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Outdoorvoices Reviews Scraper

Introduction

The Outdoorvoices Reviews Scraper is a powerful Apify Actor designed to extract customer reviews from Outdoor Voices product pages efficiently and reliably. It leverages web scraping technology to gather detailed review data, including ratings, comments, and reviewer information, enabling businesses and researchers to gain valuable insights into product performance and customer sentiment. Whether you're conducting market research, monitoring brand reputation, or analyzing trends, this Actor provides a streamlined solution for collecting high-quality review data at scale.

Features

• Comprehensive Data Extraction: Captures full review details such as ratings, titles, bodies, reviewer names, verification status, and timestamps for thorough analysis.
• High Reliability: Built on Apify's robust CheerioCrawler, ensuring consistent performance with error handling and retries for stable data collection.
• Customizable Crawling: Supports multiple start URLs and configurable request limits to tailor scrapes to your specific needs.
• Structured Output: Delivers data in clean JSON format, ready for integration into databases, analytics tools, or reporting systems.
• Fast and Scalable: Optimized for speed, handling large volumes of reviews without compromising data integrity.
• No Coding Required: User-friendly interface in the Apify Store, making it accessible for non-technical users.
• Ethical Scraping: Respects website terms by adhering to rate limits and best practices to avoid overloading servers.

Input Parameters

Example Usage

Input JSON

{
"startUrls":[
{
"url":"https://www.outdoorvoices.com/products/w-techsweat-core-7-8-legging-night?_pos=14&_sid=60871458c&_ss=r"
}
],
"maxItems":100
}

Output JSON

[
{
"reviewId":"29cbdb8d-86ea-45e6-bb32-b49db56cae88",
"productId":"shopify-6822414254158",
"productName":"The Exercise Dress",
"productHandle":"w-the-exercise-dress-black",
"productUrl":"//www.outdoorvoices.com/products/w-the-exercise-dress-black",
"productImageUrl":"https://cdn.shopify.com/s/files/1/0190/1390/files/The_Exercise_Dress_Black_000_x280.jpg?v=1757814997",
"rating":1,
"title":"1 Star",
"reviewBody":"I ordered an XXL and it was probably a size 12. Also, the fabric was of a lower quality.",
"languageCode":"en",
"reviewerName":"Kerin",
"reviewerVerified":false,
"reviewerAttributes":{},
"dateCreated":"2026-03-13T19:09:34.000Z",
"dateUpdated":"2026-03-13T19:09:34.000Z",
"isRecommended":false,
"isIncentivized":false,
"helpfulCount":1,
"unhelpfulCount":0,
"productAttributes":{},
"photos":[],
"status":"approved"
}
]

Use Cases

• Market Research: Analyze customer feedback to identify trends in product quality and preferences for Outdoor Voices items.
• Competitive Intelligence: Compare review data across similar products to benchmark performance against competitors.
• Brand Monitoring: Track sentiment and ratings to maintain or improve brand reputation through targeted responses.
• E-commerce Optimization: Use insights from reviews to inform pricing, inventory, and marketing strategies.
• Academic Research: Collect data for studies on consumer behavior in the activewear industry.
• Content Aggregation: Build databases of user-generated content for blogs, newsletters, or social media campaigns.

Installation and Usage

1. Search for "Outdoorvoices Reviews Scraper" in the Apify Store
2. Click "Try for free" or "Run"
3. Configure input parameters
4. Click "Start" to begin extraction
5. Monitor progress in the log
6. Export results in your preferred format (JSON, CSV, Excel)

Output Format

The Actor outputs data as a JSON array of review objects. Each object includes fields like reviewId (unique identifier), productName and productUrl (product details), rating (1-5 scale), title and reviewBody (content), reviewerName and reviewerVerified (reviewer info), dateCreated (timestamp), and additional metadata such as helpfulCount and status. This structured format ensures easy parsing and integration, with empty arrays for fields like photos if no data is present.

Support

For custom/simplified outputs or bug reports, please contact:

• Email: support@getdataforme.com
• Subject line: "custom support"
• Contact form: https://getdataforme.com/contact/

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