Profile Details Batch Scraper for LinkedIn + EMAIL (No Cookies)

🚀 What is Profile Details Batch Scraper for LinkedIn + EMAIL?

Profile Details Batch Scraper for LinkedIn + EMAIL is an Apify Actor and a LinkedIn profile batch scraper. Paste a list of public profile links, usernames or in/ paths and it returns one record per person: experience, education, employer details, career insights and a work email lookup. No cookies or login are needed.

• Bulk list input: a LinkedIn bulk profile scraper run starts from one list, and duplicates are removed before anything is read.
• Saved as it goes: every finished profile is written to the dataset at once, so a long run never loses completed work.
• No cookies, no login: the Actor reads pages any visitor can open. If you looked for a LinkedIn profile scraper no cookies option, the input has no cookie or login field.
• A record of where data came from: the source option lets the Actor fill hidden or missing sections from earlier public copies of the same page, and data_source shows which part came from where.
• Email lookup on by default: this LinkedIn scraper with email lookup takes an address from the profile or a listed website when one is published, and otherwise may infer one.

Click Try for free, paste your profiles and press Start.

📊 What data can you extract from LinkedIn?

As a LinkedIn profile details scraper, the Actor saves one record per profile with up to 21 top-level sections. Export the dataset as JSON, CSV, Excel, XML or HTML. A section stays empty when the public page does not show it, and masked text is never written to the output.

Field	Description	Example
basic_info	Name, headline, location, follower and connection counts, current company and title, top school, websites, picture links, badges, about text and email	{"fullname": "Dana Sample"}
experience	One entry per job with title, company, employment type, location, dates, tenure and description	{"title": "Operations Manager"}
education	Schools with degree, field of study and dates	{"school": "Sample City University"}
languages, certifications	Languages with proficiency, and certifications with issuer, date and credential	[]
volunteering, projects, publications, honors_and_awards, patents, courses, test_scores, organizations, services	Optional sections that appear only when the profile lists them	[]
recommendations	Recommendation count and received recommendations	{"received": []}
insights	Estimates worked out by the Actor from titles and dates: total experience, tenure, seniority_level, department, highest_degree, profile_completeness_pct	"manager"
company_details	Current employer: name, website, domain, industry, size, headquarters, type, founded and follower count. Present when employer details are on	{"industry": "Logistics"}
email_info	email, email_status, email_confidence, addresses found on the profile and on websites, candidates, company domain and mail provider. Present when the email lookup is on	"pattern_guess"
activity, similar_profiles	Recent posts, articles and taught courses with likes and comments, and the similar profiles shown on the page. Present when posts and similar profiles are on	[]
data_source	Where each section came from, which sections are still masked, and whether the page was the latest one	{"is_fresh": true}

The Storage tab also offers table views for overview, experience, education, certifications, languages, volunteering, email, employer, insights, activity and similar profiles. The insights values are the Actor's own estimates and not data that LinkedIn publishes.

The company_details block holds LinkedIn company data for the current employer only. The email_info block is the LinkedIn profile email extractor part of each record. As a LinkedIn profile data extractor, the Actor can only return what a logged-out visitor sees, so expect empty sections on some profiles.

💡 Use cases for LinkedIn profile data

• Lead lists: use it as a LinkedIn lead generation tool for people you already picked, with current_title, current_company and email in one table. You can also build a prospect list from LinkedIn links your team collected.
• Sales prospecting: read insights.seniority_level and department to turn a sales prospecting list from LinkedIn into a shortlist your reps can check by hand.
• B2B enrichment: B2B lead enrichment adds company_details and a work email to contacts you already hold. LinkedIn contact enrichment works the same way, one profile link per contact.
• CRM clean-up: match rows on profile_url to enrich CRM contacts with LinkedIn data such as headline, location and employer. LinkedIn profile enrichment of an existing sheet then needs only the links.
• Recruiting research: candidate sourcing from LinkedIn starts with experience, education and insights.highest_degree for people you already know. Candidate research from LinkedIn profiles then reads as structured rows instead of open tabs.
• Employer research: employer research from LinkedIn profiles combines company_details.industry, company_size and headquarters with the people who work there.
• Research datasets: build a dataset of LinkedIn professionals from experience, education and insights for labour-market or career-path analysis.
• AI inputs: LinkedIn profile data for AI is easier to use as JSON with data_source attached, because a model or a vector store can see which parts were masked.

