Google Sheets / File preparation
Clean a prospect list for Google Sheets
Export a working copy, remove duplicate rows locally, and compare the result in a new sheet without overwriting your source.
The CSV parsing, normalization, duplicate removal and download round trip are covered by automated tests against the files below. The expected result is two retained rows from four input rows. Importing into a live Google Sheets account was not performed for this example.
This worked example uses fictional people and reserved .example domains so you can reproduce the cleanup with the supplied files.
Download input CSV · Download expected output · Open CSV cleaner
1. Export a working copy
From the sheet containing your list, download a comma-separated CSV. Keep the original spreadsheet and its source URLs, observation dates and notes. CSV carries cell values rather than the full workbook’s formatting and formulas; use this workflow for a data table, not as a workbook backup.
2. Normalize the fields you actually use
Open the CSV cleaner and select your email and company-domain columns. Other values are trimmed but not inferred. Domain normalization removes URL paths and the www prefix. Start with Identical cleaned rows so two contacts at the same company remain separate.
3. Read the review report
Download both files. The cleaned CSV contains retained records; the report contains removed rows and warnings with their source row numbers. Resolve invalid addresses and conflicting duplicates against your original sources. No deliverability lookup or company validation is performed.
4. Import into a new sheet
Use Google Sheets’ file import workflow to upload the cleaned CSV into a new sheet or spreadsheet. Check the import options for automatic conversion of text, numbers and dates. Keep identifiers and phone numbers as text where needed, and verify that any leading zeros survived.
5. Compare before replacing anything
With the downloadable fixture, expect two retained rows, one duplicate and one empty row removed. Compare the result with the expected-output file. For your own list, check row counts and a sample of records before using the cleaned sheet for enrichment or outreach.
What this proves
The sample demonstrates repeatable file cleanup: one duplicate and one empty row are removed while the two retained records keep their fields. It does not demonstrate email deliverability, company existence, enrichment accuracy or business outcomes.
Continue with sourced enrichment
When formatting is clean but facts are missing, use AstroFabric enrichment and keep the source evidence with the output. Review results before they reach a live CRM or an outreach system.
Destination reference: Google Sheets data-import guidance. Reviewed September 5, 2026.