How to Extract Email Addresses from a Block of Text
Collecting contacts usually starts with hunting addresses out of a wall of text. Paste the text, run it once, and the matches come back one per line, ready to be cleaned up.
Open the tool：Extract Email Addresses
When you need addresses pulled out
A sign-up form closes and the organiser is left with a block of mixed text: name, phone, email and notes run together. Importing into a mailing list or CRM means isolating the addresses first. A few dozen can be copied by hand; a few hundred is where lines get missed or two records get pasted as one.
The other case is gathering public contacts from pages, forum posts and chat logs into one list, then checking which are still valid and appropriate to use.
- Pulling addresses from sign-up forms or survey results
- Building a contact list from pages or chat logs
- Tidying formats before a CRM import
- Auditing which addresses in an old list survive
What gets found, and what gets missed
Matching is character-based: letters, digits, dots, underscores and plus signs before the @, and letters, digits, hyphens and dots after it. An address such as a.b+c@example.co.uk is caught, while Chinese characters, full-width forms and spaces are not allowed, so an address broken by a space is cut short.
Two traps. First, a trailing full stop is swallowed, so a sentence ending in an address yields x@y.io. rather than x@y.io and needs the dot removed. Second, asset names such as logo@2x.png match the same shape and come back as addresses, which is easy to miss in a long list.
- Dots, underscores and plus signs are supported
- Trailing full stops come along and need deleting
- File names like logo@2x.png are false positives
- Spaces or full-width characters truncate an address
- Duplicates are not merged
What still has to happen afterwards
The tool only pattern-matches. It does not check whether a domain exists, whether MX records point anywhere, or whether the mailbox still accepts mail. Before a list goes anywhere near a send, remove duplicates, cut obvious false positives, and verify deliverability with a real send or a validation service.
Consent matters too. An address scraped from a public page is not permission to mail it, and many jurisdictions restrict unsolicited commercial email. Processing happens locally in the browser and nothing is uploaded, but that says nothing about whether you may contact the people on the list.
- Deduplicate and remove false positives first
- No domain or deliverability validation
- Confirm consent and an unsubscribe route before sending
- Processing is local; nothing is uploaded
FAQ
Why were some addresses not found?
Common causes are an address broken across a newline or by a space, full-width characters, symbols the rule does not allow, or an empty part before the @. Find the address in the source, add it by hand, and check whether the copy was already broken.
Can I email the extracted list directly?
Not advisable. Remove duplicates and false positives, confirm each address works, and make sure the recipients agreed to hear from you. Unsolicited commercial mail is restricted in many places and can also breach your provider's terms, putting a domain or account at risk.
Why does an image file name look like an email address?
Because logo@2x.png has the same shape: characters, an @, then a dotted domain. The rule cannot tell it apart from a real address. Such false positives usually contain a fragment like @2x or @3x, so check those first and delete them from the list.
Related tool：Extract Email Addresses