🛠️ How to scrape LinkedIn profiles in a batch

Follow these steps to scrape LinkedIn profiles from a list.

1. Create a free Apify account and open the Actor in Apify Console.
2. Paste your profiles into Profile URLs or usernames, one per line. A LinkedIn profile scraper from URL run accepts full links, in/ paths and plain usernames.
3. Keep Find email addresses on to find email from LinkedIn profile URL lists, or switch it off.
4. Set Include employer details and Include posts and similar profiles, and choose a Data freshness option.
5. Click Start and watch the log. Each profile appears in the Output tab as soon as it is saved.
6. Open the Overview table and download it as CSV to get a LinkedIn profile to CSV file with one row per person. Other formats work from the same dataset.

💰 How much does it cost to scrape LinkedIn?

Pricing is pay per event: you pay for each profile the Actor saves to the dataset, and nothing for profiles that fail. Apify platform usage is billed on top of the events.

• Result (main_result): charged once for every saved profile.
• Actor start (apify-actor-start): $0.00005 per run. The Actor is set to 1024 MB of memory, which is one GB, so the start fee is one event.

Apify plan tier	Price per 1,000 saved profiles
Free	$4.00 (0.004 x 1,000)
Bronze	$3.60 (0.0036 x 1,000)
Silver	$3.20 (0.0032 x 1,000)
Gold and above	$2.80 (0.0028 x 1,000)

Example: 500 profiles on the Gold tier cost 500 x $0.0028 = $1.40 plus the $0.00005 start fee. The same 500 profiles on the Free tier cost 500 x $0.004 = $2.00 plus the start fee.

You can set a maximum spend per run. The Actor then stops cleanly and keeps the profiles already saved. See the Pricing tab for current rates.

⬇️ Input

Only Profile URLs or usernames (urls) is required. The input of this LinkedIn batch profile scraper has no field for a maximum number of profiles, so every valid line in the list is processed. Open the Input tab for every option.

This example uses two fictional profiles:

{
  "urls": [
    "https://www.linkedin.com/in/sample-profile-a",
    "sample-profile-b"
  ],
  "includeEmail": true,
  "includeCompanyDetails": true,
  "includeActivity": false,
  "source": "auto",
  "proxyConfiguration": { "useApifyProxy": false }
}

• urls: LinkedIn profile links, in/ paths or usernames. Duplicates are removed.
• includeEmail: look for a work email for each profile. The default is true.
• includeCompanyDetails: add details of the current employer. The default is true.
• includeActivity: add recent posts, articles, taught courses and similar profiles. The default is true.
• source: auto (the default) reads the latest public page and fills hidden or missing parts from earlier public copies. live uses only the latest page and archive uses only earlier copies.
• proxyConfiguration: proxy settings. The run starts without a proxy and switches to a proxy when requests are rejected.

💡 Start with two or three profiles to check the output before you run a long list.

⚠️ A link to a company page, a post or a search is not a profile link. It is skipped and listed in the run summary.

⬆️ Output

The scraped results are shown as a dataset in the Storage tab. The table view is for convenience and does not show all the fields. You can export LinkedIn profile data as JSON, CSV, Excel, XML or HTML. The results of this LinkedIn profile information extractor then open in your own tools.

This is a fictional, shortened record for the first profile of the input above. It does not describe a real person:

{
  "basic_info": {
    "fullname": "Dana Sample",
    "headline": "Operations Manager at Northwind Sample Ltd",
    "public_identifier": "sample-profile-a",
    "profile_url": "https://www.linkedin.com/in/sample-profile-a",
    "current_company": "Northwind Sample Ltd",
    "current_title": "Operations Manager",
    "email": "dana.sample@northwind-sample.example"
  },
  "experience": [
    { "title": "Operations Manager", "company": "Northwind Sample Ltd", "is_current": true }
  ],
  "education": [
    { "school": "Sample City University", "degree": "Bachelor's degree" }
  ],
  "insights": { "seniority_level": "manager", "department": "operations", "highest_degree": "bachelor" },
  "company_details": {
    "name": "Northwind Sample Ltd",
    "domain": "northwind-sample.example",
    "industry": "Logistics"
  },
  "email_info": {
    "email": "dana.sample@northwind-sample.example",
    "email_status": "pattern_guess",
    "email_confidence": "medium",
    "emails_found_on_profile": [],
    "emails_found_on_websites": [],
    "company_domain": "northwind-sample.example",
    "mail_provider": "microsoft_365"
  },
  "data_source": { "primary": "live", "live_status": "profile", "is_fresh": true }
}

