Wayfair Reviews Scraper
by scraped
Extract Wayfair product reviews, ratings, and customer data automatically. Get structured JSON/CSV for market research and analysis without manual work.
Opens on Apify.com
About Wayfair Reviews Scraper
Need to pull customer reviews from Wayfair for market research, sentiment analysis, or competitor tracking? This scraper is built to handle that. It's a straightforward actor I've used to extract product ratings, review text, dates, and reviewer information directly from Wayfair product pages. You just feed it the product URLs you're interested in, and it returns structured data, typically as JSON or CSV, which you can then plug into your own analysis tools or databases. It saves you the massive manual effort of copying and pasting, and it's configured to handle Wayfair's page structure specifically, which means you spend less time troubleshooting and more time working with the data. It's perfect for e-commerce analysts, brand managers, or developers who need reliable, structured review data from one of the largest home goods retailers out there. Just set your input list and run it—you'll get a clean dataset of what customers are actually saying.
What does this actor do?
Wayfair Reviews Scraper is a web scraping and automation tool available on the Apify platform. It's designed to help you extract data and automate tasks efficiently in the cloud.
Key Features
- Cloud-based execution - no local setup required
- Scalable infrastructure for large-scale operations
- API access for integration with your applications
- Built-in proxy rotation and anti-blocking measures
- Scheduled runs and webhooks for automation
How to Use
- Click "Try This Actor" to open it on Apify
- Create a free Apify account if you don't have one
- Configure the input parameters as needed
- Run the actor and download your results
Documentation
Wayfair Reviews Scraper
This Apify actor scrapes customer reviews from Wayfair.com. It extracts structured data from product review pages, including text, ratings, reviewer details, and images.
Key Features
- Extracts comprehensive review data: Captures review text, star ratings, reviewer names, locations, and verification status.
- Handles media: Downloads customer-uploaded photos associated with reviews.
- Pagination support: Automatically navigates through multiple pages of reviews for a given product.
- Structured output: Returns clean, consistent JSON data suitable for analysis or storage.
How to Use
Run the actor on the Apify platform. You need to provide at least one product URL from Wayfair as input.
Basic Input Configuration:
* Start URLs: A list of Wayfair product page URLs (e.g., https://www.wayfair.com/furniture/pdp/product-name.html).
* Max Reviews: (Optional) Limit the total number of reviews to scrape per product.
The actor will process each URL, navigate to its reviews section, and collect all available data.
Input & Output
Input: The primary input is one or more Wayfair product page URLs provided via the actor's input configuration.
Output: The actor outputs a dataset of items, where each item represents a single review. The data is structured as JSON.
Example output item:
{
"reviewId": 153402617,
"reviewerName": "Casey and Tommy",
"hasVerifiedBuyerStatus": true,
"ratingStars": 6,
"date": "07/27/2025",
"productComments": "I love that white glove delivery was available...",
"reviewerLocation": "PA",
"customerPhotos": [
{
"thumbnail": "https://assets.wfcdn.com/.../thumbnail.jpg",
"src": "https://assets.wfcdn.com/.../fullsize.jpg"
}
]
}
Support
For issues or questions, contact: scraperhelp@gmail.com.
Categories
Common Use Cases
Market Research
Gather competitive intelligence and market data
Lead Generation
Extract contact information for sales outreach
Price Monitoring
Track competitor pricing and product changes
Content Aggregation
Collect and organize content from multiple sources
Ready to Get Started?
Try Wayfair Reviews Scraper now on Apify. Free tier available with no credit card required.
Start Free TrialActor Information
- Developer
- scraped
- Pricing
- Paid
- Total Runs
- 160
- Active Users
- 18
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