What this calculator does

Enter any public Instagram @username — creator or brand.

We read a short, recent window of posts (up to 18) and take the average likes + comments per post.

If there are fewer posts we use what’s available. A CAPTCHA may appear occasionally to keep bots away.

Formula, in plain words

ER shows reactions per post relative to followers. We use a simple definition that stays comparable across account types.

ER (%) = 100 × (average likes + comments per post) ÷ followers

Per‑post engagement, not a single spike

Single posts can overperform or underperform. A short rolling window gives a steadier baseline for quick decisions.

Average reactions per post = (Σ likes + comments across recent posts) ÷ number of posts

Example. Account: 75,000 followers. Recent posts: 10 posts ~ 1,200 likes + 45 comments; 5 posts ~ 800 likes + 30 comments.

ER ≈ 100 × (((1245×10 + 830×5) ÷ 15) ÷ 75,000) ≈ 1.48%

Use the baseline to compare creators in the same niche and size — not to chase a one‑off viral post.

Why we use a short recent window

Recency reflects what the audience reacts to now, while a small window reduces outliers.

If a profile has fewer posts, we divide by the number we find — no hidden boosts.

Seasonality, promos and experiments can distort long windows; a compact window keeps the score relevant.

Why marketers check ER

Manual math is slow and error‑prone. A calculator keeps everyone on the same page.

An online check saves hours and makes comparisons consistent across proposals.

With Stars.md you can:

• Triage big shortlists in minutes
• Set expectations for formats and deliverables
• Spot content‑audience mismatch early
• Compare profiles within the same topic and size

Follower growth and posting cadence help interpret ER changes.

Want to see how ER changes? Just repeat the check from time to time — it’s fast.

A pragmatic way to use ER

Run an ER check for each candidate profile.

Then combine ER with a few quick sanity checks:

• Relevance first: topic, region, language and tone
• Compare ER to peers of similar size and niche
• Open several recent posts and read real comments
• Scan growth history for unusual jumps or plateaus
• Decide: test collaboration, re‑scope, or skip

Treat ER as a fast filter, not a final verdict.

If ER is far below the peer baseline, consider a different format, timing or a smaller test before a full campaign.

Need deeper context? Our full reports add audience quality and risk indicators.

What is Instagram Engagement Rate

Engagement Rate summarizes how often people react to content: likes + comments per post relative to followers. It is simple and comparable — perfect for a first look.

Relevant content earns attention. Consistency keeps it.

What ER actually tells you

ER is a signal of audience involvement, not a full diagnosis.

It often correlates with stable reach distribution on the platform.

Follower count alone predicts little — the quality of engagement matters more.

A smaller creator with strong ER can rival the effective reach of a much larger profile with weak ER.

Use ER alongside content quality, audience match and brand safety.

There is no universal “good ER”

Build your own baseline by niche, region and size. Compare like with like and focus on recent content. Brand accounts usually show lower ER than independent creators.

Typical patterns by account size (qualitative):

• Smaller creators: often higher ER thanks to close‑knit audiences
• Mid‑size profiles: ER moderates as reach broadens
• Large accounts: ER is lower; formats and storytelling matter more
• Brands: typically lower ER than creators in the same niche

Use these as heuristics, not rules. Always check recency and audience fit.

Avoid cross‑comparing different sizes and topics — expectations and pricing models differ.

Why can ER be low

Common causes: audience mismatch, repetitive topics, a history of giveaways or pods, poor timing, or shifts in platform behavior. The remedy is usually content experimentation and better audience understanding.

Does ER reveal fake followers

ER alone is not a detector.

Very low ER is a reason to look deeper, but you need more signals.

Typical inauthentic patterns include:

• Giveaway‑driven spikes with later drops
• Unusual geography mismatches
• Comment pods or repetitive generic replies
• Mass‑follow or mass‑like behavior
• Sudden audience jumps without content drivers

Combine ER with growth history and audience quality checks to assess risks.

Why this calculator is free

Stars.md builds practical tools for creator analytics and brand collaborations.

The calculator is part of our open toolkit — a quick check you can use any time.

Use it freely for research and planning.

For deeper work, Stars.md offers advanced features:

• Creator discovery with filters
• Audience quality and risk indicators
• Audience overlap insights
• Similar profiles suggestions
• Ad post detection
• Exports with contacts
• Outreach tools

Need Engagement Rate history?

Want ER and follower dynamics over time? Re‑run checks periodically — it takes seconds. No account connection required.

Day‑by‑day dynamics help you understand how campaigns, formats and seasons affect engagement.