Data Quality Audit

Find and fix CRM hygiene issues before they corrupt your reports

20 minutesManual: 4-6 hours

Scans CRM data for completeness, consistency, and accuracy issues. Identifies missing required fields, inconsistent picklist usage, orphaned records, and stale data. Produces a prioritized remediation plan ranked by downstream impact.

Workflow Steps

1

Schema Review

/revops

Map required fields and validation rules across objects

2

Completeness Scan

/excel-work

Calculate fill rates for every field, flag those below threshold

3

Consistency Check

/synthesize-knowledge

Identify duplicate records, conflicting values, and picklist drift

4

Impact Assessment

/chief-of-staff

Rank issues by how they affect reporting, routing, and automation

5

Remediation Plan

/deep-planning

Prioritized fix list with owner, effort, and expected improvement

Example

CRM audit of 3,200 contact records. Finds 22% missing industry field (breaks routing), 340 duplicate accounts (inflates pipeline), 15% of opportunities missing close date (breaks forecasting). Remediation plan: bulk industry enrichment first (highest reporting impact), then dedup with merge rules, then close date enforcement via validation rule. Systematic data hygiene is a pillar of AI-driven GTM strategy.

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Built and maintained by Victor Sowers at STEEPWORKS