Uruguay Cardholder Contact Data Scrape
Budget: $30 – $250 USD
I need a reliable data-scraping specialist to build a contact list of people in Uruguay who are confirmed credit-card holders. I only require two fields per record—valid full name and active phone number—so there is no request for credit-card numbers or any other sensitive financial detail.
Scope and expectations
• Source flexibility: you can pull from LinkedIn, company sites, social media, or any other compliant source you find effective.
• Audience focus: Uruguayan residents, ideally at executive or professional levels, but I will consider any card-holding demographic you can verify.
• Accuracy: medium accuracy is fine; please employ automated verification such as duplicate removal, number format checks, and quick cross-referencing against public directories.
• Volume: propose the count you can deliver along with an estimated turnaround.
• Output: a clean CSV or Google Sheet containing Name and Phone columns (extra fields like occupation are welcome if they come at no added effort).
Ethical and legal compliance is non-negotiable—no breaches of platform terms or local privacy regulations.
When you respond, include:
1. A brief outline of your scraping approach and preferred tools (e.g., Python, Selenium, Scrapy, Phantombuster).
2. Examples of similar contact or LinkedIn extractions you have completed.
3. An estimated record count and delivery timeframe.
I’m ready to start as soon as I find the right fit.
Scope and expectations
• Source flexibility: you can pull from LinkedIn, company sites, social media, or any other compliant source you find effective.
• Audience focus: Uruguayan residents, ideally at executive or professional levels, but I will consider any card-holding demographic you can verify.
• Accuracy: medium accuracy is fine; please employ automated verification such as duplicate removal, number format checks, and quick cross-referencing against public directories.
• Volume: propose the count you can deliver along with an estimated turnaround.
• Output: a clean CSV or Google Sheet containing Name and Phone columns (extra fields like occupation are welcome if they come at no added effort).
Ethical and legal compliance is non-negotiable—no breaches of platform terms or local privacy regulations.
When you respond, include:
1. A brief outline of your scraping approach and preferred tools (e.g., Python, Selenium, Scrapy, Phantombuster).
2. Examples of similar contact or LinkedIn extractions you have completed.
3. An estimated record count and delivery timeframe.
I’m ready to start as soon as I find the right fit.