A LinkedIn profile scraper for full work history
Pull headline, experience, education and skills from LinkedIn profiles.
The Kavex LinkedIn profile scraper turns a list of profiles into structured contact records. Paste profile URLs or slugs and get back name, headline, location, current company, summary, recent experience, education and top skills, one row per person. It is built for recruiters and sales teams who need the background on someone in a spreadsheet, not a browser tab. You pay per profile returned.
A RUN OF 1,000 PROFILES ON THIS SOURCE, AT 3 PER PROFILE
Six columns on every row.
These come with the run and cost nothing extra. Add-ons widen the same sheet, and you pay only for the ones you switched on.
| Name | Headline | Location | Current company | Top skill | Education |
|---|---|---|---|---|---|
| Anna Visser | Head of Growth | Amsterdam, NL | North Studio | Demand Generation | UvA |
| Tom Bright | Founder & CEO | London, UK | Bright Labs | Product Strategy | Imperial |
| Lena Vogt | Senior SDR | Berlin, DE | Varzace | Outbound Sales | TU Berlin |
| Marc Dupont | Engineering Lead | Lyon, FR | Studio Meraki | Backend Systems | INSA Lyon |
Say what you want. Read the price first.
Everything else is a ceiling or a filter. The estimate moves with the numbers you type, so the run never surprises you at the end.
The LinkedIn profile scraper reads each profile and pulls the details that matter for outreach and sourcing. You provide the profile URLs and it returns a uniform row per person, so a list of fifty people becomes a dataset rather than fifty open tabs.
Each row holds the name, headline, location and current company, plus the summary, the most recent roles, education and the top skills listed. That is enough to qualify a candidate or brief a sales call without ever loading the profile yourself.
Because every profile returns the same fields, the output sorts and filters cleanly. You can rank a candidate list by current title, group a prospect list by company, or scan for a specific skill across the whole file in seconds.
Structured profile data is what makes a list workable at scale. One profile read in a browser is easy; fifty is an afternoon lost. The LinkedIn profile scraper collapses that into a single file where every person carries the same columns, so a recruiter can sort a shortlist by current title or filter for a specific skill, and a salesperson can group contacts by company before an account review. Because the data is captured live, a recent job change or a new skill shows up rather than a stale record misleading your outreach. It is the difference between a pile of links and a contact list you can actually segment and act on.
The LinkedIn profile scraper reads profiles through your own LinkedIn session. You connect a session cookie once in Settings, where it is encrypted at rest, and the scraper loads the profiles your account can already view.
Every profile is fetched live, so the current role, recent experience and skills reflect what the person has on their profile today. The data is parsed into consistent columns, turning a list of profile URLs into a single uniform file with no manual tidying.
Charged per delivered row. If the source holds fewer than you asked for, the rest of the credits go back to your balance the second the run ends.
One thousand profiles, itemised.
One line, because this source has nothing bundled on top. You pay the rate times the rows the run actually delivered.
| Line | Rate | Units | Credits |
|---|---|---|---|
| LinkedIn Profiles | 3 / profile | 1,000 profiles | 3,000 |
| 1,000 profiles | 3 / profile | 3,000 credits | $3.00 |
$0.003 PER FINISHED PROFILE · ONLY DELIVERED ROWS ARE BILLED
What people point it at.
Four ways this source is used today. Every one of them is the same run, the same export and the same credit pool.
- Recruiters sourcing candidates, headline, current role, history and skills lined up in one row each.
- Sales teams enriching CRM contacts with full work history before an account review.
- Founders doing pre-call research so they walk into a meeting already knowing the person.
- Talent teams building a structured shortlist from a set of profiles gathered elsewhere.
The rest of the linkedin stack.
Same credit pool, same export. Chain the output of one run into the next without paying for the list twice.
Asked before the first run.
Short answers, no accordion to click through. If something is still missing, the help pages go deeper.
What fields does each profile return?
Each row includes name, headline, location, current company, summary, recent experience, education and top skills, the full picture you need to qualify a person quickly.
How do I connect LinkedIn?
Add a LinkedIn session cookie once in Settings, where it is stored encrypted at rest. The scraper then runs against your profile list with no further setup.
Can I run many profiles at once?
Yes. Paste a list of profile URLs or slugs and the scraper processes them in sequence, returning one combined file with a uniform row per person.
How do results export?
Profiles download as a CSV with one person per row and a column for each field, ready to filter by title or skill and import into an ATS or CRM without any manual cleanup of the columns first.