Google Maps Data Extraction

@dissanayakepvt

Hello, I can efficiently extract business data from Google Maps as per your requirements. My approach will ensure: • Accurate extraction of business name, address, and phone number across all states. • Implementation of Python with Selenium or Scrapy, including captcha handling and rate-limiting. • Delivery of a clean Excel/CSV file with clear column labels and a brief script for future use. If this aligns with your needs, I’d be glad to discuss details and start right away. What specific format do you prefer for the final data file? Best regards, GISPromo IT Solutions

@larsenm2020

As a data enthusiast with a profound love for problem-solving, I believe that I'm the ideal fit for your Google Maps Data Extraction project. Armed with vast experience in Python programming, data extraction, and web scraping specifically utilizing Selenium and Scrapy, I'm confident in my ability to generate accurate results while effectively managing duplicates. Ensuring top-notch accuracy and handling potential captcha challenges are always a top priority in any data extraction task; it's an area where I excel. Additionally, my proficiency with the Google Maps API will definitely be an asset as we embark on extracting data from businesses spanning across all states and territories. Moreover, my strong attention to detail and dedication towards delivering error-free reports mean you can expect impeccable outputs in an Excel or CSV format. Not only will I exceed your expectations by delivering clean and well-labeled dataset but also furnish you with a reusable script or a brief “how it was done” note, empowering you to refresh the data whenever required. Let's team up to generate invaluable insights for your market research project!

@datahub0

Hello, I can reliably extract business name, full address, and primary phone numbers from the shared Google Maps saved list and deliver a clean, national-level dataset with strict de-duplication and validation. I’ll use a controlled automation approach (Python + Selenium / Maps API where applicable) with rate-limiting, captcha awareness, and normalization to ensure accuracy across all states and territories. You’ll receive a well-structured Excel/CSV, one row per location, plus a short method note or reusable script so you can refresh the data later. Approximately how many businesses are in the saved Google Maps list so I can size the run time and safeguards correctly?

@usamaansari786

Hi, Leveraging my 5+ years of experience as a Full Stack Developer with expertise in Python and Web Scraping, I am uniquely equipped to tackle your Google Maps Data Extraction project. My proficiency with tools like Selenium, Scrapy, and Google Maps API ensures that not only will I be able to efficiently extract the required information but also handle CAPTCHA verification and rate limitations. My primary focus is on providing you with accurate data while eliminating any chances of duplicates. With me, you can expect nothing less than quality deliverables. Your acceptance criterias 1 and 2 for over 95% returned rows containing the four core fields and no obvious duplicates will be closely adhered to. Furthermore, the CSV/Excel file will be designed error-free for being opened on Excel 2016+, along with a how-it-was-done documentation or even better - a reusable script for your later data refresh requirements. Lets have a chat warm regards Usama Ansari

@Maheshwar24680

Hi there, I can build a reliable, automated Python solution to extract all locations from your Google Maps saved link and deliver them in a clean, ready-to-use Excel/CSV file. ​ My approach: Use a robust scraper (Selenium/Scrapy + Maps API where suitable) with delay, captcha, and rate-limit handling to safely process all locations nationwide. ​ Capture required fields: business name, full address (street, city, state, ZIP), and primary phone; I can also include ratings and review counts if needed. ​ Apply de-duplication and validation so each row is unique and at least 95% of entries have complete data, fully compatible with Excel 2016+. ​ Deliverables: Structured Excel/CSV with one row per business and clearly labeled columns. A short technical note and reusable script so you can refresh or extend the dataset later. ​ Timeline: 3–4 days for full delivery, with fast communication and minor post-delivery tweaks included. ​ Looking forward to working on this project.

@misbahn209

I can extract Business Name, Full Address , and Primary Phone Number from the provided Google Maps saved link with high accuracy and no duplicates. I focus on clean data, proper de-duplication, and Excel-ready delivery. I can complete this within 1 day and deliver the data in Excel or CSV, fully compatible with Excel 2016+. I’ll also include a brief “how it was done” note

@ravibawri

Hello, I can assist with extracting business details from the Google Maps saved link accurately and in a clean, usable format. I will: Extract business name, full street address (city, state, ZIP), and primary phone number Ensure one row per location with clearly labeled columns in Excel or CSV Handle data across all states and territories for a true national dataset Remove duplicates by matching name, phone number, and address Deliver a file that opens cleanly in Excel 2016+ with no errors I can use a structured approach (manual or automated using Python/Selenium if required) with attention to accuracy, rate-limiting, and captcha handling to ensure smooth completion. I will also provide a short note or reusable method explaining how the data was collected so it can be refreshed later. If ratings or reviews are easily available during extraction, I can include them as optional extra columns. Ready to start once you share the Google Maps link.

