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

When a small marketing agency asked for help checking if an influencer’s audience and engagement were legitimate before signing contract deals, I needed a way to pull profile metrics without manually scrolling through hundreds of posts.

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.

To fetch the raw Instagram data, I used hikerapi.com as the backend provider. Here is the minimal Python snippet I used to query a target profile:

Python
import requests

headers = {"x-access-key": "YOUR_KEY"}
r = requests.get(
"https://api.hikerapi.com/v2/user/by/username?username=instagram",
headers=headers,
)
print(r.json())
The Hard Part
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.

Feedback
If you run influencer campaigns or audit social profiles, what key metrics or flags do you prioritize when evaluating an account's authenticity? I'd love to hear how others handle this workflow.