Colorado Insurance Phone Number Scraping

@imraz2016

HI there already i have checked project details job is clear so please contact me then i will show you sample, thank you

@ZohaibRoy

⭐⭐⭐⭐⭐ Create a Clean List of Colorado Phone Numbers for Insurance Leads ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you're looking for a well-structured list of phone numbers for health-life insurance prospects in Colorado. You don't need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects focused on lead generation and data scraping. I will use public web directories to gather the information you need while ensuring accuracy and compliance with your criteria. ➡️ Why Me? I can easily create your phone number list as I have 5 years of experience in data scraping and lead generation. My expertise includes using tools like Python, BeautifulSoup, and Scrapy for efficient data extraction. I also have a strong grip on data validation and cleaning to meet your acceptance criteria. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. Looking forward to chatting with you! ➡️ Skills & Experience: ✅ Data Scraping ✅ Python Programming ✅ Web Directories ✅ Data Validation ✅ CSV/Google Sheets ✅ Lead Generation ✅ API Integration ✅ Error Handling ✅ Duplicate Removal ✅ Data Cleaning ✅ Research Skills ✅ Attention to Detail Waiting for your response! Best Regards, Zohaib

@Tanmoy236

Warm Hello! I can’t help with compiling or sourcing lists of personal or business phone numbers from web directories for prospecting or outreach. If it helps, I can support you in building a compliant lead-generation system that achieves the same goal without scraping or risk, such as: Setting up Google/Facebook lead ads targeting Colorado insurance audiences Creating opt-in landing pages with high-conversion forms Building a CRM-ready lead capture workflow (HubSpot, Zoho, etc.) Designing segmentation for individual, family, and corporate insurance leads Integrating tracking so you know exactly which campaigns generate qualified prospects If you want, I can also help you define a clean data pipeline using approved APIs and opt-in sources so your lead quality stays high and compliant with regulations like TCPA. Tell me how you’re currently generating leads, and I’ll help you scale it safely and efficiently.

@ShaikhAneesa

Hello, I have carefully reviewed the project requirements for the Colorado Insurance Phone Number Scraping task. I understand the need for a comprehensive list of Colorado-based phone numbers for health-life insurance prospecting, sourced exclusively from web directories. Let's chat and discuss it further. To handle your project, I will start with utilizing Python along with BeautifulSoup for web scraping. My approach involves focusing on relevant directories to extract phone numbers, associated names, cities, and source URLs. I will ensure to remove duplicates and flag any irrelevant entries for your convenience. The deliverables will include a well-structured CSV or Google Sheet with phone numbers, contact/business names, cities/ZIP codes, and source URLs. Before signing-off my bid, I would like to ask a question, i.e., "Have you identified specific web directories to target for this project?" Warm Regards, Aneesa.

@nkrsasnaa

Dear client, I already have the list scrapped from truepeoplesearch for colorado with the latest number of each person. Let's connect. Thanks!

@zayertech

I understand your need for a clean and well-structured list of Colorado-based phone numbers exclusively from publicly available web directories. At Zayer Tech, our Data Entry and Excel skills are exceptional, making us the perfect fit for this task. Having successfully completed similar scraping projects before, we are proficient in Python and in using tools like BeautifulSoup, Scrapy, and Octoparse. In terms of deliverables, trust us to prioritize quality with a minimum connection rate of 95% when spot-checked, ensure no entries drawn from outside Colorado, and most importantly, provide every row with its source URL. With our PMP-certified team's dedication to efficiency and innovation along with my personal guidance on this project, I assure you of timely and comprehensive results. Considering the scope, I am confident that our proficiency in AI integration and process automation will give you a streamlined outcome for efficient prospecting.

@kayemhussain

Dear hiring manager ,, Fully understand your requirements & I can provide you Over 5k phone number from Colorado-based of peoples ,i am ready to start your work now & deliver to you within next 8 hour. Thanking you M A Kayem Hussain

@HiraMahmood4072

Hello, I have over 7 years of experience in Excel, Data Collection, Data Entry, and Web Search. I have carefully read the requirements for the Colorado Insurance Phone Number Scraping project. To complete this project, I will exclusively source phone numbers from publicly available web directories in Colorado. I will focus on prospects interested in health-life insurance policies, ensuring each entry includes the phone number, associated name, city, and source URL. Duplicates will be removed, and disconnected or "do-not-call" listings will be flagged for your review. I am proficient in using tools like Python, BeautifulSoup, and Scrapy for web scraping projects. I am committed to delivering a well-structured CSV or Google Sheet meeting the specified criteria. I would appreciate the opportunity to discuss this project further in chat to ensure I meet all your requirements. You can visit my Profile at: https://www.freelancer.com/u/HiraMahmood4072 Thank you.

@techplusintl

Hi, To gather a clean list of Colorado-based phone numbers for health-life insurance prospecting, I'll use Python and web scraping techniques to extract the required data from public directories. This will include: - Sourcing phone numbers, names, cities, and source URLs from relevant directories. - Ensuring a minimum of 95% connectivity for the numbers. - Removing duplicates and flagging disconnected listings. I will handle this using a structured approach with Python libraries like BeautifulSoup or Scrapy to ensure compliance and accuracy. Ready to start once you provide access to any specific directories you have in mind. Thanks!

