Scraping Amazon pages could seem pretty straightforward from the outside. You're just grabbing product details, reviews, or pricing data. However, Amazon's bot detection mechanisms can make the process quite painful.
Amazon employs advanced algorithms and machine learning to track and block IP addresses that exhibit bot-like behavior. Hence, it responds with the CAPTCHA and "access denied" blocks.
Luckily, you can overcome these challenges using proxies. By hiding your original IP address, proxies allow you to disguise your web activity and mimic natural user behavior.
In this article, we'll cover why you need proxies, the best proxy providers in 2024, and how to implement proxies for scraping Amazon.Â
Why Do You Need a Proxy When Scraping Amazon?
Given Amazon's robust anti-scraping measures, the key to successful web scraping lies in configuring your scraper to operate stealthily. Proxies play a crucial role in this process.
Bots typically generate excessive request volumes in short periods, exhibiting predictable patterns that make it easy for Amazon to flag and block your requests.
Also, Amazon employs rate-limiting technologies that can result in IP bans, CAPTCHA pages, or other technologies that require human verification.
You need proxies to circumvent these restrictions. They mask your original IP address, eliminating the possibility of a direct IP ban.
You can also rotate proxies to distribute traffic across multiple servers. This makes your requests appear to originate from unique users and ensures no IP gets flagged for exceeding rate limits.
Additionally, Amazon's product data, such as prices, shipping details, and availability, often varies by location. If you're interested in comparing data from different regions, proxies are essential.
They're not just about evading detection. They also eliminate geo-restrictions, allowing you to scrape as if you're browsing from actual user locations. This versatility enables you to gather more comprehensive data from different parts of the world.
That said, you can only achieve all this using the best proxy for scraping Amazon. Let's explore a few.
Best Amazon Scraping Proxies in 2024
Residential proxies are the best proxy types for avoiding anti-scraping restrictions as they use actual IP addresses assigned to real devices by their internet service providers. Below are three of the best residential proxy providers for scraping Amazon.
1. ZenRows
ZenRows' Residential Proxies allows you to access all the data you need from any web page, including Amazon. Its pool of over 55 million proxies gives you access to geo-restricted pages and location-specific content from over 185 countries.
ZenRows is much more than your conventional proxy provider. It takes things multiple steps further by automatically switching IPs to enable you to circumvent Amazon's anti-bot restrictions.
This also boosts overall performance as ZenRows learns from each request and selects the best-performing proxy for optimal results. It also ensures uninterrupted data flow by automatically handling all security challenges for you, including CAPTCHAs.
ZenRows supports multiple languages and is easy to integrate with other scraping tools, streamlining your workflow and reducing the need for consistent manual interventions.
Despite offering such a robust feature set, ZenRows remains affordable with a competitive pricing structure that ensures you pay only for what you use.Â
ZenRows Pricing
- Developer plan (12+ GB), priced at $5.5 per GB.
- Business 500 plan (100+ GB), priced at $4.5 per GB.
- Business 3K plan (1TB), priced at $2.8 per GB.
2. Smartproxy
Another leading proxy for scraping Amazon is Smartproxy. With proxies across multiple countries, this proxy provider allows you to choose from different proxy types, including data center and residential proxies.
It also offers numerous features that make it easy to get up and running, such as an intuitive dashboard and ready-made scraper templates.
Smartproxy also supports state and city-level targeting. This can be particularly valuable when accessing targeted data is critical. Large-scale tasks, such as A/B testing of products or their performance across multiple cities or states, significantly benefit from this feature.Â
Smartproxy Pricing
- Pay as you go, starting at $7 per GB
- 100 GB, priced at $4.5 per GB
- 1000 GB, priced at $3 per GB
3. Shifter
Like Smartproxy, Shifter is another top proxy provider offering different proxy types, including residential and data center proxies. However, Shifter provides the added advantage of unlimited bandwidth, which makes it a great option for large-scale scraping, as you don't need to worry about data caps.
Shifter has other features, such as high uptime, ultra-low latencies, easy-to-configure API, high success rate, rotating residential proxies, and more. Its pool of proxies spreads across every country, allowing you access to geo-restricted data from almost any part of the world.
To allow you to focus on what matters rather than the intricacies of web scraping, Shifter provides an Amazon API that lets you quickly extract real-time data from Amazon, returning results in neatly structured JSON format.
Shifter Pricing
- 5 rotating residential proxies at $99.98.
- 25 rotating residential proxies at $299.99.
- 50 rotating residential proxies at $599.99.
How to Scrape Amazon with a Proxy
Choosing the best proxy for scraping Amazon is only half the battle. Proper proxy implementation is critical to ensure smooth and uninterrupted data flow. In this section, we'll get practical with a step-by-step guide on how to scrape Amazon using proxies.
Implementing Proxies and Rotating Them Manually
For this tutorial, we'll use Python and its powerful Requests library.
To follow along, ensure you have the Requests library installed. You can do so using the following command:
pip3 install requests
Requests allow you to implement proxies in your request using the proxies
parameter.
But before we specify a proxy, here's a basic scraper that makes a standard HTTP request to https://httpbin.io/ip
, an API endpoint that returns the requesting agent's IP address.
