How do I connect Make to Scrapernode?

Use Make's webhook trigger to receive data from Scrapernode. Copy the webhook URL from Make and paste it into Scrapernode's webhook settings for the scraper. Each completed job sends results automatically.

What Facebook comments data fields are sent to Make?

All 22 output fields from the Facebook Comments scraper are included: url, post_id, post_url, comment_id, user_name, user_id, and more. The full payload is sent as structured JSON — no fields are filtered out.

Can I schedule recurring Facebook scrapes to Make?

Yes. Use Make's scheduling features to trigger Scrapernode scrapes on a recurring basis via the REST API. You can also set up Make to process results as they arrive via webhooks.

How much does it cost to scrape Facebook comments into Make?

Each comments record costs 1 credit. Credits start at $9 for 3,000 credits (Starter plan). The Make integration itself is included free — no additional charges for data delivery.

What happens if the Make delivery fails?

Your scraped data is always stored in Scrapernode regardless of the integration status. If delivery to Make fails, you can re-trigger the sync or download results manually as CSV or JSON from the job details page.

FacebookMake

How to Scrape Facebook Comments into Make

Extract comments data from Facebook and pipe into Make automatically

Step-by-step guide

Choose the Facebook Comments scraper

Navigate to the Facebook Comments scraper in Scrapernode. Select "Fresh Scrape" for real-time data or "Quick Lookup" for pre-collected records. Each record costs 1 credit.

Set up your Make connection

Create a new Make scenario with a Webhook trigger module. Copy the webhook URL into Scrapernode's webhook settings. Use Make's built-in JSON parser to map scraper fields to downstream modules like "Create Spreadsheet Row" or "Send Email".

Provide your Facebook input URLs

Paste the Facebook URLs you want to scrape — one per line, or upload a CSV. Scrapernode accepts direct profile links, search result URLs, and content pages.

Launch the scraping job

Click "Start Extraction" to begin. Scrapernode handles proxy rotation, rate limiting, and anti-bot detection automatically. Jobs typically complete in under 60 seconds per batch.

Receive data in Make

When the job completes, Scrapernode sends the full results to your Make workflow. Each record includes 22 fields like url, post_id, post_url, comment_id. Route the data to any downstream app — CRMs, databases, email tools, and more.

Cost per record

1 credit

Output fields

22 fields

Destination

Make

Sample Output

Preview the data you'll receive — 5 sample records

Record 1 of 5

Url

sample_url

Post Id

sample_post_id

Post Url

sample_post_url

Comment Id

sample_comment_id

User Name

James K.

User Id

sample_user_id

User Url

sample_user_url

Date Created

2025-12-15

Comment Text

Great analysis! Would love to see a deeper dive on the retention metrics.

Num Likes

Num Replies

Attached Files

sample_attached_files

Video Length

0:47

Source Type

sample_source_type

Subtype

sample_subtype

Type

sample_type

Commentator Profile

sample_commentator_profile

Comment Link

sample_comment_link

Yes

Parent Comment Id

sample_parent_comment_id

Commentator Profile Url

sample_commentator_profile_url

Attached Images

sample_attached_images

Data Dictionary

22 fields returned per record

The URL of the page or post containing the comments (100.00% fill rate)

Unique identifier for each post (100.00% fill rate)

URL of the specific post (100.00% fill rate)

Unique identifier for each comment (100.00% fill rate)

Name of the user who made the comment (100.00% fill rate)

Unique identifier for each user (100.00% fill rate)

URL of the user's profile (53.75% fill rate)

Date and time when the comment was created (100.00% fill rate)

The actual text content of the comment (93.65% fill rate)

Number of likes or reactions received by the comment (95.73% fill rate)

Number of direct replies to the comment (95.57% fill rate)

Any files or attachments associated with the comment (10.85% fill rate)

Length of video content, if applicable (0.00% fill rate)

Type of source (93.65% fill rate)

Subcategory or specific type of the post or comment (93.65% fill rate)

General category of the post or comment (100.00% fill rate)

Commentator profile URL (47.19% fill rate)

Direct link to the comment (85.88% fill rate)

Whether this is a reply to another comment (55.25% fill rate)

Parent comment id (1.87% fill rate)

The URL of the profile picture of the commentator (5.48% fill rate)

Any images associated with the comment (0.06% fill rate)

Frequently Asked Questions

Common questions about How to Scrape Facebook Comments into Make

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Start extracting facebook comments data and pipe into Make in minutes.

Go to Facebook Comments scraper Browse all integration guides

No code requiredAuto-delivery to Make22 data fields