Jshealth Reviews Spider

Introduction

The Jshealth Reviews Spider is a powerful Apify Actor designed to extract customer reviews from JSHealth Vitamins product pages efficiently and reliably. It scrapes detailed review data, including ratings, content, user information, and custom fields, enabling businesses and researchers to gain valuable insights into product performance and customer sentiment. This tool is ideal for e-commerce analysis, market research, and competitive intelligence, delivering high-quality, structured data with minimal setup.

Features

• Comprehensive Review Extraction: Captures full review details such as scores, titles, content, timestamps, and user profiles from JSHealth product pages.
• Sentiment Analysis Integration: Includes pre-computed sentiment scores for each review to gauge overall customer satisfaction.
• Custom Fields Support: Extracts additional metadata like age groups and other user-provided information for deeper analysis.
• High Reliability: Built with robust error handling to ensure consistent data collection even from dynamic web pages.
• Scalable Performance: Handles multiple product URLs in a single run, with efficient scraping to minimize resource usage.
• Structured Output: Delivers data in clean JSON format, ready for export to CSV, Excel, or databases.
• Easy Configuration: Simple input setup with URL lists, making it accessible for users of all technical levels.

Input Parameters

Parameter	Type	Required	Description	Example
ProductUrls	array	Yes	An array of product URLs from JSHealth Vitamins to scrape reviews from. Must include at least one valid URL.	["https://jshealthvitamins.com/products/hair-energy-formula"]

Example Usage

To run the Jshealth Reviews Spider, provide the input in JSON format:

{
  "ProductUrls": [
    "https://jshealthvitamins.com/products/hair-energy-formula"
  ]
}

Example output in JSON format:

[
  {
    "product_id": "6921002877000",
    "review_id": 731294803,
    "score": 5,
    "title": "seems to work!",
    "content": "noticeable improvement with hair growth!",
    "created_at": "2025-07-05T09:43:46",
    "verified_buyer": true,
    "sentiment": 0.94847906,
    "user_display_name": "Monique C.",
    "images": "https://cdn-yotpo-images-production.yotpo.com/Review/731294803/728247698/original.jpg?1753262287",
    "custom_fields": {
      "33318": {
        "title": "Age",
        "formId": 24266,
        "fieldType": "SingleChoice",
        "value": "35-44"
      }
    },
    "actor_id": "qd6w6NWAc54aZyAA4",
    "run_id": "qpLWBvcgcCOrIft43"
  }
]

Use Cases

• Market Research and Analysis: Analyze customer feedback to identify trends in product satisfaction and areas for improvement.
• Competitive Intelligence: Compare review data across similar products to benchmark performance and pricing strategies.
• Price Monitoring: Track reviews alongside pricing data to understand the impact of reviews on sales.
• Content Aggregation: Collect and aggregate reviews for content creation, such as blog posts or social media campaigns.
• Academic Research: Gather data for studies on consumer behavior, health product efficacy, and sentiment analysis.
• Business Automation: Integrate review data into dashboards for automated reporting and decision-making in e-commerce operations.

Installation and Usage

1. Search for "Jshealth Reviews Spider" 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 output is a JSON array of review objects. Each object includes key fields such as product_id (unique product identifier), review_id (unique review ID), score (rating out of 5), title and content (review text), created_at (timestamp), verified_buyer (boolean for purchase verification), sentiment (numerical sentiment score), user_display_name (reviewer name), images (URLs to review images), custom_fields (additional user data like age), and metadata like actor_id and run_id. This structure ensures easy parsing and integration into analysis tools.

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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