Clean CRM contact CSV exports before import

Start with a contact schema

Decide which fields are required before editing values. A typical contact import should have stable headers such as contact_id, full_name, email, company, lifecycle_stage, owner, created_at, and updated_at.

• Normalize headers to one style before mapping fields in the destination system.
• Keep source identifiers whenever they exist; they make future merges safer.
• Do not infer missing emails or names. Leave uncertain values blank and review them separately.

Deduplicate with a clear key

For CRM data, a duplicate row is not always a duplicate contact. Two records can share a company name but represent different people. Use email or source contact ID as the primary key when available.

• Trim and lowercase emails before duplicate checks in your CRM or spreadsheet.
• Review contacts with missing email addresses instead of deleting them automatically.
• Keep one export of removed duplicates for audit and rollback.

Clean status and owner fields

Lead status, lifecycle stage, owner, and region fields are usually used for routing. Normalize spelling and empty values before import so reports do not split the same group across multiple labels.

• Map values such as Active, active, and ACTIVE into one canonical value.
• Turn placeholders such as N/A, null, none, and -- into blank values.
• Validate owner names against a current user list before uploading.

Use the local cleaner

1. Paste a CRM export or load the CRM sample on the main tool page.
2. Keep trim whitespace, normalize nulls, unique headers, and duplicate removal enabled.
3. Run cleanup and inspect changed cells in the preview.
4. Download the cleaned CSV and change log before importing into the CRM.