Vet an Instagram Influencer Before You Pay: Age, Country, Engagement & Lookalikes
Combine 'About this account' (join date, country, former usernames), recent posts, and Instagram's own similar-accounts list into a quick authenticity and fit check for any creator.
- /v1/profile/about
- /v1/profile/posts
- /v1/profile/similar
- /v1/post/comments
Follower counts are easy to fake; account history and engagement aren't. This recipe pulls the signals a brand should check before signing a creator - using Instagram's own data, not third-party estimates.
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Paste a URL, see the result as a table and export it. Come back here for the code when you want it automated.
1. Check the account's history
/v1/profile/about returns what Instagram's About this account panel shows: the month the account joined, the country it's based in, and any former usernames. A two-month-old account with 500K followers, or one based far from your target market, is worth a second look.
2. Measure real engagement
Pull the last 30 posts with /v1/profile/posts and divide likes plus comments by follower count. Compare the median with the creator's peers from /v1/profile/similar - Instagram's own list of lookalike accounts.
3. Read the comments
/v1/post/comments returns the comment thread with replies. Walls of generic emoji-only comments from brand-new accounts are a classic engagement-pod signal.
Full example (Python)
# Get an API key: https://rapidapi.com/goodstobkal-goodstobkal-default/api/instagram-scraper57
HOST = "YOUR-API-HOST.p.rapidapi.com"
HEADERS = {"x-rapidapi-key": "YOUR_RAPIDAPI_KEY", "x-rapidapi-host": HOST}
BASE = f"https://{HOST}"
import statistics
import requests
def get(path, **params):
r = requests.get(f"{BASE}{path}", params=params, headers=HEADERS, timeout=330)
r.raise_for_status()
return r.json()
handle = "adenwang"
about = get("/v1/profile/about", channel_url=handle)
posts = get("/v1/profile/posts", channel_url=handle, count=30)["posts"]
similar = get("/v1/profile/similar", channel_url=handle, count=20)["profiles"]
followers = about["follower_count"] or 1
rates = [((p["like_count"] or 0) + (p["comment_count"] or 0)) / followers for p in posts]
print("joined:", about["date_joined"], "| based in:", about["account_country"])
print("former usernames:", about["former_usernames"] or "none")
print(f"median engagement: {statistics.median(rates):.2%}")
print("lookalikes to benchmark:", [s["username"] for s in similar[:10]])Replace YOUR-API-HOST and YOUR_RAPIDAPI_KEY with the values from the listing's Endpoints tab on RapidAPI.
Frequently asked questions
How can I see which country an Instagram account is based in?
/v1/profile/about returns the country from Instagram's About this account panel as account_country, along with the join date and any former usernames.
What is a good engagement rate on Instagram?
It depends on account size and niche - smaller accounts usually see higher rates. Benchmark a creator against their own lookalikes from /v1/profile/similar rather than a universal number.
How do I spot fake followers or engagement pods?
Warning signs are a very young account with a large following, engagement well below similar accounts, and comment sections full of generic emoji replies from new accounts. The calls in this guide surface each of those signals.