Company Data Scraping for Research

@justmian876

As a seasoned data extraction and web scraping expert with BN-Droids Digital Services, I am confident in my ability to provide you with the precise dataset you need for your market research. We have extracted over 20 million company-level data points from various regions, including the USA, UAE, Europe, Australia, and Canada. Endowed with scalable technologies and extensive Python automation skills on Selenium, we assure you of meticulous scraping irrespective of the source—business directories and individual company websites in your case.

@glanegonsalves

Hi, Glane here. I can scrape and compile fresh company-level data from business directories and publicly accessible company websites, including company name, location, contact details, industry/category, and other publicly listed metrics. I’ll use Python with requests/BeautifulSoup, Selenium or Playwright where appropriate, then clean and deduplicate the results and deliver a structured Excel workbook with separate sheets for each source and consistent column headers. I’ll also flag incomplete fields, include the source URL for traceability, and provide a short method note explaining the tools and workflow so the dataset can be refreshed later. I’ll respect each website’s terms and public-data policies, with no login protected scraping, CAPTCHA bypassing, or other access-control circumvention. For timing, I can typically deliver a small-to-medium dataset within 1–3 days, depending on the number of companies and sources.

@muneeb6767

I can build an automated Python scraping workflow for business directories and company websites, extracting names, locations, contacts, industries and public metrics, then deduplicating and structuring everything into separate Excel sheets with incomplete fields flagged. I’ll also provide the reusable scripts/method notes and ensure the collection stays within public-data policies without bypassing logins or CAPTCHAs.

@ganeshrasekar

I can do it.

@akkiwadhwa1995

Scraped company databases and directories at scale with Python + Playwright/Scrapy. I'd deliver a clean Excel workbook with each source on its own sheet, consistent headers, deduplicated rows, and incomplete fields flagged so you can decide what to chase manually. You'll also get the short method note (tools/scripts) so your team can re-run or refresh it later. Publicly listed sources only. Happy to share a sample sheet before you commit.

@techw6775

Hi, I can handle this project from start to finish including extracting fresh company data from business directories and company websites cleaning and deduplicating the records standardizing company names locations contact details industries and publicly available metrics and delivering everything in a well structured Excel workbook with separate sheets for each source and clear flags for incomplete information I will use reliable scraping tools and scripts with proper validation to maintain data quality and provide a brief method note explaining the process so you can replicate or update the dataset later I will only collect publicly available information and will not bypass login protected areas or CAPTCHAs Once you share the target sources countries industries and approximate volume I can confirm the timeframe and get started Thank you

@robertb297

Hi, The useful part is not filling rows — it is deduplicating directory listings against company websites so one business does not appear twice under slightly different names. How I'd run it: 1. You share the directory URLs, target geography/industry, and required fields 2. I pull a ~50-row sample into the real workbook layout (one sheet per source, same headers, incomplete fields flagged) for your OK before scaling 3. Full extract: name, location, contact fields, industry tags, public metrics — each row keeps its source URL 4. Dedup on normalized domain first, then name + city; uncertain matches flagged, not merged silently 5. Deliver cleaned XLSX (directory sheet + company-site sheet + optional consolidated sheet), plus a short method note with the Python scripts/selectors so you can refresh later Public pages only — no login areas, no CAPTCHA bypass, polite rate limits respected. If a source blocks automated reads, I'll flag it and we drop or adjust that source. ₹7,000 covers an agreed batch from public sources; if your full list is larger, we confirm scope in chat first. Which directories and roughly how many companies are you targeting? Thanks, Robert

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@nexvative

I can handle this company-data scraping and deliver a clean, deduplicated dataset ready for your market research. I have strong experience with Python web scraping using Requests, BeautifulSoup, Scrapy, and Playwright, including dynamic websites and e-commerce/business data collection. I can build a structured pipeline to collect company names, locations, contact details, industries, and publicly listed metrics from business directories and individual company websites. My approach will include source-specific extraction, normalization of names/addresses/contact fields, deduplication, validation, and clear source attribution. I can deliver the results in Excel with separate sheets for each source, consistent headers, and flags for missing or incomplete fields so you can manually review them. I’ll also provide a concise method note covering the scripts, libraries, scraping workflow, and update process so the dataset can be refreshed later. I will only collect publicly accessible information, respect applicable site policies and rate limits, and will not access login-protected areas or bypass CAPTCHAs/anti-bot protections. Once you provide the target directories/websites, geographic scope, and approximate record volume, I can confirm the extraction workflow and timeframe

@Akash7015

Hello, i read your requirement. I have experience in excel and done many projects i give you best work on your time and budget. Thanks, waiting for your response...

@petropankovdev

Hello, Your brief is specific in the right place: two source classes (business directories and individual company websites), one workbook with a sheet per source, consistent headers, dedup, and incomplete fields flagged instead of silently dropped. That last point is what most scraping jobs skip, and it is what decides whether the dataset is usable for research or just looks full. How I would run it: 1. You send the directory list plus the industry and geography you care about. Within the first day I pull a 50-row sample from one directory and send it as the real workbook, same headers, same flags. You confirm the column set before I scale, so we never argue about structure on 5000 rows. 2. Full extraction: company name, location, contact fields, industry tags, publicly listed metrics. Dedup runs on normalised name plus domain rather than the raw string, so "Acme Ltd." and "Acme Limited" on the same domain collapse into one row instead of two. 3. Method note plus the script itself, with the selectors and how to re-run it. You can refresh the dataset later without hiring anyone again. On your third deliverable: public pages only, no login-protected areas, no CAPTCHA work, robots and rate limits respected. If a directory blocks automated reads, I say so and we drop that source rather than push through it. Relevant experience: I have delivered a large contact-base harvest from public sources where the hard part was exactly this, deduplication across several sources and cleaning inconsistent fields into one column set. On this account I have two completed projects, both rated 5 out of 5, delivered on time and on budget. I also have 16 merged pull requests in third-party open source projects, mostly a Go security tool with 216 stars. Price 6500 INR, 4 days from the moment I have the directory list. One question so I can size it properly: roughly how many companies are you expecting, and which country or industry are we covering? Petro Pankov, BotCraft Group

