Facebook Reviews Scraper

Facebook Reviews Scraper

Facebook Reviews Scraper is a fast, scalable Facebook reviews scraping tool that extracts recommendations, ratings signals, review text, timestamps, reviewer details, and engagement metrics from public Facebook Pages. It solves the pain of manually collecting and monitoring feedback by automating end-to-end review extraction — a reliable Facebook review extractor and Facebook reviews API alternative for marketers, developers, data analysts, and researchers. With bulk input support, smart pagination, and proxy fallback, you can scrape Facebook page reviews at scale, export Facebook reviews to CSV/JSON/Excel, and integrate insights into BI, sentiment analysis, and local SEO workflows.

What data / output can you get?

Data field	Description	Example value
facebookUrl	The Facebook page URL where the review was posted	https://www.facebook.com/mrbeast
id	Unique review identifier (Base64 encoded)	UzpfSTYxNTg0MzE3MjA0OTY4OjEyMjEwOTkzMzE4OTE0MzkwNjoxMjIxMDk5MzMxODkxNDM5MDY=
user	Reviewer information object with id, name, profileUrl, profilePic	{"id":"pfbid022...","name":"Helen Head","profileUrl":"https://www.facebook.com/people/Helen-Head/...","profilePic":null}
date	Review creation date in ISO 8601 (UTC)	2025-12-23T18:12:27.000Z
url	Direct link to the review post	https://www.facebook.com/permalink.php?story_fbid=pfbid0...
isRecommended	Whether the reviewer recommended the page	true
text	Full text content of the review	"I'm at the homeless shelter in Alexandria..."
likesCount	Number of likes on the review	1
commentsCount	Number of comments on the review	0
facebookId	Facebook feedback ID	ZmVlZGJhY2s6MTIyMTA5OTMzMTg5MTQzOTA2
postFacebookId	Facebook post ID	122109933189143906
pageName	Name of the Facebook page being reviewed	MrBeast

Notes:

• Outputs are available in the Apify Dataset (one record per review) and as an aggregated JSON in the Key-Value Store under key OUTPUT (grouped by page name).
• You can export data to JSON, CSV, or Excel from the Dataset or Key-Value Store.
• Some fields like user.profilePic or pageName may be null if not present in the source page.

Key features

• 🚀 High-throughput scraping engine
  Asynchronous fetching with concurrent processing (3 pages in parallel) to automate Facebook reviews scraping reliably at scale.

• 🔄 Smart GraphQL pagination
  Cursor-based pagination through Facebook’s feed to collect complete review streams with robust retry logic.

• 🧹 Automatic deduplication
  Filters duplicate reviews by unique IDs to keep your dataset clean when you download Facebook reviews or rerun jobs.

• 🧭 Flexible sorting by intent
  Sort by newest, oldest, or most_relevant (likes + comments) to surface impactful reviews for brand monitoring and analysis.

• 🛡️ Intelligent proxy fallback
  Automatic stages: no proxy → datacenter → residential (with retries). Once residential is used, it sticks for remaining requests. Great for a stable Facebook recommendations scraper.

• 📦 Bulk input support
  Feed multiple page URLs or usernames in a single run — ideal for agencies and teams that need a Facebook business reviews scraper across many locations.

• 💾 Clean, structured output
  Consistent JSON with reviewer, engagement, and technical IDs, ready to export Facebook reviews to CSV, Excel, or integrate via API.

• 👩‍💻 Developer-friendly
  Runs on Apify infrastructure with Dataset and Key-Value Store outputs for easy API consumption. A solid “scrape Facebook recommendations without API” alternative for Python workflows and automation tools.

• 🔒 No login required
  Designed for public Facebook Pages — no cookies, sessions, or extensions required, unlike a Facebook reviews scraper Chrome extension.

• 🧱 Production-ready reliability
  Built-in error handling, cursor-stall detection, and detailed logging to support long-running jobs and enterprise workflows.

How to use Facebook Reviews Scraper - step by step

1. Create or log in to your Apify account
   Visit https://console.apify.com and sign in (free tier available for testing).

2. Open the actor
   Find “Facebook Reviews Scraper” in your Actors list or via the Apify Store.

3. Add your input data

   • In the Input tab, paste a list of Facebook page URLs or usernames into the inputs array.
   • Example accepted formats:
     • Full URL: https://www.facebook.com/mrbeast
     • Username: mrbeast

4. Configure limits and proxies

   • Set maxItems to control how many reviews to scrape per page (default: 100).
   • Optionally adjust proxyConfiguration (defaults to {"useApifyProxy": false}). The scraper will automatically fallback if blocked.

