Email list cleaner: split names and emails into clean columns
This email list cleaner turns messy contact text into clean columns. Paste lines like "Doe, Jane" <jane@example.com>; Bob Smith <bob@example.com> or upload a CSV, and you get one row per address with email, first name and last name, trimmed and lowercased, with duplicates merged. It runs in your browser and nothing is uploaded.
Sample result
2 contacts cleaned into tidy email, first name and last name columns.
- Contacts
- 2
- From
- "Doe, Jane" <Jane.Doe@Acme.Example>
- Fixed case
- JOHN SMITH to John Smith
What this means for you
Paste a messy recipient list and get columns ready for a mail merge.
- Reads Name <email> and Outlook recipient lists
- Splits names into first and last columns
- Merges duplicate addresses, first row wins
- Optional name guesses from first.last@
- Names
- Cleanup
- CSV
By SimpleVerifier Team · Last updated · Runs in your browser; nothing you paste is sent to us
How do I clean up a messy email list?
- Paste the list: copied Outlook or Gmail recipients, a column from a spreadsheet, a signup export or a CSV file. Files can be up to 25 MB.
- Choose the options. Duplicates are merged and all-caps names fixed by default; guessing names from first.last addresses is off until you turn it on.
- Press Clean the list and check the preview. Rows with invalid syntax are kept and flagged so you can fix them, not silently dropped.
- Download the CSV, with email, first_name, last_name, full_name and domain columns ready to import into a CRM or sending tool.
Example
- You enter
- Pasted Outlook recipients:
"Doe, Jane" <Jane.Doe@Acme.Example>; JOHN SMITH <john.smith@yourcompany.example>. - You get
- A CSV with 2 contacts in email, first_name, last_name, full_name and domain columns: Jane Doe and John Smith, with the all-caps name fixed and both marked as valid syntax.
- Limits
- Runs in your browser with no row cap; an uploaded file can be up to 25 MB.
What is email list cleaning?
Email list cleaning means fixing or removing the addresses on a list that would cause problems when you import or send: bad formatting, duplicates, typos, role and disposable addresses, and mailboxes that no longer exist. It is usually done in that order, cheapest step first.
This email list cleaner does the first step, format: it turns pasted contact text into clean columns, trims and lowercases every address, and merges duplicates. The next steps each have their own free tool: role-based addresses, disposable domains and typo domains. The last step, finding mailboxes that no longer exist, needs an SMTP mailbox check.
What formats can the email list cleaner read?
It reads the Display Name <address> form mail clients use, plus plain lines and CSV rows. Mail clients write recipients as Display Name <address>, the format defined for the From and To headers in RFC 5322. Outlook separates recipients with semicolons and puts "Last, First" names in quotes, so "Doe, Jane" <jane@example.com> becomes first name Jane, last name Doe. Gmail and Apple Mail separate with commas.
It also reads jane@example.com (Jane Doe), plain Jane Doe jane@example.com lines, labels such as To: and Cc:, and lines with several contacts on them. For a CSV with a header row naming its columns, such as First Name, Last Name and Email, it reads the columns directly instead of guessing, and keeps names like Mary Ann together.
Without a header, a CSV row is read by position: the name is the field written next to the address. If your file has headers, keep them; it gives a cleaner result.
What does cleaning change, and what does it leave alone?
It changes formatting only, never the address itself. Every address is trimmed and lowercased, and wrapping such as angle brackets, quotes and mailto: is removed. Duplicates are matched case-insensitively and merged, with a later row allowed to fill in a name the first row lacked. Names written in all capitals or all lower case are converted to title case; mixed-case names such as McDonald or van der Berg are left exactly as written.
Name guessing is off by default because it is a guess. jane.doe@ very likely belongs to Jane Doe, but j.smith@ or a shared sales.team@ does not give a usable name, so only addresses with two alphabetic parts are guessed, and the download marks those rows so you can decide whether to use the name in a greeting.
Addresses that fail a syntax check stay in the output, flagged invalid, because a typo you can see is better than a contact that silently disappears. For a full explanation of what is wrong with each one, run the list through the bulk syntax checker.
Is a cleaned email list ready to send?
Not yet: clean columns make a list importable, but they don't make it sendable. Lists pasted from old threads, events or exports carry addresses that have since been closed, and a CRM imports them as happily as live ones. Before a first send to a list like this, check the mailboxes; how to clean an email list covers the full order of steps.
