The Contact Data Problem
Contact information exists in structured form — a CRM database, a properly formatted CSV — and in unstructured form — the body of an email, the footer of a signature, the HTML of a company directory, the text of a LinkedIn message export. The structured form is easy to work with. The unstructured form requires extraction before it can be used.
The gap between these two forms is where hours of manual work happen. Someone collects 200 business card photos at a conference, OCRs them, and then manually copies name, email, phone, and company into a spreadsheet. A sales team receives a batch of email replies and copies contact details one by one into HubSpot. A developer scrapes a company directory and writes a one-off script to parse the contact fields — differently formatted for every site.
The Contact Info Extractor automates all of this in a single client-side tool. Paste any amount of unstructured text containing contact information and it simultaneously extracts all five contact fields — email, name, phone, company, and address — groups them into structured contact records, shows field coverage across the entire batch, and exports in CSV, JSON, or vCard format. No server, no API key, no script to write.
Extract structured contact records from any text
Paste email signatures, HTML directories, CSV exports, or any text with contact information. The extractor pulls all five fields at once, groups them into contact records, shows field coverage, and exports as CSV, JSON, or vCard .vcf — ready for CRM import.
Open Contact Info ExtractorHigh-Value Use Cases and How to Approach Each
- 1
Batch email signature extraction
Select multiple emails in your email client, forward them to yourself or export them, copy the full body text, and paste into the extractor. Separate each signature block with a blank line if they aren't already. The extractor identifies name, email, phone, title (used as a company hint), and company from each signature block. Export as CSV and import the email column to your CRM, with name and company as additional fields.
- 2
Company directory extraction
Open the company directory in your browser, right-click → View Page Source, select all, copy. Paste the full HTML source into the extractor — it strips HTML tags before parsing, so the structured text content is analyzed. Directories with consistent markup (each contact in a div or list item) produce very high accuracy. The extractor finds name, email, phone, and title/company from the text content of each block.
- 3
Trade show badge scan / OCR results
Badge scanners and mobile OCR apps produce text that looks like: 'John Smith, VP Sales, Acme Corporation, john.smith@acme.com, (415) 555-2671'. Paste a batch of these outputs (one per paragraph) and the extractor structures them into a table. Accuracy is typically very high because badge scan exports are consistently formatted.
- 4
LinkedIn message or profile exports
LinkedIn allows data export (Settings → Get a Copy of Your Data) which includes messages and connections with names and emails. Paste the exported text content into the extractor to get a structured table. For individual profile pages, copy the page content (not HTML source — use Ctrl+A, Ctrl+C on the rendered page) and paste it to extract the visible contact information.
- 5
Preparing a CRM import
After extraction, use the field filter to show only contacts with email addresses (the minimum for a meaningful CRM record). Use the confidence score to identify records that need manual review. Export as CSV and check the column headers match your CRM's import format. Most CRMs accept: email, first name (parsed from name), last name, phone, and company as standard import columns — you may need to split the full name field after export.
Frequently Asked Questions
How accurate is the contact grouping?
+
Grouping accuracy depends on how clearly the input separates contacts. Well-formatted email signatures (separated by blank lines or signature dividers like '--') produce accurate grouping because each block clearly belongs to one contact. Dense mixed text with multiple contacts per paragraph produces lower accuracy — some fields may be attributed to the wrong contact. The confidence score reflects field completeness, not grouping accuracy, so always review before importing.
What happens when a contact has no email address?
+
The extractor requires at least an email address OR a phone number to create a contact record — blocks with only a name and company but no contact detail are not returned as records, since they can't be meaningfully actioned. If you see contacts missing from the output, check whether their blocks contain either an email or phone number.
Can I extract contacts from PDF files?
+
Not directly — PDFs need to be converted to text first. Copy-paste from a PDF viewer works for text-based PDFs (not scanned images). For scanned PDFs, run them through an OCR tool first (Adobe Acrobat, Google Docs, or a dedicated OCR service), copy the OCR output as plain text, and paste into the extractor.
How do I split the full name field into first and last name for CRM import?
+
After exporting as CSV, open in Excel or Google Sheets. Use the 'Split text to columns' or 'Text to Columns' feature with space as delimiter to split the name column into first_name and last_name. For names with middle names or suffixes (John A. Smith, Jane Smith Jr.), you may need a TRIM/LEFT/MID formula or a quick manual review.
What export format should I use for different destinations?
+
CSV: for CRM import (Salesforce, HubSpot, Pipedrive, etc.) and spreadsheet analysis. JSON: for developer use, API import, or custom processing scripts. vCard (.vcf): for Apple Contacts, Google Contacts, Outlook, and any address book application — this is the standard format for importing contacts to phone and calendar apps. All three formats contain the same data; the format choice is about the destination tool's preference.
Want to validate the extracted emails before importing?
Run the email column through the Email Verifier to check syntax, detect disposable addresses and role accounts, and get a quality score for each address before your CRM import.
Open Email Verifier