Goodreads Actor

Goodreads Scraper

Collect public Goodreads book metadata, author information, ratings, and review signals for publishing research.

Books / Media

What it does

Collect public Goodreads book metadata, author information, ratings, and review signals for publishing research.

Best for

  • Publishing research
  • Book catalog analysis
  • Recommendation datasets

Fields

  • Book title
  • Author
  • Book URL
  • Rating when public
  • Review count when public
  • Description
  • Public metadata

Inputs

  • Book URLs
  • Author URLs
  • Search terms
  • Max results
README

Goodreads Scraper technical notes

Goodreads Scraper can be used as part of a reviewed Apify workflow to collect public Goodreads data, clean the dataset, and deliver it to business tools. The exact setup depends on the target, available data, and required output structure.

Use Cases

  • Publishing research
  • Book catalog analysis
  • Recommendation datasets

Data Fields

  • Book title
  • Author
  • Book URL
  • Rating when public
  • Review count when public
  • Description
  • Public metadata

Inputs

  • Book URLs
  • Author URLs
  • Search terms
  • Max results

Workflow

  • Public Goodreads source
  • Actor run
  • Clean dataset
  • Delivery destination
  • Business report or automation

Delivery

  • CSV
  • Excel
  • Google Sheets
  • API
  • Database
  • Airtable
  • Notion
  • Slack
  • CRM

Limitations

  • Availability depends on the target website or platform structure.
  • Some data may not be publicly available.
  • Some requests may not be suitable.
  • The workflow is reviewed before setup.

Setup Notes

  • Use book URLs for known title enrichment, author URLs for catalog review, or search terms for discovery.
  • Set max results per author or query to keep the output reviewable.
  • Clarify whether ratings, review counts, descriptions, or author metadata are required.

Output Handling

  • Keep book title, author, book URL, rating, review count, description, and public metadata together.
  • Normalize author names and book URLs before matching to internal catalogs.
  • Ratings and review counts are public snapshots and should include the collection date.

Quality Checks

  • Deduplicate editions or titles when search results include multiple versions.
  • Check that the returned author or title matches the intended book.
  • Flag missing descriptions, ratings, or review counts when they are required fields.

FAQ

Can The Scrape Lab configure Goodreads Scraper for me?

Yes. We review the target, configure inputs, run tests, clean the output, and connect delivery where needed.

Can this run on a schedule?

In many cases, yes. Recurring schedules are reviewed based on the target, frequency, and reliability requirements.

Can the output go to Google Sheets or a CRM?

Yes. Delivery can be set up to Google Sheets, CSV, Airtable, databases, APIs, Slack, CRMs, or other tools depending on your workflow.

Is every request suitable?

No. We focus on public data and review each request before setup. Some targets or data requests may not be appropriate or technically reliable.

Need data collected or piped somewhere?

Send the source and fields. We'll review the scraper, Actor, or pipeline approach.

Request a Data Task