Amazon Books Bestseller Charts Scraper

Scrape Amazon book bestseller charts including Best Sellers, Hot New Releases, Movers and Shakers, and Most Wished For. Collects rank, title, author, ASIN, format, price, star rating, and review count across book sub-categories with timestamped snapshots for trend analysis.

What it does

For each chart type, category and Amazon site you choose, the actor returns the chart entries with rank, title, author, ASIN, price, rating, and format, each saved as a dataset record with a scraped_at timestamp.

• Eight Amazon sites in one run: amazon.com, .co.uk, .de, .fr, .it, .es, .ca and .com.au, mixed freely.
• Subcategories: switch on includeSubcategories to also get the charts of every subcategory, up to three levels down.
• Paste chart URLs: give categoryUrls instead of picking charts and nodes by hand.
• Numeric prices with a currency code, not price strings that need cleaning.
• Per-category limit with maxItemsPerCategory, so a wide subcategory sweep returns the top few of each.

This makes it ideal for building rank-over-time datasets — schedule it hourly to track how books move up and down the charts.

Input

Field	Type	Default	Description
chartTypes	array (select)	["best_sellers"]	Chart types to scrape: best_sellers, hot_new_releases, movers_and_shakers, most_wished_for
categoryNodes	array	[""] (root Books)	Numeric Amazon category node IDs. Leave empty for root Books. Examples: "3" = Business & Money, "4" = Children's, "5" = Computers
marketplaces	array (select)	["amazon.com"]	Amazon sites to read: amazon.com, amazon.co.uk, amazon.de, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au
categoryUrls	array	none	Amazon Books chart page URLs from any listed site. When set, chartTypes, categoryNodes and marketplaces are ignored
includeSubcategories	boolean	false	Also scrape each category's subcategories
subcategoryDepth	integer	1	Subcategory levels to follow, 1 to 3 (with includeSubcategories)
maxItemsPerCategory	integer	none	Stop after this many records from each category chart
maxItems	integer	10	Maximum number of records per run. Set it high when you include subcategories: charts are read in order, parent first

Category node IDs differ per Amazon site; copy them from the chart URL on that site.

Example input

{
  "chartTypes": ["best_sellers", "hot_new_releases"],
  "categoryNodes": ["3", "6"],
  "maxItems": 200
}

Top 10 of every subcategory under Business & Money on amazon.com:

{
  "chartTypes": ["best_sellers"],
  "categoryNodes": ["3"],
  "includeSubcategories": true,
  "maxItemsPerCategory": 10,
  "maxItems": 1000
}

Charts from different sites in one run, by URL:

{
  "categoryUrls": [
    "https://www.amazon.com/gp/bestsellers/books/3",
    "https://www.amazon.co.uk/gp/bestsellers/books/68",
    "https://www.amazon.de/gp/new-releases/books/187254"
  ],
  "maxItems": 300
}

Output

Each record contains:

Field	Type	Description
chart_type	string	Chart type: best_sellers, hot_new_releases, etc.
marketplace	string	Amazon site the record came from, e.g. amazon.com, amazon.de
category	string	Category name, e.g. Business & Money
category_node	string	Amazon category node ID
category_url	string	URL of the bestseller chart page this record was scraped from
rank	integer	Current rank on the chart
title	string	Book title
author	string	Author name
asin	string	Amazon Standard Identification Number
format	string	Format: Paperback, Kindle, Hardcover, Audible
price	number	Current price as a number, in the currency given in currency
list_price	number	Original list price (not shown on chart pages, always null)
currency	string	ISO currency code the price was shown in (e.g. USD, GBP, EUR), null when no price was shown
star_rating	number	Average star rating (1.0–5.0)
review_count	integer	Total number of customer reviews
cover_url	string	Product cover image URL
product_url	string	Amazon product page URL
scraped_at	string	ISO-8601 timestamp of when this record was delivered to you

Sample output record

{
  "chart_type": "best_sellers",
  "marketplace": "amazon.com",
  "category": "Business & Money",
  "category_node": "3",
  "category_url": "https://www.amazon.com/best-sellers-books-Amazon/zgbs/books/3",
  "rank": 5,
  "title": "Unreasonable Hospitality",
  "author": "Will Guidara",
  "asin": "0593418573",
  "format": "Hardcover",
  "price": 16.00,
  "currency": "USD",
  "star_rating": 4.8,
  "review_count": 6638,
  "cover_url": "https://images-na.ssl-images-amazon.com/...",
  "product_url": "https://www.amazon.com/dp/0593418573",
  "scraped_at": "2026-05-23T04:19:54.245Z"
}

Common category node IDs

Node ID	Category
(empty)	All Books (root)
1	Arts & Photography
2	Biographies & Memoirs
3	Business & Money
4	Children's Books
5	Computers & Technology
6	Cookbooks, Food & Wine
12290	Christian Books & Bibles
4366	Comics & Graphic Novels

Use cases

• KDP analytics: Track how your own book climbs (or falls) across categories
• Publisher research: Monitor competitor titles and pricing
• Trend datasets: Build hourly rank-history time series for ML/analytics
• Retail intelligence: Price monitoring and format mix analysis

Scheduling

This actor is designed for recurring use. Schedule it hourly via Apify's scheduler to capture rank snapshots over time and build a rank-over-time dataset.

Notes

• Amazon's bestseller charts update hourly
• Each category chart returns the full top 100 (ranks 1–100, no gaps) when Max Items allows it. Subcategories and extra sites add more charts.
• Amazon prices by visitor location, so each Amazon site is read as a local shopper sees it: amazon.de prices are the ones a shopper in Germany sees, and amazon.com.au prices are in AUD. currency states what the page actually showed
• Gets past Amazon's bot detection, run after run
• chartTypes and categoryNodes are validated up front — an unrecognized chart type or a non-numeric category node fails the run immediately with the invalid value named, instead of quietly returning no data