Free · no signup · AI-powered insights
Instagram engagement rate, with real analysis.
Enter a public handle. We fetch live profile data and recent posts, compute follower-based engagement rate with the formula shown in your results, then add a short AI audit grounded in those numbers. Same GET /v1/instagram/profiles/{handle} endpoint our customers call from code.
Protected by Cloudflare Turnstile · 1 lookup/min · 10/day per IP
What you're measuring
Follower-based engagement rate, explained
Teams use several ER formulas. This tool sticks to the one most common in Instagram vetting: interactions divided by follower count, as a percentage. Good for comparing creators at a similar scale — not a full picture of reach or revenue.
Interactions
Likes plus comments on each post. Saves and shares stay out of the headline rate — Instagram does not expose them reliably across post types.
Follower denominator
Current public follower count from the profile. That is the usual benchmark when comparing creators of similar size, even though it understates reach for accounts that punch above their follower base on Reels.
Views stay separate
Video view counts show up in the per-post table but do not feed the average ER. Mixing views into a follower-based rate makes cross-post comparisons hard to read.
Formula per post
(likes + comments) ÷ followers × 100
Headline metrics are the average and median of that rate across recent posts with visible counts.
The math
Transparent calculation, no black box
Every figure in your results links back to the same formula. You get per-post breakdowns, sample coverage notes, and volatility when there is enough data to compute it.
Per-post, then aggregate
Each recent post with visible counts gets (likes + comments) ÷ followers × 100. We report the average and median across those posts.
Hidden counts are skipped
When Instagram hides likes or comments, that post drops out of the average. We tell you how many were excluded instead of guessing.
Labels are directional
Quality bands (nano through mega) shift the thresholds. They are rough context for account size, not a substitute for your own benchmarks.
Built on the real thing
More than a calculator — a compact audit.
We pull live profile and recent-post metrics through the production Instagram profile endpoint, compute engagement rate in the open, then run a structured AI pass on top. The audit reads your fetched numbers — content mix, volatility, best and worst posts — and suggests experiments. It does not replace due diligence on audience quality or brand fit.
Transparent math
Average and median engagement rate, per-post ER, comment-to-like ratio, and explicit notes when Instagram hides counts or the sample is thin.
Actionable AI layer
Headline read, content-pattern notes, and three experiments to try — each tied to metrics from the lookup, not generic growth advice.
Production API underneath
Paid customers hit the same profile endpoint from their backend. This page is a browser wrapper with Turnstile and rate limits.
Free tool limits
Good for spot checks, not pipelines
The browser form uses the same profile lookup as the paid API, but it is capped so the free tier stays usable for everyone. No signup required — and no substitute for an API key when you need volume or automation.
Fair-use rate limits
One lookup per minute, three per hour, ten per day per IP — enough for spot checks, not for screening hundreds of creators in an afternoon.
Recent-post window
Metrics come from the timeline posts bundled with the profile lookup. You cannot pick a date range or pull a full archive from this page.
AI is optional context
The structured metrics stand on their own. The audit layer reads those numbers only — it does not invent follower counts or engagement rates.
Private accounts may return profile basics, but public engagement math needs visible post data. If you hit the rate limit, wait for the retry window or sign up for API access — paid lookups run on your key with normal billing, not the free-tool caps.
For agencies & marketers
Audit hundreds of creators from code.
This page is for a quick manual check on one handle. When you need to screen influencer lists, refresh campaign benchmarks nightly, or pipe metrics into a CRM or Looker tile, call the profile API from your backend. You get the same JSON shape — profile, followers, recent posts with likes and comments — and you can compute ER your own way or store raw fields for later.
Need post history beyond the recent timeline, comment threads, or cross-platform data? Those live on other endpoints in the docs. Start with the profile lookup for vetting; branch out when your workflow needs more surface area.
const profile = await fetch("https://api.socialfetch.dev/v1/instagram/profiles/creator",{ headers: { "x-api-key": "…" } });
FAQ
Questions you probably have
How is engagement rate calculated?
We use (likes + comments) ÷ followers × 100 for each recent post with visible counts, then report the average and median across those posts. Video view counts are shown separately — they are not mixed into the headline rate so results stay comparable.
What's the difference between average and median engagement rate?
Average is the mean across usable posts — one viral outlier can pull it up. Median is the middle value, which is often steadier when a creator has a mix of hits and quiet posts. We show both so you can spot skew.
Why might some posts show no engagement rate?
Instagram often hides like or comment counts on certain posts or accounts. We skip those posts in the average rather than guessing, and we tell you how many were excluded.
Why don't saves or shares count toward engagement rate?
Saves and shares matter for reach, but Instagram does not expose them consistently on every post type through public profile data. Likes and comments are the fields we can rely on for a comparable follower-based rate.
Does this work on private accounts?
If an account is private, we may show basic profile info but cannot calculate public engagement from recent posts.
What are the free tool rate limits?
One lookup per minute, three per hour, and ten per day per IP, plus Cloudflare Turnstile on each submit. That is enough for occasional vetting — not for batch screening. Use the paid API with your key when you need volume.
What does the AI analysis do?
After we compute metrics from live API data, a language model reads those numbers only and writes a short audit: what's working, caveats, and three experiments to try. It does not invent follower counts or engagement rates.
Can I automate this for many creators?
This page is for manual checks with fair-use rate limits. For pipelines, dashboards, or influencer screening at scale, use the Social Fetch Instagram profile API from your code — same endpoint, your API key, no browser caps.