# Facebook Page Reviews Export to Excel (Cookieless) (`monumental_world/facebook-page-reviews`) Actor

Instantly turn Facebook page reviews into an Excel or CSV report. No coding required—perfect for e-commerce sentiment analysis and competitive benchmarking.

- **URL**: https://apify.com/monumental\_world/facebook-page-reviews.md
- **Developed by:** [Raised Pro](https://apify.com/monumental_world) (community)
- **Categories:** Automation, Social media, E-commerce
- **Stats:** 3 total users, 0 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.50 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

"# Facebook Page Reviews Export to Excel (Cookieless)

### Introduction

Need to download Facebook page reviews to Excel? This tool helps you extract customer feedback from Facebook pages and export it directly to a spreadsheet—no technical skills required. Designed specifically for e-commerce managers, agencies, and business owners who need to analyze customer sentiment, track product feedback, and compare performance across multiple platforms.

Whether you're monitoring your own brand reputation or researching competitors, this tool makes it simple to gather all your review data in one organized spreadsheet.

### Step-by-Step Guide

**Step 1:** Enter the Facebook Page ID you want to extract reviews from. You can find this in your Facebook page settings or URL.

**Step 2:** Click ""Start"" to begin extracting the reviews. No Facebook login required—the tool works completely cookieless!

**Step 3:** Download your data as Excel, CSV, or XML format. Open it in Microsoft Excel, Google Sheets, or any spreadsheet program you prefer.

That's it! Your Facebook page reviews are now ready to analyze, share with your team, or add to your reports.

### What columns will I get?

Your download will include the following columns:

- **Page URL**: The link to the review page
- **Review Title**: The headline or summary of the review
- **Review Text**: The full content of the customer's feedback
- **Reviewer Name**: The name of the person who left the review
- **Reviewer Location**: Where the reviewer is located
- **Rating Score**: The star rating given (e.g., 4.5 out of 5)
- **Review Date**: When the review was posted
- **Helpful Votes**: Number of people who found the review helpful
- **Total Votes**: Total number of votes the review received
- **Is Verified Purchase**: Whether the reviewer is a verified customer
- **Response Time (Days)**: How long it took to respond to the review
- **Platform Source**: Which platform the review came from

### How to use this data

Here are three simple ways to put your exported review data to work:

**1. Analyze Customer Sentiment**: Sort reviews by rating score and read through feedback to identify common themes. Are customers consistently praising certain features or complaining about specific issues? Use this insight to improve your products or services.

**2. Identify Product Improvement Opportunities**: Filter reviews with lower ratings and look for patterns in the feedback. Export reviews mentioning specific products to share with your product development team and prioritize improvements based on real customer input.

**3. Benchmark Against Competitors**: Export reviews from competitor Facebook pages and compare their rating scores, response times, and customer feedback themes against your own. Create comparison reports in Excel to identify where you're excelling and where there's room to improve.

### Input Settings

**Page ID**: This is the unique identifier for the Facebook page you want to extract reviews from.

To find your Page ID, look at your Facebook page URL or check your page settings. It's a string of numbers like `32467656765678`. Simply paste this number into the tool, and it will fetch all available reviews from that page.

You don't need to worry about authentication or logging in—just provide the Page ID and let the tool do the rest!

### Frequently Asked Questions

**Q: Do I need a Facebook account to use this tool?**\
A: No! This tool works completely cookieless, meaning you don't need to log in or connect your Facebook account. Just enter the Page ID and start extracting.

**Q: Can I open this in Google Sheets?**\
A: Yes, absolutely! Just download the CSV format and upload it directly to Google Sheets. You can also open Excel files in Google Sheets by uploading them to your Google Drive.

**Q: How many reviews can I export at once?**\
A: You can export as many reviews as are available on the Facebook page. The tool will gather all accessible review data for you.

**Q: Is this data updated in real-time?**\
A: The tool extracts the most current data available at the time you run it. For the latest reviews, simply run a new export whenever you need updated information.

**Q: Can I schedule automatic exports?**\
A: The tool is designed for on-demand exports. Simply run it whenever you need fresh data for your reports or analysis.

***

*Keywords: page reviews scraper, reviews data extraction, export reviews to csv, web scraper for reviews, product reviews api, online review scraping, reviews scraping tool, ecommerce reviews extractor*"

# Actor input Schema

## `pageId` (type: `string`):

Page ID of the Facebook page to fetch reviews from

## `maxPages` (type: `integer`):

Maximum number of pages to fetch (pagination handled automatically)

## Actor input object example

```json
{
  "pageId": "100063543614476",
  "maxPages": 1
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("monumental_world/facebook-page-reviews").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("monumental_world/facebook-page-reviews").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{}' |
apify call monumental_world/facebook-page-reviews --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=monumental_world/facebook-page-reviews",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/RviNpDxNzQonMG9w0/builds/goJHjdVLsJVwLJCGt/openapi.json