ZoomInfo Crawler: B2B Data Collection Solution

Engage in data collection bosses look over, hand in hand to teach you to use the proxy IP grip ZoomInfo wool!

Recently, some foreign trade friends complained to us that the enterprise data on ZoomInfo could not be captured. Either the account is blocked, or the webpage is loading in circles. I'm familiar with this matter, so I'm going to break it into pieces and give you some tips.

ZoomInfo catches three big pitfalls, how many of them have you stepped in?

Let's start with a few common rollover sites:

1. Just after 200 pieces of data are crawled, the IP is blacklisted.
2. The webpage shows 403 error even though the crawler is on.
3. The information of enterprises in different regions can't be loaded.

Nine times out of ten, it's the IP exposure that's the problem, and ZoomInfo's techies aren't exactly a pushover.High-frequency access, fixed IP, abnormal operationThese are a few traits that grab people.

Proxy IP is the law of true flavor

This thing is, quite frankly.The vest that's covering for you.The ZoomInfo site sees the access log as if it were a normal user browsing the site. For example, if you use ipipgo's residential proxy and change the IP address of a real person for every request, ZoomInfo will see the access logs as if it were a normal user browsing, and you won't be able to tell if it's a machine or a real person.

hands-on practical tutorial

Take Python for example, and use ipipgo's proxy service to mess with data collection:

import requests
from itertools import cycle

 List of proxies from the ipipgo backend
proxies = [
    "http://user:pass@gateway.ipipgo:9020",
    "http://user:pass@gateway.ipipgo:9021".
     ... Prepare at least 20+ nodes
]

proxy_pool = cycle(proxies)

for page in range(1, 100): current_proxy = next(proxy_pool)
    current_proxy = next(proxy_pool)
    try: current_proxy = next(proxy_pool)
        response = requests.get(
            "https://www.zoominfo.com/search",
            proxies={"http": current_proxy}, headers={"User/Agent": "Mozilla/5.0"),
            headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0) what's randomized"}, timeout=10
            timeout=10
        )
         Add your parsing code here...
        print(f "Page {page} captured successfully!")
    except Exception as e.
        print(f "Failed with {current_proxy}, automatically switching to the next one.")

Focused attention:Never use Python's default User-Agent in headers. It is recommended to randomly change the browser logo every 50 requests.

QA time (bosses often ask)

Q: Is it okay to use a free proxy?
A: Don't be ridiculous! Those public proxies have long been recorded by ZoomInfo small book, with ten hanging nine. ipipgo's exclusive proxies, although it costs money, but wins in the IP clean and stable.

Q: How to set the frequency of IP switching?
A: Depending on the amount of data, the general recommendation:

- Grabbing 10,000 entries per day: changing IPs every 100 entries
- Grab 50,000+ data: change every 20 items
- Cross-country data collection: different countries IP should be used separately

Q: What makes ipipgo better than others?
A: His family has three great skills: 1) real residential IP library, 2) automatically clean up the blacklisted IP, 3) support for accurate location by country/city. The last time I helped a customer grab data from a US medical device company, the success rate directly doubled with a local IP in Los Angeles.

The Ultimate Anti-blocking Magic

Remember this three dos and three don'ts:

✅ To request at random intervals (0.5-3 seconds fluctuation)
✅ To simulate mouse trails
✅ To clean cookies regularly

❌ Don't raid collection in the middle of the night
❌ Do not operate at a fixed point in time
❌ Don't use Chinese IP to capture European and American data.

Finally said a heartfelt, engaged in data collection is a cat and mouse game. With the right tools (such as ipipgo) can take 80% less detours, after all, professional things have to be a professional to do. What do not understand at any time to ask, we have helped more than two dozen foreign trade companies to get the data, good use!