5. Start the run
   Click Start. The actor resolves dynamic IDs, paginates through reviews, and pushes each review to the Dataset as it’s found.

6. Monitor progress
   Use the Log tab to see pages being processed, pagination batches, proxy stage transitions, and retry handling.

7. Access your results

   • Dataset tab: Browse individual review records.
   • Key-Value Store: Inspect the aggregated OUTPUT key (grouped by pageName).

8. Export for analytics
   Download your data as JSON, CSV, or Excel from the Dataset or Key-Value Store, then feed it into your BI tools or sentiment analysis pipeline.

Pro Tip: Need a specific order for analysis? You can pass sortOrder with values newest, oldest, or most_relevant for precise ranking in downstream reports.

Use cases

Use case	Description
Marketing + Reputation Management	Monitor and export Facebook reviews to CSV for weekly brand reports, spot trends, and prioritize responses.
Local SEO for Multi-location Brands	Aggregate Facebook recommendations across locations to measure sentiment and optimize local listings.
Competitive Intelligence	Track competitor pages to benchmark engagement, review frequency, and customer perception.
Customer Support Triage	Sort by most_relevant to surface high-impact reviews and route them to support teams quickly.
Product & UX Research	Analyze review text across multiple pages to inform roadmap decisions and CX improvements.
Academic & Social Research	Collect structured public reviews at scale for sentiment studies and social media analysis.
Data Engineering Pipelines	Automate Facebook page reviews crawler runs and pipe output JSON to warehouses via Apify API.

Why choose Facebook Reviews Scraper?

This Facebook page reviews crawler is built for precision, automation, and reliability — not brittle browser extensions.

• ✅ Accurate, structured results with reviewer, engagement, and timestamp fields
• 🌍 Works on public Pages without login or cookies
• 📈 Scales to multiple pages concurrently with clean deduplication
• 👩‍💻 Developer access via Apify’s Datasets and Key-Value Store (API-ready)
• 🔒 Ethical-by-design: public data only, no private or authenticated content
• 💰 Cost-effective alternative to a Facebook reviews data extractor software or one-off tools
• 🔌 Easy exports (JSON/CSV/Excel) and integration with automation platforms

In short: a robust Facebook reviews scraping tool that outperforms unstable add-ons and manual copy-paste — ideal for ongoing monitoring and analytics.

Is it legal / ethical to use Facebook Reviews Scraper?

Yes — when used responsibly. The actor collects data from publicly available Facebook Pages only and does not access private profiles or authenticated content. To stay compliant:

• Scrape public data only and respect Facebook’s Terms of Service.
• Ensure your use complies with applicable regulations (e.g., GDPR, CCPA).
• Use data responsibly for analysis or research; avoid spam or misuse.
• Consult your legal team for edge cases or jurisdiction-specific requirements.

Input parameters & output format

Example input (via Apify Console or API):

{
  "inputs": [
    "https://www.facebook.com/mrbeast",
    "tesla"
  ],
  "maxItems": 100,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Parameters

• inputs (array, required):
  List of Facebook page URLs (e.g., https://www.facebook.com/mrbeast) or usernames (e.g., mrbeast). Keywords require resolvable page context.

• maxItems (integer, optional, default: 100, min: 1, max: 10000):
  Maximum number of reviews to scrape per page. Pagination stops once this limit is reached.

• proxyConfiguration (object, optional, default: {"useApifyProxy": false}):
  Choose which proxies to use. By default, no proxy is used. On rejection or blocking, the scraper can automatically fallback to datacenter, then residential proxies with retries.

Example dataset record (one per review):

{
  "facebookUrl": "https://www.facebook.com/mrbeast",
  "id": "UzpfSTYxNTg0MzE3MjA0OTY4OjEyMjEwOTkzMzE4OTE0MzkwNjoxMjIxMDk5MzMxODkxNDM5MDY=",
  "user": {
    "id": "pfbid022DhB36PVT9anEH47J7WQu78JYMNhaEGeHHKAhyPXJVNjusrH3TCierbYBcaA7NTBl",
    "name": "Helen Head",
    "profileUrl": "https://www.facebook.com/people/Helen-Head/pfbid022DhB36PVT9anEH47J7WQu78JYMNhaEGeHHKAhyPXJVNjusrH3TCierbYBcaA7NTBl/",
    "profilePic": null
  },
  "date": "2025-12-23T18:12:27.000Z",
  "url": "https://www.facebook.com/permalink.php?story_fbid=pfbid036zKdeTsZRHzcZspm8CNjzv3jSuSQFmbjNc6h4FPwLvsBmjYU3ibcHqX4HSukzQakl&id=61584317204968",
  "isRecommended": true,
  "text": "I'm at the homeless shelter in Alexandria Virginia Prince William county building and there's a lot of us that are homeless that should have a Christmas maybe someone should help us all out show people love...",
  "likesCount": 1,
  "commentsCount": 0,
  "facebookId": "ZmVlZGJhY2s6MTIyMTA5OTMzMTg5MTQzOTA2",
  "postFacebookId": "122109933189143906",
  "pageName": "MrBeast"
}

