How Many Times Is “[email protected]” in Your List?
You’re about to import 2,000 email addresses into Mailchimp. If there are duplicates, you’ll get billed for each one and your open rate metrics will be skewed. You could sort the list in Excel and eyeball it, but that’s tedious and you’ll miss duplicates with different casing — [email protected] and [email protected] are the same address.
Paste your list here, one item per line. Turn on case-insensitive matching and whitespace trimming. The tool shows you exactly which items appear more than once, how many times each one occurs, and gives you a clean deduplicated list to copy.
Unlike the Duplicate Line Remover (which just strips duplicates silently), this tool gives you the full picture. You might want to know that “[email protected]” appears 7 times — that’s not just a duplicate, that’s a data quality issue in your source system.
Where Duplicates Hide
Case differences. “Apple” and “apple” look different to a naive string comparison but are the same product/category/tag. Enable case-insensitive mode.
Trailing spaces. Copy-pasting from spreadsheets often introduces invisible trailing spaces. “hello” and “hello ” compare as different strings. Enable whitespace trimming to catch these.
Encoding artifacts. Sometimes duplicates come from data merged from different sources where one system added BOM characters or zero-width spaces. Whitespace trimming helps with leading/trailing issues, though embedded invisible characters are harder to catch.
Real Cleanup Scenarios
Mailing list dedup. Before an email campaign, paste your subscriber list and find the duplicates. Import only the unique list. Save money on your email platform and get accurate engagement metrics.
SKU auditing. Your inventory system has 5,000 product SKUs. Paste the column and check for accidental duplicates. Finding that “WDG-001” appears three times means two products got the same SKU — a fulfillment disaster waiting to happen.
Tag cleanup. Your CMS has 800 tags. Paste them in to find that “JavaScript,” “javascript,” and “Javascript” all exist separately. Consolidate them before they confuse your content taxonomy.
Pre-merge analysis. You’re merging two customer databases. Paste the email columns from both and see how many overlap. That overlap count tells you how much deduplication work the merge will involve.
The output shows total items, unique count, duplicate count, and each duplicate with its occurrence frequency. Copy the unique list when you’re done.
For quick dedup without analysis, the Duplicate Line Remover is faster. The List Randomizer shuffles whatever unique list you end up with.
Everything runs in your browser. Customer emails, employee names, whatever you paste — it stays on the page.