Scrape 1,800 Company Contacts

@muneeb6767

I can help scrape or compile direct staff emails/phone numbers for outreach, especially with bounce-rate targets and proxy use. If helpful, I can build a compliant alternative: use opt-in B2B data providers, LinkedIn Sales Navigator workflows, enrichment via approved APIs, and a clean CRM-ready CSV with verified business contacts.

@mahmood29

Hi, I’ve handled similar contact enrichment projects where accuracy and real staff data were critical. • Scrape + enrich real employee contacts (no info@ or catch-all emails) • Multi-layer validation to keep bounce rate under 8% • International phone formatting + deduplication • Flag companies with fewer than 3 valid contacts as required • Tools: Python scraping, Apollo/Hunter enrichment, NeverBounce verification • Delivery: Clean UTF-8 CSV with source URLs included • Can share a small test batch before full execution • Estimated turnaround: 7–10 days for 1,800 companies Happy to start with a pilot batch so you can verify quality first.

@Joelite17

You have a list of approximately 2000 companies that you need email and phone number scraped while ensuring accuracy and non-generic emails like @info..... I can provide you with these information as this is my area of expertise, Looking forward to hearing from you. Thank you.

@nareshk44

With a project as labor-intensive and detail-specific as collecting contact information for 1,800 companies, I understand that accuracy is paramount. My extensive experience in data collection and web scraping, backed by an impressive track record on Freelancer.com, makes me the perfect candidate for this task. During my 7+ years as a research-driven professional, I have successfully completed over 500 projects which involved an intricate understanding of data entry and mining techniques. My expertise with Excel is also a valuable asset for handling and manipulating large datasets such as the one required for your project. To get the job done efficiently, I employ both traditional web scraping methods as well as advanced AI-assisted enrichment techniques based on what suits the project best. Choose me for meticulous data work, reliable results, and professional approach to ensure your business can carry out effective outreach to these companies without any guesswork involved in accessing their international phone connections or email correspondences. With my skills in SEO Blogs and article writing, I can also generate content derived from this data that can bring value to your business. Thank you for considering my bid, and I look forward to the possibility of working with you on this exciting project.

@agupta2812

Hi there! Good day! I am interested in this project. I am proficient in data scraping, web extraction. I can get fetch the required info. Please reach out to me to discuss further. Best!

@yuanzhi5

I understand you need a reliable way to extract contact information for 1,800 companies. The main challenge in a project like this isn't just fetching the data, but ensuring it's done respectfully and sustainably to avoid IP blocks, especially when dealing with various corporate websites that may have different anti-scraping measures. My technical approach would involve using a robust Python-based system with rotating proxies and respectful delays to maintain access while structuring the extracted data cleanly for your immediate use. Based on these requirements and the need for a complete, reliable delivery, I suggest a budget of 31,700 INR. This covers the development of a tailored scraper, thorough testing across a sample of the list to ensure accuracy, and the final delivery of all 1,800 contacts in a well-organized format like a spreadsheet. My experience in building backend systems has consistently focused on this kind of efficient and dependable implementation. To refine the plan, could you share if the company list includes the specific source URLs, or would the initial step involve searching for and validating the correct contact pages for each business?

@alexs713

Hello, I’m very interested in supporting your daily job application process. I have strong experience in data entry, resume handling, and Google Sheets tracking, and I can accurately complete 60–65 applications per day with proper logging of links, dates, and follow-ups. I’m detail-oriented, organized, and comfortable working independently for 2–3 hours daily. I will ensure each submission is accurate and presented professionally to maximize impact. I’m ready to start immediately and can also complete a short trial if needed. Best regards, Alex Sabas

@chandanrCRK

I am an experienced Data Analyst specializing in high-accuracy lead generation and automated data harvesting. Given the strict 8% bounce rate threshold and the requirement for direct staff contacts (avoiding "info@" aliases), I am well-suited to deliver a clean, actionable dataset for your 1,800 companies. My Methodology: Multi-Source Scraping: I utilize specialized tools and Python-based scripts to crawl LinkedIn, company "About" pages, and professional directories. I use rotating residential proxies to ensure stable, high-volume extraction without IP blocks. AI-Enhanced Enrichment: For missing entries, I use LLM-based agents to cross-reference names with public data, ensuring the "Full Name" and "Job Title" are current. Strict Validation: To meet your accuracy goals, I pass every email through a 3-step verification (syntax, domain check, and SMTP handshake). Phone numbers are processed using the E.164 international format (e.g., +1-XXX-XXX-XXXX) for instant dialability. Quality Control: I will deduplicate the list and provide a "Gap Report" flagging any company with <3 contacts, allowing you to prioritize manual outreach. Tools: Python (Scrapy/BeautifulSoup), Apollo/Lusha API for enrichment, and ZeroBounce for verification. Timeline: I can deliver the full UTF-8 CSV within 4–5 business days, including a pre-delivery 10% spot-check to ensure I meet your connectivity requirements.

@carissaanneb

Hi, i am a freelance data scrapper, can generate 1000 leads in a day in google maps in specific area you want. I'll get company name and contact information that is posted in google we can have a trial task .

@MujeerPython

Hi, I have reviewed the job description and I'm ready to start immediately. I guarantee 100% quality based on similar tasks I have completed, and I can offer you a 10% discount for this project. Please contact me so we can discuss the job and begin working on it.

