As an experienced web scraping expert who has extracted data from Amazon for years, I can tell you that gaining access to their best sellers data provides a goldmine of actionable insights.
In this comprehensive 2,300 word guide, you‘ll learn insider techniques I‘ve picked up over the years for scraping Amazon top seller data.
Why Scrape Amazon Best Sellers Data?
Here are some of the key benefits of extracting Amazon top sellers data:
Product Research: Analyze pricing, descriptions, images and other attributes of current best-sellers to get product ideas and understand customer demand.
Competitor Benchmarking: See how your products stack up against the top sellers in your niche and identify opportunities to improve listings.
Keyword Research: Uncover the most popular search terms people use to find top products on Amazon.
Market Analysis: Gain insights into rising trends and newly popular products in different categories.
Amazon SEO: Reverse engineer elements of high-ranking products like titles, bullet points and backend keywords.
Amazon PPC: Build more relevant and high-converting product targeting/negative keyword lists.
Amazon FBA: Identify the fastest selling items to source for your Amazon FBA business.
In summary, staying on top of Amazon‘s best sellers provides a wealth of data to fuel nearly all aspects of an ecommerce business. Now let‘s look at the best methods for extracting this data.
Web Scraping to Extract Amazon Top Sellers Data
While Amazon provides an API and bulk data services, these do not include any sales ranking or best sellers data. The only scalable way to get this information is through web scraping.
Over the years, I‘ve found 3 main approaches to scrape Amazon best sellers, each with their own pros and cons:
1. Scrape Best Sellers Pages Directly
The simplest method is to directly scrape Amazon‘s pre-filtered best sellers pages like:
This approach lets you quickly gather products already ranked and filtered by Amazon‘s algorithm.
- Fast and easy extraction of top listings.
- Data already filtered and ranked by Amazon.
- Only includes Amazon‘s pre-selected best sellers.
- Need to scrape each sub-category individually.
- Misses long-tail best sellers.
I recommend this method when you need a quick overview of the most popular products on Amazon. It‘s fast, simple and provides a baseline of top sellers.
2. Scrape Category Listings Sortable by Best Sellers
Rather than just extracting Amazon‘s best sellers pages, you can scrape full category listings sortable by best sellers rank like:
This reveals more comprehensive data including:
- Obscure top sellers only popular within niche markets.
- New best selling products before they land on Amazon‘s main pages.
- Alternative sorting criteria like Newest Arrivals, Price High to Low, etc.
- More flexibility to tailor data to your product niche.
- Additional sorting configurations beyond just best sellers.
- No direct URL – need to simulate filtering on the page.
- More data to scrape and post-process.
I suggest this method when you want to dig deeper into your specific category vs. just getting Amazon‘s pre-filtered best sellers.
3. Custom Scrapers
For maximum flexibility, you can build a custom scraper tailored to extract just the data points you need including:
- Product detail pages
- 3rd party listing info
- Historical price tracking
- Complete customization for your specific needs.
- Integrate external data sources.
- Continuous scraping.
- Requires technical expertise to build and maintain.
- Time-intensive development.
I generally recommend custom scrapers for power users with very specialized needs or companies scraping Amazon at scale.
Now that we‘ve covered the key approaches, let‘s look at tools to simplify Amazon scraping.
Leverage Ready-Made Scrapers to Extract Amazon Data
As an experienced developer, I could build a custom scraper for Amazon data extraction. But in most cases, it‘s faster and more cost effective to leverage an existing web scraping solution.
Here are the key capabilities to look for:
✅ Granular category selection – Scrape any department, category or sub-category.
✅ Flexible sorting – Extract products ranked by consumer best sellers, new releases, price, reviews and more.
✅ Scalable extraction – Scrape thousands of products per hour without blocks or captchas.
✅ Custom filters – Refine extraction by price range, ratings, availability and other criteria.
✅ Data export – Download results in JSON, CSV, Excel, databases and other formats.
