If you're trying to scrape Amazon data, you've probably hit a wall at some point. Maybe you started with something like Oxylabs thinking it would solve everything, only to realize it's not quite what you expected. I've been there too.
The thing is, most "Amazon scrapers" aren't really Amazon scrapers at all. They're proxy services that happen to work with Amazon pages. There's a big difference, and it matters more than you might think.
So What Makes an Amazon Scraper Different?
Let me break down what I've learned after years of working with Amazon data:
The Proxy Approach (What Oxylabs Does)
Oxylabs is fundamentally a proxy network. Their Amazon scraping is basically their general web scraper API with Amazon support tacked on. It works for simple stuff. You can get prices, titles, ratings. But when you need something deeper? You're stuck writing XPath selectors yourself, and even then, you'll only get what's visible on the page.
I've seen developers spend hours trying to extract data that just isn't there in the HTML. That's frustrating.
The Platform Approach (What We Built)
Easyparser isn't a proxy service trying to scrape Amazon. It's built specifically for Amazon data extraction from day one. We don't just parse HTML. Instead, we pull from the same data sources Amazon uses internally.
That means we can give you things like sales rank history, actual product dimensions (not just what's on the page), and sales trends over time. Stuff that generic scrapers simply can't access, no matter how good their XPath skills are.
Where Oxylabs Falls Short
Don't get me wrong. Oxylabs is great at what it does. Their proxy network is massive, and their general web scraper API works well for scraping random websites. But Amazon? That's where things get tricky.
When I tried using Oxylabs for Amazon data, here's what I found: it basically gives you the HTML, does some basic parsing, and that's it. You can get prices, titles, ratings. That's the obvious stuff. But try to get product dimensions for FBA calculations? Sales rank history? Actual sales volume trends? You're out of luck unless you build your own parser using their Custom Parser feature, which means writing XPath selectors yourself [1].
By the time you're done building that parser, you've essentially built your own scraper. At that point, why pay for Oxylabs?
What Makes Easyparser Different
We built Easyparser because we needed something that actually understood Amazon. Not just "can scrape Amazon pages" but "knows how Amazon works."
Instead of treating Amazon like any other website, we built it specifically for Amazon's ecosystem. That means we can access data sources that generic scrapers can't even see. We're not just parsing HTML. We're pulling from the same APIs and data feeds Amazon uses internally.
The Data You Actually Need
Here's the stuff that makes a real difference when you're working with Amazon data:
Rank & Dimension: Need to calculate FBA fees? You'll need the actual packaged dimensions and weight, not just what's displayed on the page. Our Rank & Dimension operation gives you BSR plus the real dimensions Amazon uses for logistics. This is the kind of data that saves you money when planning shipments.
Sales Analysis & History: Want to know if a product is trending up or down? Current price tells you nothing. But weekly sales data going back a year? That's what you need to spot trends, forecast demand, and understand whether a product is past its prime or just getting started.
Quick Comparison
Here's how they stack up side by side:
| Feature | Oxylabs (Web Scraper API) | Easyparser |
|---|---|---|
| Core Service | Proxy Provider with Generic Scraper | Specialized Amazon Data Platform |
| Data Depth | Surface-level (price, title, stock) | Deep & Analytical (sales history, dimensions) |
| Sales Rank (BSR) | ❌ Not Available | ✅ Available (Rank & Dimension Op) |
| Sales History | ❌ Not Available | ✅ Available (1-year weekly history) |
| Product Dimensions | ❌ Not Available | ✅ Available (for logistics) |
| Parsing | Basic automated, advanced requires manual XPath/CSS | Fully automated, structured JSON |
| Ease of Use | Requires technical configuration | Developer-friendly, plug-and-play |
| Pricing Model | Complex, variable per target | Simple, credit-based (1 credit = 1 result) |
How It Works in Practice
Use this operation to track product views and sales numbers in real time and get sales data going back up to 1 year:
import requests
import json
# Get sales analysis and history for a product
params = {
"api_key": "YOUR_API_KEY",
"platform": "AMZ",
"operation": "SALES_ANALYSIS_HISTORY",
"domain": ".com",
"asin": "B0FBF9NG2Y",
"history_range": "12"
}
# Execute the request
api_result = requests.get("https://realtime.easyparser.com/v1/request", params=params)
product_analytics = api_result.json()
print(json.dumps(product_analytics, indent=2))
Try all Easyparser operations for free with our demo package. Sign up now and start using your demo credits →
The Bottom Line
Look, if you just need to get past a captcha and scrape some basic HTML from Amazon pages, Oxylabs will do the job. But if you're trying to make actual business decisions like calculating FBA fees, tracking sales trends, or forecasting demand, you need data that goes deeper than what's on the page.
Easyparser isn't really an "Oxylabs alternative" in the traditional sense. It's a completely different tool for a completely different use case. If you need Amazon data, not just Amazon HTML, you need a platform built for Amazon. Everything else is just a workaround.
References
[1] Oxylabs. (n.d.). Web Scraper API. Retrieved from: https://oxylabs.io/products/scraper-api
[2] Easyparser Documentation. (n.d.). Advanced Operations. Retrieved from: https://easyparser.gitbook.io/easyparser-documentation/real-time-integration
