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Data Quality

Find the record problems that change downstream decisions.

VehicleDesk surfaces import confidence, provenance, duplicate candidates, contact quality, malformed fields, and linkage gaps so staff can review possible corrections before relying on a queue, relationship, or report.

Explore a demo Available / review first
Current VehicleDesk interface · Synthetic demo data, not customer results.
VehicleDesk data-quality workspace with synthetic provenance, duplicate, contact, and linkage findings
Import confidence and source provenance
Duplicate, contact-quality, and linkage findings
Preview-oriented correction and merge review

How it works

Prioritize, prepare, and track the next staff action.

The feature stays connected to source context and makes each staff-controlled transition visible.

01

Prioritize

Rank findings by workflow impact.

Missing vehicle links, uncertain contact points, duplicate candidates, and stale source evidence have different consequences for daily work.

02

Trace

Keep the source and related records visible.

Import run, mapping, timestamp, provenance, and downstream relationships explain where a finding came from and what it affects.

03

Review

Preview the correction before any action.

Possible duplicate or merge outcomes remain inspectable and do not become destructive automatic cleanup.

Connected workflow

Data quality governs every downstream workflow.

Findings connect the import boundary to customer and vehicle records, staff queues, controlled communications, and reporting interpretation.

Shopmonkey and sync health

Inspect import runs, mappings, quota, errors, freshness, and source authority.

Explore the connection

Customer and vehicle records

Review how duplicates, contact points, ownership, and linkage affect the relationship view.

Explore the connection

Communication compliance

Keep uncertain or suppressed contact points from becoming eligible merely because a message was drafted.

Explore the connection

Limits and trust

Important boundaries stay beside the feature claim.

No destructive automatic merge

The current workflow identifies and previews findings; it does not advertise irreversible autonomous cleanup.

Confidence is evidence, not certainty

A score or healthy connection cannot replace source coverage review for the specific business decision being made.

Practical workflow review

Review the data-quality evidence your workflows need.

Preview the workflow-review agenda, current product scope, safety boundaries, and implementation questions before public requests open.