@hearthacker8474

Hi, I have carefully reviewed your requirements and have hands-on experience with web scraping, data extraction, data cleaning, deduplication, and Excel/CSV data preparation. I can collect fresh company-level information from business directories and individual company websites, including company names, locations, contact details, industry/category and publicly available business metrics. My approach will include: • Extracting only publicly available information • Cleaning and standardizing the data • Removing duplicates • Flagging incomplete/missing fields • Separating directory and company-website data into different sheets • Maintaining source URLs for verification • Providing a clear method note covering the tools/scripts used • Respecting website policies, with no login-protected areas or CAPTCHA bypassing I will deliver a clean, structured and reusable Excel/CSV dataset that can be easily updated in the future. I am also flexible with the budget and can complete the project for even half of the posted budget, if required. My priority is to provide genuine value, maintain good communication, and build a long-term working relationship rather than focusing only on a single project. I can start immediately and will provide full support throughout the project. Looking forward to working with you.

@Jennycreation

Hello Sir, I have already worked on similar types of website and software development projects and I am confident that I can successfully handle your project. I am a full-time freelancer with **17+ years of experience** in web development, software development, automation, and API integrations. My expertise includes: * ASP.NET C# web and software development * Android app development * Python automation and web scraping (Amazon, Instagram, Facebook, Google Maps, LinkedIn, Telegram, and other custom scraping solutions) * JavaScript, jQuery, AJAX, Bootstrap, HTML5 * Microsoft SQL Server database development * Payment gateway integration * SMS, Email, Banking, Financial, and Insurance API integration * Custom automation bots and workflow automation software I focus on delivering **high-quality, scalable, and reliable solutions** with clean code and long-term support. Please contact me in private chat so we can discuss your requirements in detail. I can also show you a **demo of similar projects** I have completed. Looking forward to working with you. Thanks & Regards

@alfatrade2

Deduplication across two sources is the tricky part: a directory listing and the company's own site rarely spell the name the same way, so I'd match on domain first and on name plus city second, and flag the uncertain pairs instead of merging them silently. I built a tender monitoring system with a separate adapter for each source, and the same structure fits your two sheets. Which directories do you have in mind, and roughly how many companies are you aiming for?

@MrShortFlow

Company data extraction from business directories and company websites, deduplicated and split by source into a single Excel workbook is exactly what I will deliver. Steps: collect and structure fields (name, location, contact, industry tags, listed metrics), flag incomplete rows, then deliver one workbook with a directory sheet and a company-sites sheet, plus a short method note listing tools used. v1 within 2 working days for review, final after your feedback. I do not promise access to gated or login-protected data, only public listings. Question to start: which industries, regions, and target company count should I focus on, and can you share the directory names or URLs. Price: 4300 INR fixed · Timeline: 3 working days from access/brief Konrad

@Digitalizers010

Hi, a deduplicated company list off business directories plus the company sites, one sheet per source, gaps flagged not left blank. Directory records and site records rarely agree, so the merge is the real work. How we would build it: a crawler per directory paging listings into a raw table, a second pass visiting each company site for the contacts the directory withheld, then matching on domain first and normalised name second so two records for one company become one row. Missing fields stay flagged, never guessed. Public pages only. Which directories and which industry should we start from? The method note ships as a readme with the scripts so you can rerun it. Regards, Digitalizers

@diyaluo

Hi, I can complete this with high accuracy. Proven pipeline: automated extraction (pdfplumber/camelot/ccxt-style parsers) plus row-by-row validation against source and manual QA, tested on 800+ page documents. Deliverable is a clean, ready-to-use file with data preserved exactly. I can send a sample page first. Free revisions until you're satisfied. Ready to start now.

@LeonBoshoff

Your project for scraping fresh company-level information aligns perfectly with my expertise in data extraction. I've recently completed similar tasks, efficiently gathering and organizing data from business directories and company websites. I understand the importance of delivering a cleaned spreadsheet with clear source attribution and structured data. I'll ensure that the data is deduplicated, with separate sheets for each source, and I'll flag any incomplete fields as requested. My approach involves using reliable tools that respect public-data policies, ensuring a smooth process without bypassing any restrictions. I’ll also include a method note detailing the tools and scripts used, making it easy for you to replicate the process. I emphasize clear communication and reliability, ensuring that the data supports your market research goals effectively. What is your target timeframe for this project? P.S I look forward to your message Leon B.

@LuanCoetzee42

? I NOTICED SOMETHING IN YOUR PROJECT DESCRIPTION THAT MOST FREELANCERS WILL MISS In a recent project, I successfully scraped and organized data for a client in the tech industry, extracting over 500 company profiles from both business directories and individual websites. This led to a comprehensive database that enhanced their market analysis, resulting in a 30% increase in lead generation. I have over five years of experience in data scraping and analysis, specializing in extracting structured information while adhering to compliance standards. My expertise includes using tools like Python, Beautiful Soup, and Scrapy, ensuring efficiency and accuracy. I understand your need for clean, reliable data to support your market research. My approach involves setting up automated scripts to gather fresh information while closely monitoring for any changes in site structures or policies to maintain compliance. I prioritize clear communication and timely updates throughout the project to ensure long-term success. I am confident that I can deliver the results you need promptly. The difference between an average result and an exceptional one is usually decided before the work even begins. Regards, LuanCoetzee42