CRM Data Cleanup & Salesforce Data Migration
Duplicates collapse under a written merge rule, ownership is corrected to who works the account, and activity history keeps its real dates. The dataset reconciles against a locked baseline, and the validation that keeps it clean is left in place.
Where the Breakage Shows Up
Duplicates collapse to the wrong record
A merge rule that keeps the newest record discards the one carrying the real history, and the contact that resurfaces three weeks later is the one you deleted.
Activity history stamps the cleanup date
Emails, calls, and meetings land under an admin login on the day the merge ran, so rep activity reporting and pipeline history read as if the relationship started the week you cleaned up.
Ownership rewrites the territory map
Records reassigned to whoever last touched them hand an entire account list to the wrong rep, and the dispute surfaces as a commission correction after the close.
Validation fields stay required
Migration keys and external IDs left required on create screens block the team from saving new records, which is how a technically successful cleanup still stops the sales floor.
The cleanup is not repeatable
A one-time scrub done by hand degrades the moment new records enter, and the dataset you trusted last quarter is back to the same state within two cycles of entry.
How Cleanup Runs
Profile before anything is deleted
Record counts, duplicate clusters, orphan associations, and fields that fire on save are inventoried against the source of truth, because a cleanup run without a baseline reconciles nothing and destroys the only copy of the record that was correct.
Merge rule written and approved
Which record wins on each field, how ownership resolves, and what happens to activity history are decided on paper before the first merge. A merge rule kept in someone's head produces a different dataset every time it runs.
Cleanup against validation gates
Duplicates collapse under the approved rule, ownership is corrected to the rep who actually works the account, and required fields that exist only to feed a migration are retired so the save screen stops blocking new records.
Reconciliation and documented handoff
Counts before and after, the merge log, and the validation rules left in place are documented in language the team reads, so the cleanup is repeatable without the person who ran it.
Data cleanup is one capability inside a wider build; the rest sit on what we build and run in the order the review establishes. Teams moving between platforms can read how a HubSpot to Salesforce migration runs here.
Data Work We Have Run
Photo Agency, 27 Years of History
An external ID field used as migration plumbing was required on create screens, so the team could not save new opportunities. 7,432 calendar events were invisible because import ownership landed on an admin login, 51,555 tasks carried the import date instead of real activity dates, and the Contact Roles picklist held Salesforce stock defaults instead of the 85 values the agency actually uses.
Read the engagementCommercial-Stage Manufacturer
Health authorities were duplicated between two and five times over, a domain auto-association rule was linking contacts to the health authority instead of the hospital they work at, and five active deals including an $81K opportunity had no contact attached at all.
Read the engagementEvery engagement on proof of execution is drawn from engagement records with a verifiable receipt.
What Buyers Ask
What does a CRM data cleanup service include?
Duplicate profiling and merge under a written rule, ownership correction, retirement of validation fields that exist only to block bad data, and a reconciliation against the pre-cleanup baseline. The deliverable is a clean dataset plus the validation that keeps it clean, documented so the team can run it again without us.
How do you clean up CRM data without losing the right records?
Nothing is deleted until the merge rule is written and approved. The rule names which record wins on each field, how ownership resolves, and how activity history is preserved with its real timestamps. A locked export is kept as the baseline, so every change is a diff against something verifiable rather than a guess.
What does a Salesforce data migration include?
Object and field mapping, record load in dependency order with external IDs carried through so associations survive, activity history preserved with real dates and owners, and a reconciliation of counts, ownership, and picklist values against a locked source export. The migration is one capability inside a wider build and runs in the order the review establishes.
How long does a CRM data cleanup take?
Record volume, the number of duplicate clusters, and how much of the object model has to be corrected rather than scrubbed drive the range. The review establishes the scope before any commitment, and the plan names the sequence and the reconciliation gate.
Can cleanup run while the team keeps using the CRM?
Yes, and the risk is drift between the cleanup and live entry. Where parallel work is required, one source of truth is named for each object and the cutover is written down, so new records created during cleanup land in the reconciled dataset rather than recreating the duplicates you just removed.
What does an engagement cost?
Scope and fee are set in writing before any work starts. The 30-minute intro carries no fee, and the paid review is quoted as a fixed amount once its scope is agreed.
How long does it take?
The intro is 30 minutes. The review runs on working sessions with the people who run sales, finance, and operations and ends with written findings. Build sequences are quoted with dates attached.
What happens if it is not a fit?
The intro ends with a direct answer. When the work belongs somewhere else, or when nothing needs rebuilding yet, we say so on the call.
- 238,945Records reconciled
- 27 yearsOf history migrated
- 0Records lost
Client names are withheld. Industry, size, timeline, and metrics are drawn from engagement records.
30 minutes on what to clean, in what order, and what gets retired.