Vetting Instagram Influencers Before Paying Them: What I Learned Building a Quick Audit Script

Description and use

A Python script automates the audit of Instagram influencer metrics, flagging fake engagement and regional mismatches.

Problem

A marketing agency needed a quick way to verify an influencer’s audience and engagement legitimacy before signing contracts.

Outcome

The script enabled rapid assessment of influencer authenticity, reducing manual effort and identifying potential fraud.

Workflow

• Identify target influencer username
• Use hikerapi.com to fetch user data via API
• Parse JSON response for follower count, post stats, account history
• Apply custom thresholds to detect abnormal engagement patterns
• Flag accounts with sudden spikes or region mismatches
• Review flagged accounts before contract signing

Evidence

I set up a small Python script to pull user data, basic post stats, and account history to flag potential red flags—like sudden follower spikes or accounts registered in completely different regions than their target audience.

Source

The trickiest part wasn’t pulling the raw data—it was dealing with edge cases in engagement consistency. Standard follower-to-like ratios fail when posts go viral, so distinguishing between natural viral reach and paid bot engagement required writing custom thresholds rather than relying on simple averages.

Source