crm-auditor

Auditing CRM data quality involves scanning configured CRM tabs to identify missing required fields, exact and fuzzy duplicates, stale leads, and invalid emails. The process generates per-record completeness scores and a prioritized cleanup plan with actionable remediation steps.

A stale lead in CRM data is a record that has remained inactive or untouched beyond a defined threshold based on configured CRM stages. It is detected by validating lead status and activity timelines against crm.config settings to flag records needing re-engagement or removal.

Yes, you can automate fixes by applying the audit report's recommendations through crm-writer. This handles cross-tab duplicate resolution and invalid email corrections directly against the configured CRM tabs without manual intervention.

You configure required fields and tabs by defining crm.tabs, crm.required_fields, and crm.stages within the crm.config file. The audit enforces checks against these settings to accurately surface data gaps and score record completeness.

The best way to prioritize CRM data cleanup is using per-record completeness scores and a global data quality grade. This approach ranks remediation tasks across all configured tabs so teams can fix high-impact data gaps and duplicates first.

Yes, CRM duplicate detection supports both exact and fuzzy matching across configured CRM tabs. It identifies cross-tab duplicates by evaluating record similarities and outputs actionable remediation steps within the structured audit report.