B2B Databases such as Apollo.io or Zoominfo scrape the web to update their people and company data. With hundreds of millions of leads (Apollo says 275M), they can't keep their data fresh.
Profiles with data not updated for more than 1 year are more common than you think. The only places with fresh data are where people update their profile themself. And the best place is LinkedIn.
👉 LinkedIn is the most reliable source for fresh profile data.
With the LinkedIn Profile Scraper, you only need the LinkedIn profile URL (Sales Navigator URL or Public URL) and it will scrape available public data. And Datablist is built for scale, so run this enrichment on hundreds or thousands of LinkedIn profiles.
Main features:
- Update all or only missing fields.
- Compatible with Sales Navigator URLs.
- This enrichment doesn't need your LinkedIn credentials. No risk of having your LinkedIn account blocked.
- Run at scale
Step-by-step guide
Step 1: Load your CSV or Excel file on Datablist
Create a free account and import your data file. Datablist is a powerful CSV editor. Perfect for opening large CSV files or Excel files with a list of items.
Create a new collection and import your file.
Step 2: Select the "LinkedIn Profile Scraper" enrichment
Click on the "Enrich" button in the header, and search for "LinkedIn Profile Scraper".
Step 3: Configure settings and inputs
After selecting the enrichment, a drawer opens with settings and the input configuration.
Select "Disable cached profiles" to get only real-time data from LinkedIn (see pricing). When disabled, you might get a cached version (less then 1 month). This allows faster and cheaper scraping.
You can also define the number of experiences that will be scraped for the profile. Select between 3, 5 or 10. 3 experiences being the default.
In the "Input" section, select the property from your collection with the LinkedIn Profile URL.
Step 4: Configure Outputs and Run the enrichment
The final step is to configure when the scraped data will be stored. You can map the output data with an existing property or create a new property that will store the results.
Note: If you are scraping LinkedIn Sales Navigator URLs, the "LinkedIn Profile URL Normalized" output will return the LinkedIn Public Profile URL.
The last work experience includes detailed company data. The others only have the job title, company name, and start and end dates.
Once your output properties are set, click "Run enrichment".
How much does it cost to scrape a LinkedIn Profile?
Datablist Enrichments work with a credit system. You receive credits with your monthly plan and you can buy non-expiring credits with top-ups.
The Linkedin Profile Scraper enrichment costs 25 credits per profile (50 credits when "Disable cached profiles" is checked).
A $20 top-up gives you 20,000 credits. The scraping of one profile costs $0,025. You can scrape 800 profiles with a $20 top-up.
A $150 top-up gives you 200,000 credits (25% discount). The scraping of one profile costs $0,01875. You can scrape 8000 profiles with a $150 top-up.
Learn more about the Datablist Credits System.
What to Prepare Before Scraping LinkedIn Profiles
Use one LinkedIn profile URL per row. Standard LinkedIn profile URLs work best. But it also works with LinkedIn Sales Navigator URLs.
Before running a large file:
- Keep the original profile URL column
- Create output columns for the fields you need
- Run a small preview
- Keep the status column for retries
Use the results to refresh CRM records, qualify leads, personalize outreach, or enrich recruiting lists.
FAQ
Can I scrape LinkedIn profile data from a CSV file?
Yes. Import your CSV or Excel file, map the LinkedIn profile URL column, choose output fields, and run the enrichment in bulk.
What can I use LinkedIn profile data for?
Use it to refresh job titles, company names, locations, headlines, profile details, and other public fields before outreach, recruiting, or CRM cleanup.
Should I keep the original LinkedIn URL?
Yes. Keep the source URL and write scraped fields into new columns. This makes it easier to audit results and rerun failed rows.
What happens when a profile cannot be scraped?
Use the status output to filter failed rows. Fix malformed URLs or remove unsupported records before retrying.