How to Get Instagram Analytics for Any Public Account

You can build genuinely useful Instagram analytics for any public account — a competitor, a creator you might sponsor, an account you're benchmarking against — using nothing but the data Instagram already displays publicly. Likes, comments, view counts, and post dates are visible to everyone; the trick is collecting and ranking them systematically instead of eyeballing a grid. A Chrome extension like FeedRama does that in a couple of clicks: sort the account by any metric, read the patterns, and export the numbers to a spreadsheet.

To be clear about what this is and isn't: Instagram Insights — reach, impressions, follower demographics — is only available to an account's owner, and nothing changes that. But most competitive questions don't need Insights. They need to know what's working for an account and how hard it's working, and public data answers both.

What's public and what's owner-only

Before you spend an hour hunting for a tool that reveals a competitor's reach — save the hour. Here's the actual dividing line:

Everything in the top half is enough for top-content analysis, engagement benchmarking, and trend tracking — the analytics that actually change your content decisions.

Step 1: Rank the account's content by what matters

Open the profile on instagram.com with FeedRama installed — it's a free, one-click install from the Chrome Web Store — then sort the feed by your metric of choice:

1. Sort by likes to see the account's crowd-pleasers — the content their audience broadly rewards.
2. Sort by views on their Reels to find what the algorithm amplified beyond their existing audience.
3. Sort by comments to spot the posts that started conversations — often the strongest community signal.
4. Sort by date to reconstruct their posting cadence and see how output maps to results.

Free accounts get unlimited sorts covering the previous 25 posts or last week — a solid monthly check-in. Pro removes the range limit for full-history analysis.

Even before any spreadsheet work, the sorted grid answers real questions. Are their winners a repeatable format or one-off virals? Do their top Reels cluster in a content pillar they've since abandoned? Is their most-commented post a community win or a controversy? Five minutes of sorted scrolling gives you a readout most people would only guess at.

Step 2: Turn rankings into metrics

A sorted grid answers "what's their best content?" A spreadsheet answers "how is this account really doing?" Export the sorted posts to CSV (a Pro feature) and compute:

• Engagement rate: (likes + comments) ÷ views on Reels. It won't match the owner's internal dashboard, but applied consistently across accounts it's a fair comparison stick.
• Consistency index: median engagement versus their top-post engagement. A big gap means they depend on occasional viral hits; a small gap means a reliable formula.
• Cadence curve: posts per week plotted against average engagement, which shows whether more volume is helping or hurting them.

A worked example: you're choosing between two creators for a sponsorship. Creator A averages 150k views with a 2% engagement rate; creator B averages 60k views at 7%. The sorted grids looked similar at a glance — the spreadsheet says B's audience actually listens. That's the kind of call public-data analytics exists to make.

The mechanics of the export live in How to Export Instagram Post Data to CSV; repeat it monthly and you get trend lines, as laid out in How to Track Competitor Engagement in a Spreadsheet.

Step 3: Read the qualitative layer

Numbers identify the winners; the content itself explains them. Once sorting surfaces an account's top ten Reels, run them through FeedRama's transcription and study the openings — the first sentence of a top-performing Reel is a free lesson in hook writing. Captions from the CSV give you the same visibility into their written voice, and on carousel-heavy accounts the first line above the fold does the same job a spoken hook does in a Reel. This is where analytics stops being a scoreboard and starts being a curriculum.

Where this fits in a competitor-research routine

Account-level analytics is one layer of a bigger practice. A monthly rhythm that works for small teams: sort each tracked account by views and likes, export to the running spreadsheet, transcribe any new outliers, and file standout posts into FeedRama folders for the swipe file. The complete playbook — including how to choose which accounts to track — is in How to Do Competitor Research on Instagram.

Two practical constraints to plan around: FeedRama runs in desktop Chrome only (no mobile, no Safari), and it can only ever analyze public accounts — if a competitor goes private, that's the end of the data trail, for everyone. The public-only rule cuts both ways, of course: your own account is equally legible to anyone with the same tooling, which is a strong argument for knowing exactly what your public numbers say about you before a competitor reads them first.

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