LinkedIn & Facebook Group Contact Scrape
Краткое
Freelancer Client is hiring: LinkedIn & Facebook Group Contact Scrape.
Location: Remote
I need a reliable way to pull every publicly available contact detail from more than ten LinkedIn and Facebook Groups. Both platforms matter to me equally, so the workflow has to switch smoothly between the two and respect their different rate limits, anti-bot checks, and privacy policies.
Each chosen group may contain hundreds or even thousands of members. From every member profile I want the following, whenever it can be found: full name, profile URL, current job title, company, location, plus any email address or phone number that is visible either on the profile itself or through permitted enrichment techniques.
I expect the scraping to run through a proven stack—Python with Selenium or Playwright, Phantombuster, TexAu, or another dependable solution is fine as long as it stays within the platforms’ terms of service. Captcha bypasses, rotating residential proxies, and time-spaced requests are essential so accounts are not flagged.
An .xlsx or .csv file for each individual group
Columns: Group name, Member name, Profile URL, Title, Company, Location, Email, Phone, Other notes
Skills: Python, Data Processing, Web Scraping, Software Architecture, Data Mining, Data Extraction, Data Analysis, Selenium
Budget: $8–$15 USD
Source: Freelancer Client via Remote / Online. Apply on the source website.
Оригинал
I need a reliable way to pull every publicly available contact detail from more than ten LinkedIn and Facebook Groups. Both platforms matter to me equally, so the workflow has to switch smoothly between the two and respect their different rate limits, anti-bot checks, and privacy policies.
Scope
Each chosen group may contain hundreds or even thousands of members. From every member profile I want the following, whenever it can be found: full name, profile URL, current job title, company, location, plus any email address or phone number that is visible either on the profile itself or through permitted enrichment techniques.
Data handling
I expect the scraping to run through a proven stack—Python with Selenium or Playwright, Phantombuster, TexAu, or another dependable solution is fine as long as it stays within the platforms’ terms of service. Captcha bypasses, rotating residential proxies, and time-spaced requests are essential so accounts are not flagged.
Deliverables
• An .xlsx or .csv file for each individual group
• Columns: Group name, Member name, Profile URL, Title, Company, Location, Email, Phone, Other notes
• One consolidated master file with all groups merged, duplicates removed, ready for import into my CRM
Acceptance
I will run random checks against at least 5 % of the rows. A successful job means 95 %+ accuracy on those samples, no dead profile links, and no banned accounts during or after extraction.
Let me know your proposed toolset, estimated turnaround time, and any limits on daily scraping volume.
Локация & Details
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