How to Scrape ZoomInfo Data in 2025 Using ProxyTee

ZoomInfo is a powerful platform for gathering in-depth company and professional data. However, extracting this valuable information can be challenging due to strict security measures that prevent automated access. In this guide, we’ll explore the best practices for scraping ZoomInfo, discuss the limitations of traditional scraping methods, and show how ProxyTee’s residential proxies provide a seamless solution for large-scale data extraction.

What is a ZoomInfo Scraper?

A ZoomInfo scraper is an automated tool designed to extract company and employee information from the ZoomInfo platform. It can retrieve details such as:

• Company Information: Business names, industries, revenue, headquarters locations, and employee counts.
• Employee Details: Names, job titles, emails, and phone numbers.
• Industry Insights: Competitors, market trends, and company hierarchies.

Scraping ZoomInfo can be done manually using browser automation tools like Selenium or Puppeteer, but this approach faces many challenges due to ZoomInfo’s anti-scraping measures.

Challenges of Scraping ZoomInfo Manually

ZoomInfo implements multiple layers of protection to prevent data extraction, including:

• Advanced Bot Detection: Techniques like CAPTCHA challenges, browser fingerprinting, and behavioral tracking can detect and block automated scrapers.
• IP Bans and Rate Limiting: Frequent requests from a single IP address trigger 429 (Too Many Requests) errors, making it difficult to scrape at scale.
• JavaScript-Rendered Content: ZoomInfo relies on JavaScript to load content dynamically, requiring a headless browser for scraping, which is often detected and blocked.

Because of these challenges, a simple Python script using libraries like Requests and BeautifulSoup is insufficient. Instead, a browser automation approach using Selenium is required.

Manual Scraping with Python and Selenium

To demonstrate the difficulties of manual scraping, let’s walk through a Python script that extracts company information from ZoomInfo using Selenium.

1️⃣ Step 1: Project Setup

Ensure you have Python 3 installed and create a virtual environment:

mkdir zoominfo-scraper  
cd zoominfo-scraper  
python -m venv env  

Activate the virtual environment:

# On Linux or macOS:
./env/bin/activate

# On Windows:
env\Scripts\activate

Install Selenium:

pip install -U selenium

2️⃣ Step 2: Initializing the WebDriver

Set up a Selenium WebDriver to control Chrome:

from selenium import webdriver  
from selenium.webdriver.chrome.service import Service  

driver = webdriver.Chrome(service=Service())  

3️⃣ Step 3: Navigating to a ZoomInfo Page

Use Selenium’s get() method to access a target company page:

driver.get("https://www.zoominfo.com/c/nvidia-corp/136118787")  

4️⃣ Step 4: Extracting Company Details

Use CSS selectors to locate and extract elements from the webpage:

from selenium.webdriver.common.by import By  

name_element = driver.find_element(By.CSS_SELECTOR, ".company-name")  
company_name = name_element.text  

subtitle_element = driver.find_element(By.CSS_SELECTOR, ".company-header-subtitle")  
subtitle = subtitle_element.text  

5️⃣ Step 5: Extracting Additional Information

ZoomInfo organizes data within sections that require precise navigation. Below is an example of extracting key details such as headquarters location, phone number, revenue, and stock symbol:

def extract_info(text_container_elements, label_name):
    for element in text_container_elements:
        label = element.find_element(By.CSS_SELECTOR, ".icon-label").text.strip()
        if label == label_name:
            return element.find_element(By.CSS_SELECTOR, ".content").text
    return None  

about_section = driver.find_element(By.CSS_SELECTOR, "app-about")  
containers = about_section.find_elements(By.CSS_SELECTOR, ".icon-text-container")  

headquarters = extract_info(containers, "Headquarters")  
phone_number = extract_info(containers, "Phone Number")  
revenue = extract_info(containers, "Revenue")  
stock_symbol = extract_info(containers, "Stock Symbol")  

6️⃣ Step 6: Saving Data to a JSON File

import json  

company_data = {  
    "name": company_name,  
    "subtitle": subtitle,  
    "headquarters": headquarters,  
    "phone_number": phone_number,  
    "revenue": revenue,  
    "stock_symbol": stock_symbol  
}  

with open("company.json", "w") as json_file:  
    json.dump(company_data, json_file, indent=4)  

7️⃣ Step 7: Running the Script

Execute the script to extract and save company data:

python scraper.py  

The Limitations of Manual Scraping

While the above script works in theory, it quickly encounters issues:

• Headless Browsers Are Blocked: ZoomInfo detects automated browsing and prevents access.
• IP Address Restrictions: Repeated requests result in IP bans.
• CAPTCHAs and Session Tracking: Additional verification methods make automation unreliable.

For effective data extraction at scale, a robust proxy solution is needed.

The Best Alternative: Using ProxyTee’s Residential Proxies

Rather than struggling with ZoomInfo’s security measures, ProxyTee’s Unlimited Residential Proxies provide a seamless way to access data efficiently.

1. Why Choose ProxyTee for ZoomInfo Scraping?

• • Bypassing Blocks – IP rotation is essential for avoiding IP bans, and the Auto-Rotation feature in ProxyTee makes it straightforward. This makes sure your scrapers remain active and undetected. ProxyTee Residential Proxies ensure requests originate from different IPs.
  • Global IP Coverage: With access to over 20 million IPs from 100+ countries, you can appear to be browsing from any location that’s needed. This can provide location-specific data that isn’t available via any other method.
  • Multiple Protocol Support:ProxyTee proxies support both HTTP and SOCKS5 protocols to match your requirements. Use HTTP for basic web traffic or use SOCKS5 for more advanced networking.
  • No Bandwidth Caps: Using the unlimited bandwidth, allows large-scale data extraction without worrying about added costs. ProxyTee’s unlimited bandwidth, ensure you won’t be charged extra for usage, especially with high-traffic data gathering activities.
  • Simple API: API Integration facilitates the automation of your proxy tasks through simple, consistent endpoints.
  • User-friendly interface ProxyTee prioritizes simplicity with a clean, intuitive graphical user interface (GUI).

2. How to Use ProxyTee Proxies with Selenium

Configure the WebDriver to use a rotating residential proxy:

from selenium.webdriver.chrome.options import Options  

proxy = "your-proxytee-proxy-address:port"  
chrome_options = Options()  
chrome_options.add_argument(f"--proxy-server={proxy}")  

driver = webdriver.Chrome(service=Service(), options=chrome_options)  

This method ensures that every request comes from a different residential IP, bypassing IP bans and rate limits.

While manual ZoomInfo scraping using Selenium is possible, it is time-consuming, unreliable, and prone to IP bans. ProxyTee’s residential proxies provide a much simpler, scalable, and cost-effective solution. With automatic IP rotation, global coverage, and unlimited bandwidth, ProxyTee is the ideal choice for hassle-free data extraction.

If you’re looking to collect ZoomInfo data efficiently, ProxyTee’s Residential Proxies offer the best performance and reliability. Get started today and take advantage of the best proxy solution for web scraping!