What problem does the Reels Outlier Detection solve?

The client needed to monitor 50+ Instagram business accounts and instantly identify high-performing Reels without manual checking. Manually reviewing every new Reel across all accounts took 5+ hours daily. Viral content was missed and responses to trending opportunities were delayed. There was no central system tracking which Reels had already been reviewed or notified.

How does the Reels Outlier Detection work?

Loop over unprocessed accounts from the accounts sheet. Scrape the 12 most recent Reels per account via SocialCrawl. Normalise the data and calculate the median view count. Filter for outliers at ≥ 3× median within a 14-day window. Deduplicate against the Reels sheet so nothing is notified twice. Send a formatted Telegram message, log the Reel, and mark the account processed.

Which tools and integrations does it use?

It is built on n8n and integrates n8n, SocialCrawl API, Google Sheets, Telegram Bot, JavaScript.

What results does it deliver?

10+ hours saved per week by eliminating manual Reel monitoring. 100% detection rate — no viral Reel missed. ~20 qualified Reels notified per run on average. Client acts on viral content within hours instead of days. Scalable — accounts are added or removed via a Google Sheet.

Instagram Reels Outlier Detection with n8n & Telegram

n8n social analytics system monitoring 50+ competitor accounts, scoring video views against account medians and sending viral outlier alerts to Telegram.