How to clean and verify an email list CSV
A reliable CSV workflow starts by choosing the correct column and ends by reconciling every row. Do not use a broad email-extraction regex as a substitute for parsing a tabular file: it can pull addresses from details, hide malformed entries and lose the relationship to the original records.
Open the relevant free tool →Preview the column before checking the list
Prepare the file
Export a small set of necessary fields, ideally including a stable record identifier and the email column. Keep the original export unchanged. Check whether the first row contains headings. Quoted fields may include commas or line breaks, so a simple split on commas is not a complete CSV parser.
Choose the email column explicitly
Upload the CSV and inspect the column preview. In EmailValidly, select the email column and indicate whether the first row is a header. This avoids accidentally checking an address mentioned in a note or another contact field. If you paste addresses instead, put one destination on each line so errors are easy to see.
Understand the free batch boundary
The public bulk tool checks up to 100 unique addresses within its daily allowance. If a file contains more, review the explicit first-100 choice. Do not assume the rest were checked. Account workspaces can save supported uploads, and paid plan limits are shown separately. Keep the checked count with your export so partial work is not mistaken for a complete cleanup.
Review results before importing
Keep invalid, risky and unknown results distinct. An unknown mailbox is not automatically a bad contact. Download the result CSV and compare the number of checked addresses with the intended input. The free result export contains verification fields, not every original CRM column; join it back carefully rather than replacing your customer table wholesale.
Protect the original record context
Preserve source, consent and suppression state during the join. Do not reactivate an unsubscribed contact because verification passed. Review corrected addresses before applying them. If spreadsheet software interprets a entry as a formula, keep the export’s protective quoting or import the column as text. Finally, retain a brief update log so you can explain which records were removed, corrected or left for review.
Put it into practice
- Keep the source file unchanged.
- Select the intended column and header setting.
- Check the exact batch and output counts.
- Join results without erasing consent or suppression.