@SnTechnologies59

Hello, I can extract business data from Google Maps saved links and deliver a clean, well-structured Excel or CSV file. The data will include business name, full street address (city, state, ZIP), and primary phone number, with one row per location and clearly labeled columns. I have 5+ years of experience in Python-based web scraping and data extraction using tools like Selenium, Scrapy, and API-based methods. I focus on accuracy, proper duplicate handling, and stable scraping with rate limiting and captcha-aware logic to ensure the process completes without blocks. The final file will be validated for accuracy, free of obvious duplicates, and fully compatible with Excel. I can also provide a reusable script or brief documentation so you can refresh the data later if needed. Best regards, SoftNexus Technologies

@aryankhaliqu

Hello, I’m a data scientist with hands-on experience in data collection, cleaning, validation, and large-scale spreadsheet delivery, and I’ve completed similar market-research and business-listing projects before. I can reliably extract business contact data from your Google Maps saved link and deliver a clean, national-level dataset that meets all of your acceptance criteria. How I’ll do it I’ll use a Python-based automated workflow (Selenium + structured parsing) specifically designed for Google Maps listings. The process will: Traverse all businesses in the shared Maps link across all states and territories Extract business name, full street address (city, state, ZIP), and primary phone number Handle pagination, rate-limiting, and captcha scenarios to avoid blocks Detect and remove duplicates using name + phone + address matching Validate results to ensure 95%+ field completeness Deliverables Excel or CSV file (Excel 2016+ compatible), one row per location with clearly labeled columns Optional extra columns (ratings/reviews) if captured effortlessly A short “how it was done” note or reusable script so you can refresh the dataset later Accuracy, duplicate handling, and clean delivery are priorities for me. I’m comfortable adjusting the workflow once you share the Maps link and brief. Looking forward to working with you. Best regards, Aryan

@ashishrai7704080

As your project demands a professional capable of handling complex and dynamic tasks, my experience as a full-stack developer and app engineer makes me the ideal candidate. My expertise in Python, Selenium, and Scrapy will ensure an accurate extraction of data from Google Maps for your forthcoming market-research venture. Rest assured, built-in captchas and rate-limiting features will be integrated into the code to ensure an error-free and unobstructed run. Having worked extensively on API integrations and database designs using PostgreSQL, I assure you that I possess the necessary skills to keep your data organized, free from duplicates, and correctly labeled in an Excel or CSV file format. Besides proficiently scraping the required fields (business name, street address, phone number), I can include an added layer to capture reviews/ratings efficiently should you require. My approach is to ensure not just completion but also client satisfaction. Therefore, beyond delivering an accurate dataset with an easy-to-use script or method that you can reuse in the future if needed, I immerse myself in your project vision. I guarantee a clean production-grade code with comprehensive documentation that purposes to deliver a true national snapshot by meeting all four acceptance criteria – 95%+ returned rows validity, no duplicate fields, error-free Excel 2016+ compatibility. Let’s accelerate your market research together!

@leoh100

Hi! I’m Leonardo — a Data Science student (IBM) with additional coursework from the University of Michigan. I’m starting on this platform, so I’m bidding with a more competitive price and a safe timeline, but I’m fully committed to delivering clean, accurate data and earning a strong first review. What I will deliver (1 row per location) Business Name Full Address (City, State, ZIP/Postal Code) Main Phone Number Quality-focused approach (matches your acceptance criteria) Excel/CSV compatible with Excel 2016+ Clearly named columns + consistent formatting De-duplication (same name + phone + address) Basic QA pass to maximize completeness and reduce obvious errors If a business does not publicly list a phone number, I will leave it blank rather than guessing (to protect accuracy). Workflow I will first send a sample (30–50 rows) for format approval. Then I will deliver the full dataset in batches, keeping duplicates under control. Scope & Pricing This bid covers up to 300 locations from your saved Google Maps link. If the list is larger, I can continue with: +100 locations = +₹250 INR Timeline Sample within 24 hours after award Full delivery within 9 days (often sooner depending on total locations) If you need a reusable refresh method later, I can also provide an option using the Google Places API (requires your API key and API usage costs). Thank you — I’m ready to start immediately and I’ll dedicate 100% to making this first project a success.

@omkumarsingh1

Hi there, I saw your project for the Google Maps extraction. I can definitely handle this for you. I use a custom Python and Selenium setup that handles rate-limiting and captchas naturally, so we won't run into blocks. I'll make sure the data is clean with zero duplicates and 100% Excel compatibility. I've done similar large-scale scraping projects before. Please take a quick look at my profile to see samples of my previous data extraction work. I'm ready to get started on the national snapshot whenever you are. Best, Om

@abdelrahmanh022

Hello, I can extract the required business data from your provided Google Maps saved link and deliver a clean, structured Excel/CSV file with one row per location. I will ensure: • Business name • Full address (street, city, state, ZIP) • Primary phone number • Minimum 95% completeness • Careful duplicate removal • File compatible with Excel 2016+ To ensure accuracy and prevent blocks, I will use a structured scraping approach with built-in rate limiting and validation checks. Data will be cleaned and standardized before delivery. You will also receive a short “how it was done” note and a reusable script so you can refresh the dataset later if needed. Estimated delivery: 2–3 days. Looking forward to working with you. Best regards, Abdelrahman

@mshandu3

Hi Please view my profile to see an example of a project I have done scraping data from Google maps. I would like to avail myself immediately for this job. Sincerely, Busisiwe