✅ Web app – Monitor scraper, view results and manage data in an intuitive dashboard.
✅ Cloud-based – No installation, run scrapers instantly in the cloud.
✅ Affordable pricing – Cost-effective for individuals to enterprises.
Now let‘s walk through a quick example of extracting Amazon data with Apify.
Getting Started: Scraping Amazon Best Sellers with Apify
Apify is my go-to tool for most Amazon scraping projects due to its robust features, scalability and ease of use. Let‘s see it in action:
Step 1 – Create a Free Apify Account
First, sign up for Apify to access their free trial. You can also log in with your GitHub account.
Step 2 – Open the Amazon Best Sellers Scraper
In the Apify Store, search for "Amazon Best Sellers" or go to:
Click "Try for Free" to launch the actor.
Tip: Apify provides pre-made scrapers and automation tools for hundreds of sites – it‘s a great starting point for common scraping tasks!
Step 3 – Configure the Scraper
The main input fields to set are:
Start URL – The base Amazon category like
Max Pages Per Category – Scrape depth into subcategories.
Max Items Per Page – Number of best sellers to extract per page.
I suggest starting with a small sample while testing (1-2 pages, 10-20 items per page).
Step 4 – Run the Scraper
Click "Run" to launch the actor and start scraping Amazon! Progress bars will display scraping status.
Step 5 – Export the Results
Once finished, go to the "Runs" tab and click your run to view output. Select "Export Results" to download the Amazon best sellers dataset as JSON, CSV or Excel.
And that‘s it! In just a few minutes you can leverage Apify to extract thousands of Amazon‘s top-selling products.
From here, the data can be imported into Excel, Google Sheets, BigQuery or business intelligence tools for further analysis and visualization. The possibilities are endless!
Next let‘s look at some pro tips and advanced techniques to take your Amazon scraping to the next level.
Pro Tips for Power Users: Advanced Amazon Scraping Techniques
Over the years, I‘ve picked up some useful tricks to go beyond basic Amazon scraping:
🛒 Scrape International Amazon Domains
Expand your market research by extracting best sellers data from other Amazon country sites:
- amazon.com (USA)
- amazon.co.uk (UK)
- amazon.de (Germany)
- amazon.fr (France)
- amazon.co.jp (Japan)
- amazon.cn (China)
Apify makes it easy to switch Start URLs across domains.
📈 Track Best Sellers Over Time
Schedule your scraper to run on a recurring basis to reveal product trajectory:
Daily scraping -> monitor daily rankings
Weekly scraping -> analyze weekly trends
Monthly scraping -> identify new hits
📊 Interactive Data Analysis
Import results into BI tools like Data Studio for interactive dashboards:
🤖 Enrich Data with External Sources
Cross-reference your Amazon data with other APIs and datasets:
- Google Trends (search volume)
- SEMrush (related keywords)
- Social media ads libraries (competitor spend)
- Product feeds (pricing)
The options for expanding your analysis are nearly endless!
Key Takeaways: Extracting Insights from Amazon Data
In summary, here are the key lessons I‘ve learned for unlocking Amazon‘s data:
Scraping Amazon best sellers provides invaluable market intelligence for ecommerce brands and marketers. Product research, competitor tracking, advertising and more can be powered by this data.
Leverage web scraping to gather Amazon top sellers data at scale. While Amazon limits access to sales data in their APIs, scraping levels the playing field.
Ready-made tools like Apify simplify the extraction process for most use cases, without the cost of building and maintaining a custom web scraper.
With the right approach, extracting Amazon data is fast, affordable and scalable. You can go from zero to insights in no time.
Creative analysis and enrichment can extract even deeper strategic value from the scraped data. The sky‘s the limit once you have the data!
I hope this guide provided an insightful overview of professionally scraping Amazon best sellers data from my years of experience. Let me know if you have any other questions!
To get hands-on with scraping Amazon yourself, sign up for a free Apify account using the link below: