoid customer names, emails, request bodies, support messages, and raw content in the aggregate table. Restrict account-level drill-down to approved responders.
Scope the incident
The customer impact SQL recipe counts assessed and affected accounts by plan, calculates the affected share, and averages duration only for affected rows. Its fixture shows three affected enterprise accounts and two affected starter accounts.
Use the query after service-level detection:
- Verify the incident start and affected product outcome.
- Build the assessed account population for the same complete window.
- Compare impact by plan, region, route, or another reviewed bounded dimension.
- Track newly affected and recovered accounts as separate flows.
- Preserve the query, definition, and result in the incident record.
Do not equate a higher plan with higher human impact without an approved response policy. Plan is one prioritization dimension, not a substitute for contractual or safety requirements.
Verify recovery
Recovery means the customer-visible workflow succeeds again and delayed retries or jobs have drained. A rollback timestamp alone is not proof. Continue watching complete buckets and ensure request volume did not disappear.
The incident_impact_observed event schema provides a field-level starting contract. The incident response guide covers detection, route and release scoping, timelines, and recovery. The API reliability use case provides the broader measurement strategy that can feed impact analysis.