How to Extract Contact Details From Email Signatures

Every business reply you get ends with a small, structured contact record: the signature block. It usually lists a name, a job title, a company, a direct phone number, an email, and often a website. That is exactly the data a sales or recruiting team spends hours retyping into a spreadsheet. Here is how to pull those details out of email signatures automatically, so a folder of replies becomes a contact list instead of an afternoon of copy and paste.

Last updated July 2026.

How do I extract contact details from an email signature?

To extract contact details from an email signature, connect the mailbox to a parser, name the fields you want (full name, job title, company, phone, and email), and let it read each message. The parser looks at the signature block in the body, maps those values to columns, and writes one contact per email. You export the result as Excel, CSV, or JSON, or send it straight to your CRM, instead of opening every message and typing the details by hand.

Can you pull contact info from an email automatically?

Yes. Because a signature is text at the bottom of the message body, a parser can read it and pull the fields out on its own, with no manual copying. You define the fields once, and every email you run through the parser produces the same columns. The work shifts from reading and typing to a quick review, which is where the time saving comes from when you are processing hundreds of messages.

How do I turn email signatures into a spreadsheet?

Point the parser at a Gmail, Outlook, or IMAP folder, or upload the emails as .eml or .msg files. Choose which signature fields become columns, then run the folder. Each message is written as a row with the name, title, company, phone, and email in their own cells, and you download an .xlsx workbook, a CSV, or JSON. Because the field mapping is saved, the same export runs again whenever new replies arrive.

What fields can you get from a signature?

Most signatures carry a predictable set of details, and each can become its own column:

Does it work with HTML signatures that have logos?

Yes. A styled HTML signature with a logo image and linked social icons is still text and markup underneath, and that is what the parser reads. It pulls the name, title, phone, and email from the HTML the same way it does from a plain-text signature. The logo image is treated as content rather than a field, so it does not end up in your contact columns. If a sender attaches a vCard (.vcf) file, MailParse records that attachment by filename, type, and size; the fields it extracts come from the signature text in the message body, and reading the contents of an attached file is a separate document extraction step.

Is signature parsing the same as email scraping?

No, and the difference matters. An email scraper harvests addresses in bulk from web pages or an entire mailbox, usually with no structure and no context about who the person is. Signature parsing works on emails you actually received and maps the real fields in each signature into columns, so you get a sourced, structured contact record rather than a raw list of addresses. Each contact keeps the sender, subject, and date of the message it came from.

Putting the contact list to work

Once the signatures are parsed, the export is ready to import into your CRM through the email to CRM workflow, or to keep as a spreadsheet with the email to Excel route. Sales teams often feed a fresh, structured contact list straight into their personalized outreach sequences, so the details you captured turn into a first touch without a second round of data entry. To read what MailParse can and cannot pull from a message, see what data you can extract from an email, and to start now, map your fields on the email signature parser page.