Before migrating to a new CRM, check these five data quality dimensions for every primary object: completeness (are required fields populated?), uniqueness (are duplicates identified?), validity (are email and phone formats correct?), consistency (are categorical values standardized?), and timeliness (are there stale records worth excluding?).
Every CRM migration carries one decision that determines whether the project is a fresh start or a fresh coat of paint on an old mess: do you audit and clean your data before migrating, or do you migrate everything and clean up afterward?
The answer should always be before. Here's why — and what to check.
Why Pre-Migration Cleaning Matters More Than You Think
In your old CRM, you know where the data lives. You know which reports to run, which objects to query, and which problems to look for. After migration, you're learning a new system while simultaneously trying to fix data problems, with users who are already adopting the new platform and encountering bad data.
More importantly: the cost of a data quality failure multiplies post-migration. A duplicate that's easy to merge in your familiar old CRM becomes a complex merge involving unfamiliar new workflows, potential sync errors, and frustrated users.
The Pre-Migration Data Quality Checklist
Contacts and Leads
- [ ] Duplicate detection by email address — merge confirmed duplicates
- [ ] Email format validity — flag or remove records with invalid email syntax
- [ ] Phone format standardization — normalize to a consistent format
- [ ] Required field completeness — flag contacts missing first name, last name, email
- [ ] Stale record review — identify contacts with no activity in 3+ years for archival vs. migration decision
Accounts and Companies
- [ ] Duplicate detection by company name and domain — merge confirmed duplicates
- [ ] Company name normalization — standardize "IBM Corp," "IBM Corporation," "IBM" to one form
- [ ] Website/domain completeness — fill where available from contact data
- [ ] Industry and company size standardization — ensure categorical values map to destination system's approved list
Opportunities and Deals
- [ ] Duplicate opportunity detection — same name + account + close date
- [ ] Close date review — close dates more than 12 months in the past for open opportunities should be reviewed
- [ ] Amount completeness — required for revenue forecasting
- [ ] Stage standardization — map old stages to new CRM stage definitions
Activities and Notes
- [ ] Decide how far back to migrate (typically 12-24 months is sufficient)
- [ ] Verify that activities are associated with the correct contact/account records
[IMAGE: A pre-migration data quality dashboard showing completeness and duplicate counts per object type: Contacts, Accounts, Opportunities]
Frequently Asked Questions
Q: How long should a CRM data quality audit take before migration? Budget 20-30% of your total migration timeline for data quality work. For a 10-week migration project, that's 2-3 weeks of data audit and cleanup. Organizations consistently underestimate this phase and pay for it post-migration.
Q: Should I migrate all historical data or only recent data? Typically only migrate data from the last 12-24 months as active records. Older data can be archived or left in the old system for reference. Reducing migration scope improves quality of the migrated dataset and reduces migration complexity.
Q: How do I handle records in my old CRM that don't map to fields in the new CRM? Document them explicitly in your field mapping. Options: map to a custom field in the new CRM, store in a notes or description field, or exclude from migration (if the data isn't needed in the new system). Never silently drop data without documenting the decision.
Q: What is a field mapping document and why is it critical for migration quality? A field mapping document specifies which field in the source CRM maps to which field in the destination, including any value transformations required. Without it, the migration team makes ad-hoc decisions that produce systematic quality failures.
Q: How do I validate that the migration worked correctly? Compare pre- and post-migration record counts per object. Spot-check 50 records across objects to verify field values transferred correctly. Check that key relationships (contacts associated with accounts, opportunities associated with contacts) are intact.
Q: What should I do with contacts that can't be verified before migration? Create a "Needs Verification" segment in your new CRM and flag these records for post-migration follow-up. Don't delete them — flag them so they don't pollute your active segments while still being accessible if needed.
Q: Is it worth deduplicating contacts who have been in the CRM for 5+ years? Yes — if you're migrating them. Old duplicate records carry old, potentially stale data that can overwrite current data if merged incorrectly post-migration. Deduplicating before migration lets you do it on familiar ground.
Q: How many CRM migration projects fail due to data quality problems? Industry estimates suggest that data quality issues are among the top three causes of CRM implementation challenges. The issues typically surface 3-6 months post-migration, when data degradation becomes visible in report accuracy and user trust.
Q: Should the sales team be involved in pre-migration data cleanup? Yes, for their own records — sales reps are the best judges of which opportunities are real vs. zombie pipeline, and which contacts are active vs. dormant. Build a cleanup sprint into the migration project with a defined deadline for sales-assisted record review.
Q: What's the single most impactful pre-migration data quality action? Contact and account deduplication. Duplicates create downstream problems in every report, automation, and user interaction. Cleaning duplicates before migration prevents the most widespread quality failure in the new system.
A CRM migration is your chance for a clean start. Take it. Audit the data, clean the highest-impact problems, document what's left — and your new system will earn user trust from day one.
[INTERNAL LINK: How to Audit Data Quality Before Migrating to a New CRM] [INTERNAL LINK: Why Merging Two Databases Always Creates Data Quality Nightmares]