Goodreads Reviews Scraper

🚀 Supercharge your book research with our comprehensive Goodreads Reviews scraper! Automate collection of detailed book reviews from Goodreads.com. Get complete review data including ratings, review text, reviewer information, dates, and helpful counts. Perfect for authors, publishers, researchers, and book enthusiasts who need accurate, up-to-date review intelligence without manual work.

Target Audience: Authors, publishers, book researchers, literary analysts, marketing professionals, and book enthusiasts
Primary Use Cases: Market research, competitive analysis, sentiment analysis, book marketing, reader insights

What Does Goodreads Reviews Scraper Do?

This tool collects comprehensive book review data from Goodreads.com, supporting both direct URL access and book ID-based searches. It delivers:

• Book Information: Title and book ID
• Reviewer Details: Name and profile URL
• Review Content: Full review text with ratings
• Engagement Metrics: Helpful counts and comment data
• Metadata: Review dates, spoiler status, and review URLs
• Timestamps: When each review was scraped

Business Value: Understand reader sentiment, track book performance, analyze competitor reviews, and gather market intelligence to make data-driven publishing and marketing decisions.

How to use the Goodreads Reviews Scraper - Full Demo

[YouTube video embed or link]

Watch this 3-minute demo to see how easy it is to get started!

Input

To start Goodreads Reviews web scraping, simply fill in the input form. You can scrape Goodreads reviews based on:

• startUrl - A direct URL to a Goodreads book reviews page (e.g., https://www.goodreads.com/book/show/4671.The_Great_Gatsby/reviews). When using startUrl, all filters must be included in the URL itself. Cannot be used together with bookId, sort, or rating.
• bookId - The Goodreads book ID (found in the book's URL). Cannot be used together with startUrl.
• sort - Sort reviews by: default (default order), rating (by rating), or date_added (by date). Only works with bookId, not with startUrl.
• rating - Filter reviews by rating (1-5 stars). Only works with bookId, not with startUrl.
• maxItems - Maximum number of reviews to collect. Free users: Required, maximum 50. Paid users: Optional, maximum 1,000,000.

Here's what the filled-out input schema looks like:

And here it is written in JSON:

{
    "bookId": "4671",
    "sort": "default",
    "maxItems": 10
}

Output

After the Actor finishes its run, you'll get a dataset with the output. The length of the dataset depends on the amount of results you've set. You can download those results as an Excel, HTML, XML, JSON, and CSV document.

Here's an example of scraped Goodreads review data you'll get if you decide to scrape "The Great Gatsby" reviews:

{
    "imageUrl": null,
    "reviewId": "Y5vd7PFolPnJDnptbCJRfA",
    "bookId": "4671",
    "bookTitle": "The Great Gatsby",
    "reviewerName": "Nataliya",
    "reviewerProfileUrl": "https://www.goodreads.com/user/show/3672777-nataliya",
    "rating": 5,
    "reviewDate": "5/2/2010",
    "reviewText": "Oh Gatsby, you old sport, you poor semi-delusionally hopeful dreamer...",
    "reviewUrl": "https://www.goodreads.com/review/show/Y5vd7PFolPnJDnptbCJRfA",
    "helpfulCount": 2435,
    "spoiler": false,
    "scrapedTimestamp": "2025-11-24T23:13:16.439Z"
}

What You Get:

• Book Information: Track which book each review belongs to
• Reviewer Insights: Understand who is reviewing and their profile information
• Rating Analysis: See star ratings to gauge overall sentiment
• Review Content: Full text for sentiment analysis and content research
• Engagement Metrics: Helpful counts show which reviews resonate with readers
• Spoiler Detection: Know which reviews contain spoilers
• Timestamps: Track when reviews were posted and scraped

Download Options: CSV, Excel, or JSON formats for easy analysis in your preferred tools

Why Choose the Goodreads Reviews Scraper?

• Complete Data Collection: Get all review fields including ratings, text, dates, and engagement metrics in one automated process
• Flexible Search Options: Use direct URLs or book IDs with sorting and filtering options
• Time Savings: Collect hundreds of reviews in minutes instead of hours of manual copying
• Accurate Data: Extract structured data directly from Goodreads with proper formatting
• Scalable: Process up to 1,000,000 reviews for comprehensive market analysis

Time Savings: What would take hours of manual copying and pasting is now done automatically in minutes
Efficiency: Collect comprehensive review data at scale for multiple books simultaneously

How to Use

1. Sign Up: Create a free account w/ $5 credit (takes 2 minutes)
2. Find the Scraper: Visit the Goodreads Reviews Scraper page
3. Set Input: Add your book ID or start URL (we'll show you exactly what to enter)
4. Run It: Click "Start" and let it collect your review data
5. Download Data: Get your results in the "Dataset" tab as CSV, Excel, or JSON

Total Time: Less than 5 minutes from sign-up to downloaded data
No Technical Skills Required: Everything is point-and-click

Business Use Cases

Authors & Publishers:

• Track reader sentiment for your books
• Analyze competitor book reviews
• Monitor review trends over time
• Gather feedback for book improvements

Market Researchers:

• Analyze book market trends
• Study reader preferences and patterns
• Conduct sentiment analysis on book reviews
• Track genre popularity

Book Marketing Professionals:

• Identify influential reviewers
• Track review engagement metrics
• Monitor book launch performance
• Gather testimonials and quotes

Data Analysts:

• Build comprehensive book review databases
• Create regular market reports
• Support publishing decisions with data
• Analyze reader behavior patterns

Using Goodreads Reviews Scraper with the Apify API

For advanced users who want to automate this process, you can control the scraper programmatically with the Apify API. This allows you to schedule regular data collection and integrate with your existing business tools.

• Node.js: Install the apify-client NPM package
• Python: Use the apify-client PyPI package
• See the Apify API reference for full details

Frequently Asked Questions

Q: How does it work?
A: Goodreads Reviews Scraper is easy to use and requires no technical knowledge. Simply provide a book ID or reviews URL, set your preferences, and let the tool collect the review data automatically.

Q: How accurate is the data?
A: The scraper extracts data directly from Goodreads.com, ensuring high accuracy and up-to-date information. All fields are captured as they appear on the website.

Q: Can I scrape multiple books?
A: Yes! You can run multiple scraper instances for different books, or use the Apify API to automate collection across multiple books.

Q: Can I schedule regular runs?
A: Yes, you can schedule regular runs using Apify's scheduling features or the API to keep your review data up-to-date automatically.

Q: What if I need help?
A: Our support team is available to help you get the most out of this tool. Contact us through the Apify platform for assistance.

Q: Is my data secure?
A: Yes, all data is processed securely through Apify's platform. Your scraped data is stored securely and only accessible to you.

Integrate Goodreads Reviews Scraper with any app and automate your workflow

Last but not least, Goodreads Reviews Scraper can be connected with almost any cloud service or web app thanks to integrations on the Apify platform.

These includes:

• Make
• Zapier
• Slack
• Airbyte
• GitHub
• Google Drive
• and much more.

Alternatively, you can use webhooks to carry out an action whenever an event occurs, e.g. get a notification whenever Goodreads Reviews Scraper successfully finishes a run.

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Need Help? Our support team is here to help you get the most out of this tool.

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⚠️ Disclaimer: This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Goodreads or any of its subsidiaries. All trademarks mentioned are the property of their respective owners.