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⭐ Jcpenney Reviews Parser Script · Apify Actor

Extract clean, structured customer reviews from JCPenney product pages with precision. Perfect for sentiment analysis, brand monitoring, product research, and e-commerce intelligence. Built and maintained by DataWizards.

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📌 What Is Jcpenney Reviews Parser Script?

The Jcpenney Reviews Parser Script is a powerful Apify Actor designed to automatically scrape detailed customer reviews from any JCPenney product URL. It collects essential data points such as rating, author, demographic details, review text, timestamps, and more — all delivered in clean JSON.

This actor is ideal for analysts, marketers, e-commerce brands, and researchers who want accurate review insights without manual browsing.

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🧠 Key Features

✔️ Extracts full review details: rating, title, text, author, age, gender, location ✔️ Captures exact submission timestamps ✔️ Supports any public product URL ✔️ Built-in RESIDENTIAL proxy support to avoid blocking ✔️ Clean, ready-to-use JSON output ✔️ Fast, reliable, and scalable for large datasets

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🛠️ Input Schema

Simply provide proxy configuration:

{
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

🔐 Proxy Configuration Notes

• useApifyProxy must be true
• Use RESIDENTIAL IPs for best success rate
• Automatically rotates IPs to reduce blocks

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📤 Output Example

[
  {
    "URL": "https://www.jcpenney.com/p/st-johns-bay-womens-crew-neck-long-sleeve-t-shirt/ppr5008501460",
    "Title": "Great styles",
    "Rating": 5,
    "Review_Text": "I love this shirt. The fit is so nice and at a great price was great as well. Everyone is so nice and helpful. I love this store.",
    "Submission_Time": "2025-12-06T02:30:01.000+00:00",
    "Author": "Your girl",
    "User Location": "California",
    "Age": "30to39",
    "Gender": "female",
    "Review Helpful": null
  }
]

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🚀 Use Cases

🛍️ Product Research – Understand real customer sentiment 📊 Market Insights – Analyze demographic trends 🧠 Sentiment Analysis – Feed into NLP models 🏪 Brand Monitoring – Track customer experience over time 📝 Competitor Analysis – Benchmark similar products 📈 Data Aggregation – Build dashboards or datasets

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✅ Best Practices

• Use RESIDENTIAL proxies for high-volume scraping
• Avoid sending too many requests too quickly to prevent blocks
• Always double-check URLs to ensure they point to valid product pages
• Use pagination logic if running large reviews extraction tasks
• Store results in datasets for faster analysis

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🧰 Additional Capabilities

• Custom field extraction
• Bulk URL support
• Custom output mapping
• Review sentiment tagging (on request)
• API-ready formatted results

If you need customized outputs, additional fields, or workflows — DataWizards can do it for you.

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🤝 Support

Need help, custom parsing rules, or a tailored automation workflow? DataWizards is always ready for you!

📩 Email: hello.datawizard@gmail.com ✉️ Subject: Jcpenney Reviews Parser Script – Support Request 🔗 Connect: https://linkedin.com/in/data-wizards-aa8080342

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🐞 Bug Reports & Feature Requests

Found an issue? Want new features? Send us a message at hello.datawizard@gmail.com ✉️ Subject: Bug Report – Jcpenney Reviews Parser Script

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🌟 Final Note

Whether you need a custom scraper, advanced data cleaning, or fully automated pipeline, DataWizards delivers fast, reliable, and scalable data extraction.

🚀 Start extracting JCPenney review insights like a pro — effortlessly.

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