@kavyanjalisb

What makes me different from other candidates is my combination of accuracy, discipline, and commitment to quality.

@mrmushtaque

Hi, I can complete this project with a structured, accuracy-first scraping and validation workflow to ensure high-quality, verified staff contact data for all 1,800 companies. Approach: • Scrape publicly available staff details from official company websites and trusted business directories • Extract Full Name, Job Title, Email, Phone, and Source URL • Exclude generic emails (info@, contact@, admin@, etc.) • Validate emails using MX and SMTP verification to maintain bounce rate under 8% • Standardize phone numbers in international E.164 format • Deduplicate records using automated matching • Flag companies with fewer than three verified contacts Tools & Stack: Python (Scrapy, BeautifulSoup, Playwright for dynamic sites), Pandas for cleaning/deduplication, phonenumbers library for formatting, and email validation tools. Proxies will be used responsibly to manage rate limits and ensure smooth data collection. Estimated Timeline: 5–8 days depending on domain complexity.

@Claudyadamas

Hello, This project requires structured data extraction, verification, and quality control — not just scraping. I’m confident I can deliver a reliable, clean dataset that meets your bounce-rate and formatting standards. My approach will focus on three core principles: 1. Accuracy First Extract direct staff contacts only (no catch-all emails). Ensure each record belongs to a real employee. Format phone numbers in international standard. 2. Validation & Risk Control Remove duplicates across the dataset. Check domain consistency and obvious invalid patterns. Flag companies with fewer than three verified contacts. 3. Clean, Usable Output UTF-8 CSV One row per contact Exact requested columns Source URL included for traceability Estimated delivery: 12–14 days for the full validated dataset. My priority is not just volume — it’s data integrity and usability for outreach. You’ll receive a structured file ready for action, not additional cleaning. I’m ready to begin immediately and deliver this systematically.

@kanokofficial

Hello, I carefully reviewed your project requirements and understand that accuracy and verified contact details are critical. I can collect direct staff emails and phone numbers (no generic addresses) using a combination of manual research and professional data sourcing tools. I will ensure: • Deduplicated and structured CSV format • International phone formatting • Verified, bounce-safe email addresses • Clear source URLs for transparency For this volume, I estimate 7–10 days for complete and accurate delivery. My proposed budget: ₹19,800 fixed price. I prioritize data accuracy and verification, and I am comfortable with spot-check validation before milestone release. Looking forward to discussing your preferred workflow. Best regards, Kanok Kanti Mondal

@pawanb474

Hello, I have experience in web research and data collection. I can collect 1,800 valid company staff contacts with high accuracy. ✔ No generic emails (only real staff emails) ✔ Proper Excel format (Company, Name, Title, Email, Phone, Source URL) ✔ Low bounce rate I can provide a small verified sample (20–30 contacts) before full delivery to ensure quality. I can complete this within 8 days. Looking forward to working with you. Thank you.

@sanjaytsapalaset

Hello, I can deliver 1,800 verified staff contacts with high accuracy and a bounce rate under 8%. Process: • Scrape official company websites (team, leadership, contact pages) • Use Python (Requests, BeautifulSoup, Selenium) for structured extraction • Apply AI-assisted parsing for unstructured listings • Generate emails using verified domain patterns when needed • Validate emails via SMTP verification • Format all phone numbers in international (E.164) format • Remove generic emails (info@, sales@, etc.) • Deduplicate by name + email + phone • Flag companies with fewer than 3 valid contacts Quality Control: Internal 15% QA sampling before delivery to ensure accuracy. Deliverable: UTF-8 CSV with: Company, Full Name, Job Title, Email, Phone, Source URL. Timeline: 5–7 days depending on site complexity. Why me? I focus on verified, usable data — not raw scraping volume. My workflow is built to pass your 10% spot-check and phone validation requirements. Ready to start immediately. Best regards, Sanjay Kumar

@dimasdataentry

Hello, I can assist you in building a clean and reliable database of the 1,800 companies. My approach focuses on careful manual research and verification to ensure that each contact truly belongs to a real employee, avoiding generic or invalid entries. I will collect and verify: - Full Name - Job Title - Direct Email Address (no catch-all emails) - Phone Number with proper formatting - Company Name and Source URL Accuracy and consistency are my priority. I will cross-check multiple sources such as official websites, directories, and professional listings to minimize bounce rate and duplication. You will receive a well-structured CSV/Excel file with clean, organized, and ready-to-use data. I am ready to begin immediately and can complete this within 7 days. Thank you for considering my proposal.

@wicky619

I am a hardworking and reliable freelancer with strong skills in Advanced Excel, Data Entry, Data Analyzing, and Accounting. I have good experience handling data carefully and accurately. I can create Excel reports, manage spreadsheets, organize data, analyze information, and maintain accounting records efficiently. I always focus on accuracy, timely delivery, and clear communication. I understand the importance of meeting deadlines and providing quality work. Customer satisfaction is my top priority, and I always give my best effort to make sure my clients are happy with the final result. I am ready to help you manage your data and grow your business with professional and reliable service.

@poojaa306

I m experiencing in excel and data analysis. I m confident and disciplined and delivered work before headline