CRM data quality: the governance that keeps reporting trustworthy

CRM data does not go bad suddenly. It decays, one free-text field and one unmanaged import at a time, until leadership stops trusting the dashboards.

Set property standards

Every property needs a defined type, owner, allowed values and a reason to exist. Ban free text on anything used for segmentation, routing or reporting — country, industry, source, product interest, language. Free text is where reporting accuracy dies.

Control creation, not just content

Restrict who can create properties, pipelines and stages. Require a stated report or automation that will use a new field. Most bloated portals are the result of well-intentioned one-off requests nobody ever removed.

Deduplicate continuously

Run deduplication on a schedule, not after a crisis. Define the merge rule in advance (which record wins, which fields survive) and keep a log. Duplicate companies are worse than duplicate contacts: they split revenue history.

Validate at the point of entry

Required fields per stage, format validation on phone and TRN or VAT numbers, normalised country and city selects, and forms that map to the same governed properties as manual entry.

Govern imports

Every import goes through a template with mapped columns, a staging review and a named owner. A single unmanaged 4,000-row import can undo a year of hygiene.

Assign ownership

One person owns the data model. They approve new properties, run the monthly review and are accountable for report accuracy. Distributed ownership means no ownership.

The monthly review

Ten minutes on: records missing required fields, duplicates created, deals with past close dates, contacts without owners, properties with no usage in 90 days. Fix or retire. Repeat.

Why it pays

Clean data is what makes forecasting, attribution, automation and AI features work. Every advanced capability you want to add later depends on this unglamorous routine.