Publishers and authors
Reader language
Favorable to scraping
Collect review comments for comparable books, then tag praise, objections, audience expectations, and repeated language before positioning a launch.
Reviews & ratings$50Free
Goodreads Comments Scraper for CSV Export
This Goodreads comments scraper exports public Goodreads book review pages into a structured CSV for book research, reader sentiment analysis, and publishing market checks. Import the workflow into the UScraper local desktop app, replace the sample review URLs, and collect book title, author, reviewer username, rating, comment date, review text, likes, and page number without building a custom crawler.
Output
CSV
Columns
8
Pages
1-10 URLs
Focus
Reviews
Template
Free
At a glance
Scrape Goodreads reviews into a clean CSV
Goodreads review pages are useful for understanding how readers describe a book, but copying comments by hand makes it hard to compare tone, rating, dates, and engagement. This Goodreads data extractor targets rendered review cards and exports one row per visible comment, with page-level fields repeated so you can filter, group, or join the CSV later.
The bundled workflow starts with 10 sample URLs for one book review listing, using Goodreads ?page=N pages from 1 through 10. Change the Navigate URL list to another Goodreads book or page range, confirm the save folder, then run the loop. For broader discovery before review extraction, pair this page with the Goodreads Scraper, Google Books Scraper, and Google Search Scraper.
Review text plus context
Export each comment beside the book title, author, reviewer name, rating label, review date, like count, and source page number.
Known-page loop
The template uses an editable finite URL list, so you can review exactly which Goodreads pages are included before running.
Local desktop workflow
The stock export writes to your configured local folder and does not send the CSV through a hosted scraping actor.
Selector fallbacks included
The export columns use multiple Goodreads review-card patterns to handle common markup variants and older page layouts.
Who this is for
Use cases for Goodreads review exports
Researchers and librarians
Book response analysis
Favorable to scraping
Build a review corpus for approved qualitative analysis, reading-list evaluation, or collection notes while keeping the original page number attached.
Agencies and analysts
Market monitoring
Nuanced outcome
Export Goodreads reviews for title-level snapshots, then compare rating labels, dates, likes, and comment themes in a spreadsheet or BI workflow.
Treat the CSV as a research export, not a permission slip to republish reader comments. Review Goodreads policies and your own legal basis before distributing derived datasets.
How to use
Configure the Goodreads reviews scraper workflow
1
Download and import
Download the hosted JSON template, import it into UScraper, and open the workflow graph.
2
Replace review page URLs
Edit the Navigate block with the Goodreads book review pages you are approved to collect. Start with one book and a small page range before scaling.
3
Confirm the CSV path
Structured Export writes goodreads_comments_scraper_reviews.csv with headers enabled and append mode on. Change the save folder for each project or client.
4
Run the loop
UScraper navigates to each URL, waits for the page, waits for review cards, expands visible long comments, exports structured rows, and advances to the next URL.
5
Audit the output
Open the CSV, check a few rows against the live page, and confirm that ratings, dates, comment text, and likes are present before downstream analysis.
Output preview
Goodreads reviews CSV fields
The output mirrors the JSON workflow definition. Goodreads markup can vary by page, so the template uses fallback selectors and JavaScript expressions for titles, authors, reviewer names, rating labels, dates, comment bodies, and likes.
| current_page | book_title | author | username | rating | comment_time | comment_content | likes |
|---|---|---|---|---|---|---|---|
| 1 | I Am Malala | Malala Yousafzai, Christina Lamb | Priya Reads | really liked it | Jan 12, 2026 | A clear and emotional account with strong classroom discussion value. | 18 |
| 2 | I Am Malala | Malala Yousafzai, Christina Lamb | Mateo B | it was amazing | Feb 3, 2026 | The personal details make the historical context much easier to understand. | 42 |
| 4 | I Am Malala | Malala Yousafzai, Christina Lamb | Lena K | liked it | Mar 21, 2026 | Useful for a book club, though some sections felt repetitive. | 7 |
goodreads_comments_scraper_reviews.csvColumn
current_page
Page number parsed from the Goodreads URL, defaulting to 1.
Column
book_title
Book title from the page heading or document title fallback.
Column
author
One or more author names joined into a single cell.
Column
username
Reviewer display name from the review card.
Column
rating
Goodreads rating label such as really liked it or it was amazing.
Column
comment_time
Visible review date when present.
Column
comment_content
Expanded review text cleaned into one cell.
Column
likes
Visible like count parsed as a number.
Headers included - one row per visible Goodreads review card
Related workflows
Compare Goodreads review collection options
| Option | Good fit | Trade-off |
|---|---|---|
| UScraper Goodreads comments template | No-code users who need Goodreads reviews CSV exports from a local desktop app | Best for modest, reviewable batches with explicit URL scope |
| Custom Python scraper | Developers who need deeper control over parsing, retries, or storage | Requires maintenance when Goodreads markup, rate behavior, or access rules change |
| Hosted scraping actors | Teams that want managed infrastructure | Review URLs and output pass through a third party and may bill by request or row |
Use the full UScraper template library when you need enrichment after the review export, and install the desktop app from UScraper download before importing the JSON workflow.
Frequently asked questions
Goodreads review pages may be publicly visible, but automated collection can still be limited by Goodreads terms, robots guidance, copyright, privacy rules, and local law. Keep batches modest, do not bypass access controls, and get legal review before republishing, reselling, or training models on exported comments.
Before you run
Practical limits and maintenance notes
Keep these constraints visible
Rate limits
Goodreads may slow, block, or challenge long sessions
Keep batches modest, avoid parallel runs against the same book, and increase waits if pages load slowly or review cards appear late.
Layout changes
Selectors can drift when Goodreads changes review cards
Empty cells usually mean the page layout changed, the review text is hidden, or a login wall replaced the expected content. Refresh the row selector and column fallbacks before scaling.
Compliance
Reader comments can include personal data and copyrighted text
Use the export for approved research workflows, retain only what you need, and confirm rights before publishing quotes or sharing datasets.
Get Started
Download and use this template instantly
$50Free
What's Included
- Template JSON file ready to import
- Pre-configured scraping nodes
- Works with UScraper desktop app
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