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CRM data migration starts with a source audit — mapping every object type (contacts, accounts, deals, activities, notes, custom fields) in your current CRM against the target system schema. The specialist identifies fields that do not have a direct equivalent, creates a transformation map for each data type, and runs a test migration on a subset of records to validate accuracy before touching production data. The full migration runs in a maintenance window with the old system still accessible as a read-only backup for 30 days post-migration. You receive a data validation report comparing record counts and spot-checked field values between source and destination.

Yes. A failed migration is recoverable as long as your source system is still intact. The specialist diagnoses the failure point — whether a schema mismatch, character encoding issue, foreign key constraint, or timeout — restores the target to its pre-migration state, fixes the root cause, and re-runs the migration with the corrected configuration. For large migrations, the specialist implements a checkpoint-based approach so if any phase fails, only that phase needs to rerun rather than starting from scratch. You never lose data from the source during a correctly executed recovery.

Post-migration validation uses three methods: record count verification (exact count match between source and target for every table or object type), checksum validation (hash comparison on key fields to detect silent data corruption), and business logic spot-checks (randomly sampled records verified against source for correctness of transformed fields, currency conversions, date format changes). The validation report shows pass/fail for each table with details of any discrepancies found. Discrepancies above the agreed threshold trigger a rollback and re-migration of affected data.

Common migration types include: CRM-to-CRM (Salesforce, HubSpot, Pipedrive, Zoho), ERP migrations (SAP, NetSuite, QuickBooks, Xero), database migrations (MySQL to PostgreSQL, SQL Server to Aurora, MongoDB to Atlas), spreadsheet consolidation (Excel/Google Sheets to a proper database or BI tool), SaaS platform switches (Zendesk to Freshdesk, Notion to Confluence), and legacy system decommissions where data is extracted before the old system is shut down. The specialist is matched based on your specific source and target systems.

Zero-downtime migrations are possible for most systems using a dual-write or blue-green approach. During migration, new data is written to both the old and new systems simultaneously. Once the migration is complete and validated, traffic is switched to the new system with the old system serving as a warm backup. For migrations that require a maintenance window, the specialist calculates the minimum downtime required based on data volume and network throughput, and schedules the migration during your lowest-traffic period. The maximum downtime for a planned migration is communicated in writing before execution begins.