Can't I just do this with Excel formulas?
For one clean pattern, yes. Pasted recipient lists mix patterns, which is where formulas get long:
| This tool | Excel formulas | |
|---|---|---|
Jane Doe <jane@acme.com> | Email and both names | =TEXTBEFORE(TEXTAFTER(A2,"<"),">") for the email; another formula per name |
"Doe, Jane" <jane@acme.com> | First Jane, last Doe | A separate formula for the reversed order |
| Several contacts in one cell | One row each | TEXTSPLIT, then repeat the above |
JOHN SMITH and McDonald | All-caps fixed, McDonald kept | PROPER fixes the first but turns McDonald into Mcdonald |
| Duplicates | Merged, names filled in | Remove Duplicates, names not merged |
Who uses this tool, and for what?
- Sales ops
- Turn a pasted Outlook thread or event sheet into email, first_name and last_name columns that map straight onto a HubSpot or Salesforce import.
- Recruiters
- Paste the recipients from a long candidate thread and get one row per person with the name split out, ready for an ATS import or a mail merge greeting.
- Marketers
- Fix an all-caps sign-up export, merge the duplicates and keep the names, then filter role addresses before importing it into the email platform.
- Agencies
- Normalise contact lists that clients send in different shapes into one CSV layout before the list goes into a sending tool.
What can’t this tool tell you?
- Names are split into first and last by position: "Mary Ann Smith" with no header becomes first name Mary, last name Ann Smith. A CSV with First Name and Last Name headers avoids this.
- An unquoted "Last, First" name in a comma-separated list, like
Doe, Jane <jane@acme.com>, is split at the comma, so the last name can be lost. Outlook's quoted form is read correctly. - Guessed names come from the address only and are often wrong for shared or abbreviated addresses; they are marked in the download.
- It cleans formatting. It doesn't check whether any address still works.
Common questions
- What is email list cleaning?
- Fixing or removing the addresses on a list that would cause problems: bad formatting, duplicates, typos, role and disposable addresses, and dead mailboxes. This tool handles formatting and duplicates; the other steps have their own tools, and dead mailboxes need a mailbox check.
- How do I separate names and email addresses in a list?
- Paste the list into the cleaner above and press Clean the list. Each address becomes a row with separate email, first name and last name columns, taken from the text written next to it, such as Jane Doe <jane@example.com>. Download the result as a CSV for Excel, Google Sheets or your CRM.
- How do I clean up a list copied from Outlook?
- Copy the recipients from the To or Cc field and paste them in. Outlook's format, with semicolons between contacts and quoted "Last, First" names, is recognised: "Doe, Jane" <jane@example.com> becomes first name Jane, last name Doe, email jane@example.com.
- Does it change the email addresses?
- Only by trimming spaces, removing wrapping like angle brackets, quotes and mailto:, and converting to lower case. The address itself is never rewritten or corrected. Addresses with invalid syntax are kept and flagged so you can fix them.
- Can it guess first names from email addresses?
- Yes, if you turn the option on, and only for first.last style addresses such as jane.doe@ or jane_doe@. Guessed names are marked in the download, because an address doesn't always belong to the person its name suggests.
- How do I clean up email addresses in Excel?
- For one tidy column, =LOWER(TRIM(A2)) in a helper column removes stray spaces and capitals; then use Data, Remove Duplicates. For cells with names, brackets or several addresses, paste the column here instead and download clean email, first name and last name columns.
- Can I clean an email list for free?
- Yes, for the formatting steps. This cleaner, the duplicate remover, the role and disposable filters and the syntax checker are free tools that run in your browser. Checking whether each mailbox still exists is the step that needs a paid SMTP mailbox check.
- Is my contact list uploaded?
- No. Parsing happens in your browser with JavaScript, so contact names and addresses never leave your device. There's no account and no row limit beyond a 25 MB file size.
Sources
A tidy list can still be full of dead addresses.
Extracting, deduplicating and syntax checks all work on the text of an address. None of them can tell whether the mailbox exists. Only the server that hosts it can answer that, through an SMTP check, and that is what the paid product does.
- Upload the cleaned file as it is: CSVs up to 100,000 rows
- A real SMTP mailbox check on every row, with catch-all detection
- Small list? $9 one-time covers 2,500 emails, no subscription
One plan, cancel anytime, no contract. Sign in with Google and your first 100 email checks are free, no card. The free tools stay free either way.