TechieTutuQ: Instagram scraping - structured data output for n8n/Airtable?
Hi Claire,
Planning to scrape Instagram posts from ~150 profiles from my clients & mastermind people weekly → Airtable via n8n. I see I can provide IG credentials for login.
Questions:
Does BrowserAct return Instagram data as structured JSON (username, post_date, caption, image_url, likes, comments as separate fields)? Or unstructured data requiring manual parsing?
How easily do BrowserAct outputs map to Airtable columns in n8n?
Assuming my Credit calc is correct: Scraping 20 posts from 150 profiles weekly. My estimate: Login (5) + Navigate (5) + Scroll (5) + Extract (5) + Output (5) = 25 credits/profile × 150 = 3,750 credits/run × 4 weeks = 15,000/month. Is my calculation right & is Tier 1 (20k credits) sufficient?
Need clean, structured data before purchasing. Currently evaluating vs Apify & Phantombuster. Thanks!
Claire_BrowserAct
Feb 8, 2026A: Hi there — yes, this is fully supported inside BrowserAct.
You can extract posts from Instagram accounts, including customers or mentors, and export the results as structured JSON directly from your workflow.
Once the data is generated, you can map each JSON field into n8n and send it into Airtable by matching keys with Airtable column names. This setup is widely used for content tracking, creator monitoring, and lead data pipelines.
About credit usage:
Each workflow step consumes credits.
Navigate = 5 credits
Scroll = 5 credits
If Loop is used, every node inside the loop is multiplied by the number of iterations, so total credits depend on how the workflow is structured and how many posts are processed.
If credits run low, you can purchase additional credit packs anytime to keep workflows running.
If you'd like faster help or want us to review your workflow setup, you’re welcome to join our Discord community. Our team is active there daily and can guide you step by step based on your exact use case.
Please feel free to send over any additional questions anytime.