Example aggregated output (Key-Value Store, key: OUTPUT):

{
  "MrBeast": [
    {
      "facebookUrl": "https://www.facebook.com/mrbeast",
      "id": "UzpfSTYxNTg0MzE3MjA0OTY4OjEyMjEwOTkzMzE4OTE0MzkwNjoxMjIxMDk5MzMxODkxNDM5MDY=",
      "user": {
        "id": "pfbid022DhB36PVT9anEH47J7WQu78JYMNhaEGeHHKAhyPXJVNjusrH3TCierbYBcaA7NTBl",
        "name": "Helen Head",
        "profileUrl": "https://www.facebook.com/people/Helen-Head/pfbid022DhB36PVT9anEH47J7WQu78JYMNhaEGeHHKAhyPXJVNjusrH3TCierbYBcaA7NTBl/",
        "profilePic": null
      },
      "date": "2025-12-23T18:12:27.000Z",
      "url": "https://www.facebook.com/permalink.php?story_fbid=pfbid036zKdeTsZRHzcZspm8CNjzv3jSuSQFmbjNc6h4FPwLvsBmjYU3ibcHqX4HSukzQakl&id=61584317204968",
      "isRecommended": true,
      "text": "I'm at the homeless shelter in Alexandria...",
      "likesCount": 1,
      "commentsCount": 0,
      "facebookId": "ZmVlZGJhY2s6MTIyMTA5OTMzMTg5MTQzOTA2",
      "postFacebookId": "122109933189143906",
      "pageName": "MrBeast"
    }
  ],
  "Tesla": []
}

Notes:

• Fields that may be null or “Unknown”: pageName (if not detected), facebookUrl (rare), user.profilePic, text, date. Engagement fields default to 0 when not present.
• Reviews are pushed to the Dataset immediately during scraping for near-real-time access.

FAQ

Do I need to log in to scrape Facebook reviews?

No. The actor targets publicly available Facebook Pages and does not require login, cookies, or a session. It’s designed as a stable Facebook reviews API alternative without browser automation.

How many reviews can I collect per page?

You control this via the maxItems parameter (default 100, up to 10,000). The scraper paginates through reviews until it reaches your limit or the feed ends.

Can I sort the results by relevance or date?

Yes. The scraper supports sorting by newest, oldest, or most_relevant (likes + comments). Provide sortOrder in your input when running via API to change ranking.

What formats can I export to?

You can export data from the Apify Dataset or Key-Value Store to JSON, CSV, or Excel, making it easy to download Facebook reviews for analysis or reporting.

Does it work on multiple pages at once?

Yes. It supports bulk processing of multiple page URLs or usernames. Internally, it processes up to 3 pages concurrently for efficiency.

What happens if Facebook blocks my requests?

The actor includes an intelligent proxy fallback: starts with no proxy (or your configured proxy), then tries datacenter, then residential proxies with retries. Once residential is used, it sticks for the remaining requests.

Can it scrape Facebook recommendations as well as reviews?

Yes. It collects recommendation signals and sets isRecommended accordingly, functioning as a Facebook recommendations scraper for public Pages.

Is this better than a Facebook reviews scraper Chrome extension?

For automation and reliability, yes. This server-side Facebook page reviews crawler avoids browser fragility, scales to bulk runs, and outputs structured JSON ready for APIs and analytics.

Closing CTA / Final thoughts

Facebook Reviews Scraper is built to automate accurate, large-scale extraction of public Facebook Page reviews and recommendations. With bulk inputs, smart pagination, and robust proxy fallback, it helps marketers, developers, analysts, and researchers turn unstructured feedback into usable insights. Export to CSV/JSON/Excel, feed dashboards or warehouses, or connect via the Apify API for end-to-end automation. Start extracting smarter review data and power your sentiment analysis, brand monitoring, and local SEO — at scale.