What workarounds did people try for "How to clean up messy CRM data after importing"?

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Community members documented 45 workarounds:
1. defining lifecycle stages before building automation
2. cleaning data before importing
3. getting internal alignment on lead definitions
4. writing a one-pager of the funnel
5. standardizing properties early
6. deduping on email and company domain
7. scheduling a weekly merge review
8. Manually auditing and deleting junk data
9. Rebuilding pipelines and simplifying automations
10. Merging duplicate contacts
11. Using third-party data validation tools to screen incoming contacts automatically
12. Centralizing research, list logic, and enrichment outside the CRM using tools like Clay before pushing structured records in
13. Locking down record creation permissions so only admins and operations staff can create new company records
14. Running weekly deduplication audits and manual cleanup reviews
15. Building internal hygiene dashboards to surface stale deals and missing values for visibility
16. Using Add/Edit Multiple List Entries to paste from Excel
17. Fixing names outside the software before importing
18. Using batch update tools or IIF/SDK importers
19. Using the most recent lead as fallback logic
20. Having sales reps manually choose which record to map activities to
21. Aggregating all info onto a single record in the secondary platform
22. Catching and cleaning them up manually when noticed
23. Setting up rules to prevent duplication of email and/or phone numbers
24. Using tools to find and merge duplicates
25. Employing a deterministic identity order before a merge and avoiding auto-merging on name alone
26. Hiring an external agency or HubSpot partner to do the audit and cleanup
27. Fixing broken components yourself or leaving tedious and risky parts untouched
28. Trying to figure out where phone validation should happen in the process, such as contact creation, before assignment, or during sales outreach.
29. Experimenting with using AI to assist with auditing and researching records
30. Considering bulk-deleting or overwriting records
31. Opening the existing contact and adding another deal directly in the deals section
32. Merging duplicate contact records rather than deleting them
33. Routing all raw leads into a temporary staging list to deduplicate before they hit the main database.
34. Stamping every imported row with a batch ID, source, and date to allow for easy bulk deletion if the list is bad.
35. Setting automatic enrichment tools to 'fill blanks only' so they never overwrite fields typed by a human.
36. Normalizing data (lowercasing, stripping email plus-tags, matching on domain) before attempting to merge records.
37. Writing a custom Python script to check for matching emails and flag records with over 95% similarity.
38. Asking Account Executives what workflows they actually use and deleting the rest.
39. Hiring an external vendor or consultant to run an audit.
40. Using a platform migration as an opportunity to scrub tables and transform fields.
41. Running massive, stressful cleanup projects right before reporting season or quarterly audits.
42. Replacing free-text fields with mandatory dropdowns to enforce data validation at the point of entry.
43. Assigning one specific person to do a 15-minute weekly spot check or review of records missing basic information.
44. Setting up automated workflows or "self-cleaning lists" to flag records that haven't had a real interaction (call or email) recently.
45. Migrating only the fields actively used in reports when fixing old data and dumping the rest into a legacy text field.

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