A CRM migration is not a file import. It is a controlled change to the business’s customer memory. Contacts, companies, opportunities, activities, consent, ownership, attribution, and workflow state have different meanings and dependencies. Moving rows without preserving those meanings creates a cleaner-looking system that the team cannot trust.
Profile the source before designing the destination
Measure record counts, duplicates, empty required fields, invalid formats, unexpected values, inactive owners, orphaned opportunities, and conflicting lifecycle stages. Identify which fields are actively used in filters, reports, automations, and integrations. Interview operators about spreadsheets or notes that compensate for missing CRM structure. This profile becomes the baseline for migration decisions and reconciliation.
Define identity and duplicate policy
Decide how contacts and companies are matched. Email can be a strong contact key but may be shared, absent, or changed; phone numbers require normalization; company names vary. Use a hierarchy of deterministic keys and send ambiguous matches to review. Define which record wins for each field and how activity history is combined. Never merge automatically when the cost of a wrong identity match exceeds the review effort.
Create an explicit mapping specification
For every destination field, document its source, transformation, allowed values, default, and treatment of blanks. Map owners to active users, stages to their new operational definitions, timestamps with time zones, consent without broadening it, and source attribution without overwriting the original. Preserve old identifiers in dedicated migration fields so records can be traced during reconciliation.
If a field transformation cannot be explained in a mapping table, it should not be hidden inside an import script.
Rehearse on a representative subset
Test recent and old contacts, active and closed opportunities, records with rich history, duplicates, missing fields, multiple locations, and unusual ownership. Validate relationships and automation behavior—not just record counts. Keep outbound workflows disabled during rehearsal so test imports do not contact customers or create live tasks.
Control the cutover window
Choose a freeze or delta-sync strategy for changes made after the final export. Back up the source, version the mapping, record import job identifiers, and define rollback criteria. Sequence parent entities before dependent records. Activate integrations and workflows only after data validation. Communicate when teams must stop using the old system and where they should report discrepancies.
Reconcile and support adoption
Compare source, transformed, imported, rejected, and duplicate counts. Sample critical records manually, verify owner totals and pipeline value, and review errors by cause. Maintain a post-cutover issue log with record identifiers and resolution. Train users on new field meanings and stage rules. The migration finishes when the operation is stable, not when the import reaches one hundred percent.