# Jcpenney Reviews Parser Script (`hello.datawizards/jcpenney-reviews-parser-script`) Actor

“Jcpenney Reviews Parser Script quickly extracts detailed customer reviews from JCPenney product pages, delivering clean JSON with ratings, text, demographics, and timestamps. Ideal for sentiment analysis, product research, and e-commerce insights with proxy support.”

- **URL**: https://apify.com/hello.datawizards/jcpenney-reviews-parser-script.md
- **Developed by:** [datawizards](https://apify.com/hello.datawizards) (community)
- **Categories:** Automation, E-commerce, Lead generation
- **Features:** Limited permissions
- **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $8.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

***

## ⭐ 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](https://linkedin.com/in/data-wizards-aa8080342)**.

***

### 📌 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**.

***

### 🧠 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

***

### 🛠️ Input Schema

Simply provide proxy configuration:

```json
{
  "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

***

### 📤 Output Example

```json
[
  {
    "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
  }
]
```

***

### 🚀 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

***

### ✅ 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

***

### 🧰 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.

***

### 🤝 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>

***

### 🐞 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`

***

### 🌟 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.*

***

# Actor input Schema

## `itemLimit` (type: `integer`):

Maximum number of items to scrape. Use 0 for no limit.

## `proxyConfiguration` (type: `object`):

Specifies proxy servers that will be used by the scraper in order to hide its origin.

## Actor input object example

```json
{
  "itemLimit": 5,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "itemLimit": 5,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("hello.datawizards/jcpenney-reviews-parser-script").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "itemLimit": 5,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("hello.datawizards/jcpenney-reviews-parser-script").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "itemLimit": 5,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}' |
apify call hello.datawizards/jcpenney-reviews-parser-script --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,hello.datawizards/jcpenney-reviews-parser-script"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/K2lOha5Liq6t0cUVO/builds/SwsVlKo24uaKbiKpr/openapi.json