The second profile could not be read, so it is not in the dataset and not charged. It appears in the RUN_SUMMARY record of the key-value store:

{
  "totalProcessed": 2,
  "totalSaved": 1,
  "totalFailed": 1,
  "failedUsernames": ["sample-profile-b"],
  "failureReasons": {
    "sample-profile-b": "profile not found on LinkedIn (404); no saved copy of this profile is available"
  },
  "unfinished": []
}

How to read the email fields

email_status tells you how an address was reached, and it is the field to read before you use any address:

• found_on_profile and found_on_personal_website: the address is written in the profile text or on a website listed on the profile.
• pattern_guess: the Actor inferred the address from the person's name and the employer's domain. It can be wrong and nothing confirms it exists.
• domain_has_no_mail_server, only_generic_emails_found and not_found: no personal address could be returned, so email is null.

The Actor sends no email, and none of the addresses are verified. email_confidence is a label per outcome, not a probability. To find work email by name and company domain, the Actor needs the first and last name from the profile and a company domain. The Actor works as a work email finder only for people you already listed. To find email address from LinkedIn profile pages, switch on Find email addresses. As a LinkedIn email finder tool it returns at most one address per profile. Think of the email part as a LinkedIn email scraper for published addresses plus an inferred fallback.

⚠️ Limitations and error handling

• The Actor reads only public pages as a visitor, so private, login-only and contact-hidden data is never collected. Because it is a LinkedIn scraper no cookies tool, it sees the logged-out view and some sections stay empty.
• It needs profile links, usernames or in/ paths. As a LinkedIn profile extractor it does not search LinkedIn for people.
• It is a LinkedIn data scraper for person profiles and the current employer's public page. It is not a LinkedIn company data scraper for whole companies.
• Without a search function it is no bulk LinkedIn profile finder: you supply the list.
• Earlier public copies can be older than the latest page. data_source.profile_as_of and is_fresh show how current a record is.
• Pages are read at a measured pace and several profiles at a time. If LinkedIn keeps rejecting requests, the Actor skips fresh pages for the rest of the run and, with source set to auto, uses earlier copies instead. Run a short test to see how long your list takes.
• A long list may need more than one run, because a run has a time limit set in its options.
• Profiles that cannot be read are not saved and not charged. The reason is stored in failureReasons of the RUN_SUMMARY record:

Reason in RUN_SUMMARY	Meaning	What to do
not a LinkedIn profile username or URL	The line is not a profile reference	Fix the line and run again
profile not found on LinkedIn (404)	The profile is not available	Check the link
LinkedIn rejected the request on every connection tried	The page kept refusing requests	Try again later
fresh page skipped after repeated rejections	The latest page was skipped after many refusals	Try again later or use auto
LinkedIn showed a login wall	The page asked for a login	Try again later
no saved copy of this profile is available	No earlier copy exists to fill the gap	Nothing, or try the latest page later
saved copies exist but none is a readable profile page	Earlier copies were not usable	Try again later
network unavailable	Requests did not reach a server	Run again
internal error while processing (...)	The profile crashed the parser	Report it in the Issues tab

The run status message reads Done - N profile(s) saved. on success, No profiles saved - LinkedIn did not return readable pages. See RUN_SUMMARY for the reasons. when nothing was saved, and Spend limit reached when your maximum cost per run stopped the run.

🔌 Integrating Profile Details Batch Scraper for LinkedIn + EMAIL with other apps

You can run the Actor from the Apify API, on a schedule, or from webhooks that fire when a run finishes. Ready-made code samples are in the API tab. The Apify integrations connect the dataset to Make, Zapier, Google Sheets, Slack and Airbyte.

You can run this LinkedIn profile scraper online from Apify Console with nothing to install. Teams that need a LinkedIn profile data API for their own app can start runs and read the dataset items over HTTP. To start a run, send a request to https://api.apify.com/v2/actors/data_wiki~profile-details-batch-scraper-for-linkedin-email-no-cookies/runs.

