Airbnb dataset: a resource for B&B data

The Pitfalls of Data Capture in B&B

Recently, a lot of friends doing B&B operation approached me to complain, saying that they wanted to analyze the listing data on Airbnb, and as a result, just after grabbing a few pages, their IPs were blocked, which is something I am too familiar with, and I fell into trouble last year when I helped a hotel chain to do a competitor's analysis. At that time, I used my office network to capture the data, the first 200 articles were fine, but suddenly the CAPTCHA jumped, and then after half an hour, the IP directly into the blacklist.

It was later discovered that the platform's anti-crawl mechanism was more sophisticated than expected.Much smarter... They don't just look at the frequency of visits, they check:

1. whether the request header looks like a real browser
2. whether there is any irregularity in the interval between clicks as in the case of human operations.
3. whether the geographic location of the IP address matches the location of the B&B.

How Proxy IPs Became a Data Acquisition Tool

A real life case must be mentioned here. I have a trainee doing B&B pricing analysis in Chengdu, and need to monitor the listing data in Sanya in real time. Using a local IP just checked 3 times and triggered the wind control, then changed theipipgos dynamic residential IPs, successfully simulating the browsing behavior of real visitors.

Focus on the wonders of dynamic residential IPs. LikeipipgoThe rotation pool automatically changes IPs for each request, which is especially suitable for scenarios that require multi-region data comparison. For example, if you simultaneously capture the prices of B&Bs in the second and fifth ring roads of Beijing, and visit them with IPs from different regions, the platform will consider them natural traffic.

Teach you how to use proxy IP to pick up data

Here's a live Python example (don't worry about reading it, just follow along):

import requests
from random import choice

 Proxy pool from ipipgo
proxies = [
    "http://user:pass@23.88.12.34:8888",
    "http://user:pass@45.67.89.12:8888".
     It is recommended to have at least 50 IPs here
]

url = "https://www.airbnb.cn/room/123456"

for _ in range(100):
    try: resp = requests.get(url, url)
        resp = requests.get(url,
            proxies={"http": choice(proxies)}, headers={"User-Agent": "Mozilla 5.0.
            headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0)..."}
        )
        print(resp.text[:200]) Prints the first 200 characters to see if it succeeded.
    except Exception as e.
        print("Retrying with a different IP address:", e)

There are three key points:① IP pool should be large enough ② randomly selected IP ③ request header camouflage. When using ipipgo's service, remember that their API supports automatic endpoint IP replacement, which is much less work than maintaining a proxy pool yourself.

Five Questions Frequently Asked by White People

Q1: Why is a residential IP necessary?
A: B&B platforms are particularly sensitive to data center IPs. Residential IPs look like real tourists, as if wearing a mask at a masquerade is more natural than not.

Q2: How much IP volume is needed per day?
A: Look at the collection frequency. It is recommended that each IP does not exceed 30 requests per hour, and if you want to collect 1,000 pieces of data, it is more prudent to prepare 50 IPs.

Q3: What should I do if I encounter a CAPTCHA?
A: Immediately stop the current IP request, change to a new IP and reduce the frequency. ipipgo's package comes with an automatic switching function, which can save a lot of work.

Q4: Is data scraping legal?
A: As long as user privacy is not involved, the simple collection of public listing information is a legitimate competitive analysis. However, remember to set reasonable collection intervals.

Q5：How to choose an agent service provider?
A: Focus on IP purity (whether it is labeled by the platform) and response speed. Like ipipgo's IP pool is updated weekly with 20%, which basically avoids blacklists.

A little bit of heartfelt experience.

Last year, when I helped my client to do the Southeast Asia B&B market analysis, I used seven or eight proxy services. Some cheap IP look cost-effective, the result of 30% IP are platform blacklist. Later changed ipipgo exclusive IP package, collection efficiency directly doubled. Their customer service has a function that is particularly useful--IP warm-up detectionThe IP address of a blocked IP segment can be excluded in advance.

Two final reminders of two potholes for newbies:
1. Don't buy a shared IP for cheap, it's no different from squeezing into a bus, one person will be blocked and the whole bus will suffer.
2. Don't collect at regular intervals; humans don't pause for seconds when browsing the web.

If you're just starting out with proxy IPs, we recommend starting directly with ipipgo's experience package. They send new users a 3-day trial period, just enough to test the collection process. Remember, the collection tool is just a means to an end, the point is to see the real needs of the B&B market through the data.