# import the required module
import requests
# make a GET request to target website
response = requests.get("https://httpbin.io/ip")
# print HTML content
print(response.text)
Since this code doesn't include any proxies, it'll return your machine's IP address, like in the example below:
{
"origin": "108.01.235.405:1590"
}
Now, specify a proxy and observe the difference in results. To do this, define your proxy details and pass them as parameters in your request.
We've grabbed a proxy from the Free Proxy List. Here's the complete code:
# import the required module
import requests
# define a proxy dictionary
proxy = {
"http": "http://66.29.154.105:3128",
"https": "http://66.29.154.105:3128",
}
# make a GET request to target website using the specified proxy
response = requests.get("https://httpbin.io/ip", proxies=proxy)
# print HTML content
print(response.text)
If done correctly, you'll notice that your result differs from the previous non-proxy code but matches your proxy's IP address.
{
"origin": "66.29.154.105:46844"
}
Awesome! That's how to specify a proxy for scraping Amazon.
However, since Amazon employs sophisticated techniques that track IP addresses, your proxy could eventually get flagged and blocked. To avoid this, you must rotate proxies between requests.
Here's a step-by-step guide on how to achieve that.
Start by defining your proxy pool.
To set up this example, we've grabbed five unique proxies from the Free Proxy List. If these aren't working at the time of reading, you can grab some new ones.
# import the required modules
import requests
# define a proxy list
proxy_list = [
"http://66.29.154.105:3128",
"http://47.242.47.64:8888",
"http://41.169.69.91:3128",
"http://50.172.75.120:80",
"http://34.122.187.196:80"
]
After that, randomly select a proxy from your proxy list using Python's random.choice()
method. You must import the random module for this to work.
# ...
import random
# ...
# choose a proxy at random
proxy = random.choice(proxy_list)
Next, define a proxies
dictionary specifying the proxies for HTTP and HTTPS requests.
#...
# specify proxies to be used for HTTP and HTTPS requests
proxies = {
'http': proxy,
'https': proxy,
}
Lastly, make a GET request using the randomly selected proxy.
#...
# make a GET request to target website using the specified proxy
response = requests.get("https://httpbin.io/ip", proxies=proxies)
# print HTML content
print(response.text)
That's it.
Put all the steps together to get the following complete code:
# import the required modules
import requests
import random
# define a proxy list
proxy_list = [
"http://66.29.154.105:3128",
"http://47.242.47.64:8888",
"http://41.169.69.91:3128",
"http://50.172.75.120:80",
"http://34.122.187.196:80"
]
# choose a proxy at random
proxy = random.choice(proxy_list)
# specify proxies to used for HTTP and HTTPS requests
proxies = {
'http': proxy,
'https': proxy,
}
# make a GET request to target website using the specified proxy
response = requests.get("https://httpbin.io/ip", proxies=proxies)
# print HTML content
print(response.text)
Run this code multiple times to verify it works. You'll get a different IP address for each request.
Here are the results for three runs.
# request 1
{
"origin": "47.242.47.64:53487"
}
# request 2
{
"origin": "50.172.75.120:11156"
}
# request 3
{
"origin": "34.122.187.196:10843"
}
Congratulations! You've rotated proxies to avoid Amazon's restrictions.
However, you should know we only used free proxies to show you the basics in this example. Free proxies are unreliable due to their short life span. Also, they get blocked easily due to their lower quality and overuse. A better option for scraping Amazon or any websites using anti-bot protection is to use premium proxies like those discussed earlier.
Since ZenRows leads the curve, let's explore how to scrape Amazon using the ZenRows premium residential proxy.
Implementing Proxy Providers - Using ZenRows Residential Proxies
To use ZenRows, sign up and navigate to the ZenRows Proxy Generator page. Your automatically generated residential proxy is at the top of the page.

You can customize the settings by navigating to the Credentials tab and setting a proxy username and password.
Once you're all set up, copy the generated proxy URL and use it with the Requests library, just as in the previous examples.
Your new code should look like this:
# import the required module
import requests
# define a proxy dictionary
proxy = {
"http": "http://<ZENROWS_PROXY_USERNAME>:<ZENROWS_PROXY_PASSWORD>@superproxy.zenrows.com:1337",
"https": "https://<ZENROWS_PROXY_USERNAME>:<ZENROWS_PROXY_PASSWORD>@superproxy.zenrows.com:1338"
}
# make GET request to target website using the specified proxy
response = requests.get("https://httpbin.io/ip", proxies=proxy)
# print HTML content
print(response.text)
ZenRows automatically rotates proxies by default. Thus, this code will return different IPs for each request.
Here's the result for two runs.
# request 1
{
"origin": "2.60.102.197:64587"
}
# request 2
{
"origin": "31.181.240.86:56195"
}
Well done!
Conclusion
Proxies can help bypass Amazon's anti-bot restrictions and grant access to your desired data. You can even increase your chances of avoiding detection by switching IPs between requests, disguising your web activity, and mimicking natural browsing behavior.
However, not all proxies offer the same features. You need a provider that not only provides access to geo-restricted data but can also bypass Amazon's anti-bot restrictions.
ZenRows is one of the top residential proxy providers for this use case. In addition to proxy features, it offers a scraper API and proven techniques for web scraping without getting blocked, helping you bypass any protection system.
Sign up now to try ZenRows for free.