Goodreads is where millions of readers track what they’ve read, review what they love, and discover what to read next. It’s one of the most active hubs for real-time book opinions, rankings, and user-generated reading data — across every genre and market.
Our Goodreads scraper helps you unlock this insight. Whether you’re tracking trends, analysing reviews, or profiling readers, we collect the data you actually need.
We don’t offer scraping tools you have to manage. Our Goodreads data scraper works as a service — you tell us what data matters, and we deliver it ready to use. No parsing, no manual effort, just reliable information tailored to your goals.
We extract everything directly from Goodreads listings and user activity — book titles, authors, reviews, ratings, genres, user shelves, and more. You receive clean, structured data in CSV, Excel, JSON, or any other format you prefer — already filtered and formatted for your use case.
The Goodreads scraper focuses on extracting detailed, reader-generated content and metadata tied to books and authors. We collect:
This structured dataset offers deep insight into how books are perceived and positioned in the market — directly by the readers themselves.
When you scrape Goodreads, you get access to much more than book listings and reviews. We can extract:
These additional layers are key for trend spotting, audience segmentation, and building content or recommendation engines around actual reader behaviour.
Goodreads.com is the world’s largest platform for readers and book recommendations, with over 150 million users and a library of more than 2.5 billion books rated or reviewed. Launched in 2007 and acquired by Amazon in 2013, it serves as a social cataloging site where users track their reading, leave reviews, and discover new books based on community activity.
While the platform is available globally, it’s especially popular in the US, UK, Canada, India, and Australia. The interface is primarily in English, but Goodreads supports other languages for broader accessibility. Unlike bookstores or marketplaces, Goodreads isn’t for selling — it’s for shaping opinion. It’s a trusted source of honest reviews, reading trends, and genre-based communities, all created by readers themselves.
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Developers
Customers
Pages extracted
Hours saved for our clients
Customized scraping setup for Goodreads — faster and cheaper than building a solution from scratch.
Data limits (rows): up to 10%
Iterations: up to 3
Custom requirements: Yes
Data lifetime: up-to-date
Data quality checks: Yes
Delivery deadline: 1-2 working days
Output formats: CSV, JSON, XLSX
Delivery options: e-mail
A Goodreads web scraper helps you extract valuable public data that reflects how real readers interact with books — what they rate highly, how they describe them, and which authors build loyal audiences. This isn’t just metadata — it’s opinion at scale.
Use it for competitive analysis, content recommendation systems, audience profiling, or book marketing research. Whether you’re a publisher, data analyst, or app developer, scraping Goodreads gives you access to community-driven insights that simply aren’t available anywhere else.
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Amazon provides valuable information gathered in one place: products, reviews, ratings, exclusive offers, news, etc. So scraping data from Amazon will help solve the problems of the time-consuming process of extracting data from e-commerce.
The use of sentiment analysis tools in business benefits not only companies but also their customers by allowing them to improve products and services, identify the strengths and weaknesses of competitors' products, and create targeted advertising.
ScrapeIt is a data extraction company that helps you access valuable information from platforms like Goodreads — without the complexity of building a custom tool. We act as your business scraper, delivering exactly the data you need, tailored to your niche and goals.
Whether you're gathering insights for marketing, trend analysis, or product planning, we deliver structured data that's ready to export in a clean, organised file. No code, no setup — just usable data from day one. Our Goodreads scraper turns public book data into actionable information for your team.
Yes. By analysing reader reviews, preferences, and engagement patterns, you can identify niche audiences and influencers — which helps generate qualified leads for marketing campaigns, pre-launch buzz, or direct outreach.
A Goodreads web scraper is designed specifically for the structure and logic of the Goodreads platform. It knows how to extract reviews, user shelves, ratings, and author content efficiently, without requiring manual setup or platform-specific coding.
We focus only on publicly available information, and our data scraping practices respect terms of use and ethical standards.
No. Goodreads does not display phone numbers or addresses of users or authors. However, you may find external links to social media or personal websites where additional contact information is available publicly.
Services in publishing, digital marketing, book discovery platforms, and literary analytics all benefit from Goodreads data. Whether you’re building recommendation systems or researching reader sentiment, the data is highly actionable.
1. Make a request
You tell us which website(s) to scrape, what data to capture, how often to repeat etc.
2. Analysis
An expert analyzes the specs and proposes a lowest cost solution that fits your budget.
3. Work in progress
We configure, deploy and maintain jobs in our cloud to extract data with highest quality. Then we sample the data and send it to you for review.
4. You check the sample
If you are satisfied with the quality of the dataset sample, we finish the data collection and send you the final result.
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