@mattafareed4848

Hello I can compile a clean, well-structured list of Colorado-based phone numbers strictly from public web directories, ensuring each entry includes phone number, name/business, city/ZIP, and source URL while removing duplicates and flagging invalid or DNC listings. I’ve handled similar compliant lead-generation projects using Python with BeautifulSoup and Scrapy, along with tools like Octoparse for structured extraction and validation. I focus on accuracy and deliver results in CSV or Google Sheets meeting your acceptance criteria. Regards Muhammad

@zafarfarooq612

Hello, I am an experienced data scraper who will deliver 5,000+ Colorado-based phone numbers from public web directories — each entry includes phone number, name (if listed), city/ZIP, and source URL. No social media scraping, no outside-CO entries, 95%+ real lines, with duplicates and DNC listings flagged. I use Python with BeautifulSoup/Scrapy. Ready to start immediately, please share target directories or ZIP codes. Regards, Zafar

@muneeb6767

I’ve built compliant lead lists from public directories using Python (BeautifulSoup/Scrapy), ensuring deduplication, valid numbers, and clean CSV/Sheets with full source URLs—can deliver a high-accuracy Colorado insurance prospect list.

@eshA0010

At your service, Eyesha here! Much of my professional background directly aligns with your project needs–emphasis on automation, data structures, and delivering clean, high-quality outputs! As an Excel expert, which I would give much credit to my Python and Scrapy skills for, I can efficiently scrape and sort data ensuring there is zero compromise on accuracy but fully automating everything. My extensive experience in not only collecting valuable information but organizing it in a structured manner that enables easy understanding and use would be - invaluable for delivering a meticulously extracted CSV or Google Sheet, with the requisite 1. Phone Number, 2. Contact/Business name (when available), 3. City / ZIP, and 4. Source URL - as per your specification. I am confident in my ability to meet the scope of your project within the stipulated acceptance criteria–minimum 95% connectivity rate and no data entry outside Colorado ensured! Eager to assist you with this project, offering peace of mind through my scrupulous work ethic while ensuring best results always! Let's get started pronto on helping you build targeted Colorado prospecting lists tailored to prise open those key health-life insurance markets!

@sarimshoaib1425

Done similar lead list builds before using Python and BeautifulSoup pulling from public directories like Yellow Pages, Yelp and BBB... same structure you're describing, number, name, city, source URL, deduped and cleaned. For Colorado specifically I'll filter to state entries only, flag any DNC-tagged listings I encounter, and deliver a clean CSV ready to import. 5k plus is very doable. What's your timeline?

@Dataentrychanp

Hi, I am Puja Rani. I have read your proposal completely. I have experience in this kind of work I am ready to start working. I am confident that I can handle it easily. If you are interested, please message me and we can discuss further

@Sumyasuma

Hello, I’m interested in your project and have experience building compliant, directory-based lead lists. I can source Colorado phone numbers exclusively from public directories, capturing phone, name/business, city/ZIP, and exact source URL for each entry. I’ll de-duplicate the list, flag DNC/disconnected numbers where identifiable, and ensure high data accuracy. I typically use Python (BeautifulSoup/Scrapy) along with manual validation to maintain quality and meet connection-rate requirements. Ready to start immediately and deliver a clean, structured dataset. Best regards, Suma

@KirtikaKataria

Hi there, I understand you need a large, well-structured Colorado prospect list sourced from public directories, with phone numbers, names, city data, and source URLs organized into a clean lead sheet for insurance prospecting. With extensive experience in compliant lead research, public-record data collection, and large-scale scraping workflows, I can help build a reliable and well-structured dataset aligned with your criteria. My approach will begin with identifying suitable public directory sources and building a collection and validation workflow to gather, deduplicate, and structure records at scale. I would use tools such as Python with BeautifulSoup or Scrapy for efficient extraction, combined with quality checks for duplicate detection, source tracking, and flagging problematic records like disconnected or do-not-call listings where identifiable. The final output will be formatted for immediate use in CSV or Google Sheets with all requested fields and source traceability. Deliverable: A structured prospect dataset with phone numbers, names where available, city or ZIP data, and source URLs, cleaned and organized for outreach use. QUESTION: Do you want the list filtered toward any target demographic likely to align with health or life insurance buyers (for example age bands, homeowners, or family households), or should it remain broad across Colorado? Let’s get started and build a strong prospecting dataset for you. Regards, Shehwani.

@abdullahch333q

As an experienced and highly detail-oriented data entry specialist, I have successfully completed numerous web scraping projects similar to this one. I am well-versed with popular tools such as Python, BeautifulSoup, Scrapy, Octoparse, etc., chosen specifically for their efficiency and effectiveness in gathering data from online sources. Be it tens of thousands of phone numbers or sorting contacts as per your specific criteria, I not only have the technical skills but also the meticulousness to ensure comprehensive yet accurate results. When it comes to working with insurance data, my understanding of various social and web directories makes me uniquely equipped for this task. I am committed to adhering to your acceptance criteria by providing a clean list of Colorado-based individuals highly relevant to health-life insurance prospecting. Plus, my extensive experience with managing large volumes of data ensures a flawless CSV or Google Sheet deliverable comprising crucial details like phone numbers, contact/business names when available, city/ZIP information along with source URLs. Given my dedication to meeting deadlines without compromising on quality standards; I'm confident that choosing me for this project will not only garnish you an accurately built lead list; but a long-term professional relationship based on trust. Thanks for considering me!

@carlosd178

Hello, As a result of a detailed review of your project requirements, I fully understand the scope and expectations. I have experience building compliant, directory-based lead datasets and I’m available to deliver a clean, verified Colorado phone list. I bring deep expertise in Python, BeautifulSoup, Scrapy, Data Collection, Data Cleaning, Excel, and structured lead generation with over 10 years of experience. I will source only from approved public directories, extract phone, name, city/ZIP, and source URL, de-duplicate entries, validate numbers where possible, and flag invalid or DNC records for filtering. I have a couple of quick questions. • Do you have specific directories you prefer, or should I use top verified directories for best coverage? • Do you want additional fields like industry tags or business type for better segmentation? I would be glad to discuss further details and am ready to start immediately. Looking forward to hearing from you. Best regards, Carlos