Instagram engagement rate calculator
Add up the likes and comments on a handful of recent posts, type in your follower count, and get your engagement rate by followers. Add reach from Insights to get engagement by reach as well.
From Insights
From Insights
From Insights, for engagement by reach
- Interactions per post
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- Engagement by followers
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- Engagement by reach
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- Posts sampled
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per post ÷ followers
interactions ÷ reach
The formulas
- Interactions = likes + comments + saves + shares (saves and shares count as 0 when left empty).
- Engagement by followers = interactions ÷ posts ÷ followers.
- Engagement by reach = interactions ÷ total reach of the same posts.
Limitations
The result is only as good as the sample. Hidden like counts, giveaways, boosted posts and Reels shown to non-followers all move the number. Comparing your own accounts over time with the same method is more meaningful than comparing against someone else's rate.
Engagement is not in your follower export, so FindUnfollower's export tools cannot compute it. For the numbers that are in the export, see the account health checker.
Engagement rate questions
How is Instagram engagement rate calculated?
By followers: (likes + comments + saves + shares) on your sampled posts ÷ number of posts ÷ followers. By reach: the same interactions ÷ the total reach of those posts. This calculator shows both, so you can see which one a brand or report means.
Engagement by followers or by reach: which should I use?
By followers works for any public account, because likes, comments and the follower count are visible. By reach is more accurate, since it only counts people who actually saw the post, but reach is only available in your own Insights.
Can you calculate engagement for any profile automatically?
Not here. Doing that means scraping Instagram, which its terms forbid. Type in the numbers you can see or that your Insights show; nothing is fetched from Instagram.
How many posts should I sample?
Take your last 6 to 12 regular posts and skip ones that were boosted or went unusually viral; they skew the average. Use the same sample every time you compare.
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