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High-volume inbound (messy CRM data)

CRM enrichment that improves data (without making it messy)

Normalization + validation gates so enrichment makes routing/segmentation better—not worse.

Client names withheld by NDA. Details are generalized to protect privacy while preserving the technical and operational shape of the work.

Problem

Duplicates, inconsistent properties, and low-quality enrichment made routing unreliable and segmentation brittle.

Context & constraints

  • Duplicate leads/accounts and inconsistent CRM properties
  • Enrichment vendors produced conflicting or low-confidence data
  • Multiple contributors caused schema drift over time
  • Routing and segmentation depended on clean fields

Approach

  • Define “source of truth” per field and implement normalization rules (not just enrichment).
  • Use confidence thresholds + quarantine to prevent low-quality writes.
  • Monitor write volume, drift, and validation failures so data quality stays stable over time.

What Shipped

  • Enrichment + normalization agent with validation gates
  • Dedupe + merge rules and quarantine for low-confidence updates
  • Property conventions + documentation to prevent schema rot
  • Monitoring + alerts for unusual write patterns

Operational outcomes

  • Field-level ownership and normalization stabilized segmentation
  • Confidence-gated writes prevented CRM pollution
  • Duplicate rate reduced via dedupe/merge rules and quarantine
  • Monitoring caught drift before it broke routing

Governance & Safety

  • Confidence thresholds
  • Manual review for edge cases
  • Backfill strategy + rollback plan
  • Audit logs for updates

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