Schedule a run to refresh the same list. Each run writes a new dataset, so you compare runs yourself. As a LinkedIn profile data scraper it writes one dataset item per profile, which suits spreadsheets and databases. Export the dataset to a sheet or a file to feed your talent sourcing tools or your CRM. For AI agents, the hosted Apify MCP server at https://mcp.apify.com lets an agent find the Actor with search-actors, read it with fetch-actor-details and run it with call-actor.

🔗 Other scrapers for LinkedIn and employer research by data_wiki

Only the first Actor below reads LinkedIn. The others relate by workflow: they add company websites, technology and employer data around the people you research.

Actor	What it extracts	When to use it
LinkedIn Profile Scraper + Email	Public LinkedIn profiles with a maxProfiles limit, a compareWith option and 61 fields	You want a profile Actor with the options listed in its own README, see the FAQ below.
Contact Details Scraper	Emails, phone numbers, social links and addresses from company websites	You have the employer's website and want its published contact details.
BuiltWith Official Technology Scraper	Technologies, hosting and contacts of any website	You research which companies use a technology before you look at their people.
Glassdoor Reviews & Jobs Scraper	Employee reviews, salaries, interviews and jobs per company	You want the employer side of a hiring or sales research.

For help with runs, see the Apify documentation.

⚖️ Is it legal to scrape LinkedIn?

The Actor collects only information that a visitor can see on LinkedIn without logging in, and it does not collect private or login-only data. That does not make every use lawful. The records contain personal data: names, job history, photos, locations and email addresses that are either published or inferred.

• You decide the purpose. You need a lawful basis to collect and store the data, for example under GDPR or CCPA, and you must handle access and deletion requests.
• Outreach rules apply. Anti-spam and e-privacy laws cover any message you send. An inferred address may belong to someone else or not exist.
• Check the site's terms. LinkedIn's terms may restrict automated collection, and you carry that risk.
• Collect less. Turn off the parts you do not need, and delete data you no longer use.

Questions such as LinkedIn scraping legal limits have no single answer, because they depend on your country and purpose. This is not legal advice, and the Actor makes no promise that your use is lawful. Talk to a lawyer if you are unsure. See Apify's posts on the legality of web scraping and ethical web scraping.

❓ FAQ

How does the LinkedIn profile batch scraper handle a large list?

It processes several profiles at a time with a short pause between page requests, and saves each profile as soon as it is ready. The input has no maximum, so the limits are your spend limit and the run time limit. Run a short test first to see how long your list takes.

Can I scrape LinkedIn profiles without login?

Yes. The Actor needs no login, account or cookies. The trade-off is that you only get the view a logged-out visitor sees, so some sections can be empty or masked.

Can you scrape LinkedIn profiles that are private?

No. Private and login-only profiles are not collected. Such a profile is skipped and listed in the run summary with a reason.

How accurate is the LinkedIn email finder part?

Treat any pattern_guess address as inferred, not confirmed. The Actor builds the address from the person's name and the employer's domain, so it can be wrong. Addresses with the status found_on_profile or found_on_personal_website were published, but you should still check them before outreach.

How do I find work email from LinkedIn profile links?

Paste the links, keep Find email addresses on and read email_info.email_status for each profile. The employer's domain comes from the employer details, so leave Include employer details on for best results. The Actor sends no email.

Can I find someone's work email with this Actor?

Only for a profile you give it. The Actor does not search by name. It reads the profile you list and then returns a published address, an inferred one, or null.

Is there a LinkedIn profile scraper API?

Yes. You can start the Actor and read its dataset through the Apify API. It is not an official LinkedIn profile API: it reads the same public pages a visitor can open.

Which LinkedIn profile Actor should I use?

Both Actors read public LinkedIn profiles without a login. This one takes a list only, has no maximum-profiles input, has a source option and returns 21 snake_case sections, and profiles that fail are listed in the run summary. The other one, LinkedIn Profile Scraper + Email with run comparison, has a maxProfiles input and a compareWith option, returns 61 camelCase fields including skills, and reports a status for each input. Choose the one whose output fields and options match your task.

Do I need proxies?

No. The run starts without a proxy and switches to a proxy when requests are rejected. You can set proxy settings in the input. Proxy traffic, if used, counts as Apify platform usage.

Can I use it through an MCP server?

Yes. Use the hosted Apify MCP server at https://mcp.apify.com, where an agent can search for the Actor, read its details and call it with the input above.

💬 Your feedback

Found a bug or need another field? Open an issue in the Issues tab of the Actor. Need a custom solution? Contact hello.datawiki@gmail.com.