Export Instagram Post & Reel Likers to a Spreadsheet
Extract everyone who liked an Instagram post or reel. Paste a fetch() from DevTools (Copy as fetch from the likers dialog) to scrape usernames, names, and profile URLs with automatic pagination.
Export Instagram Post Likers to a Spreadsheet
Extract everyone who liked an Instagram post or reel and export their profiles to Google Sheets — automatically with pagination.
What This Workflow Does
Paste a fetch() request from your browser's DevTools (copied from the Instagram likers dialog), and this workflow pages through all likers, extracts their usernames, full names, and profile URLs, then saves everything to Google Sheets.
The Pipeline
- Manual Trigger: Paste a fetch() from DevTools (Instagram GraphQL likers request)
- Parse Request: Extracts the URL, headers, media ID, and auth tokens
- Loop Through Pages: Fetches each page of likers with automatic cursor-based pagination
- Extract Profiles: Pulls username, full name, profile URL, and verification status
- Save to Google Sheets: Writes each batch to your spreadsheet in real time
Setup
- Go to Instagram and open the post/reel you want to scrape
- Click the likes count to open the likers dialog
- Open DevTools (F12) > Network tab
- Filter by
graphqland find thePolarisPostLikedByListDialogQueryrequest - Right-click > Copy as fetch
- Paste into the Manual Trigger node
- Connect Google Sheets and set your sheet URL in the AI node
- Run the workflow
Data Extracted
| Field | Description |
|---|---|
| username | Instagram handle |
| full_name | Display name |
| profile_url | Link to profile |
| is_verified | Blue checkmark status |
Best Practices
- Session freshness: Instagram sessions expire. Use a fresh fetch() each run.
- Rate limits: The workflow includes delays between requests to avoid throttling.
- Large posts: Posts with thousands of likes will take longer but the workflow handles pagination automatically.
Who Is This For
Marketers, brands, and growth teams who want to analyze engagement, build lookalike audiences, or identify potential leads from competitor posts.
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