RJNSHow to Find the Best-Performing
Instagram Posts
Find the posts worth studying by separating raw scale from unusual performance. The strongest competitor post is not always the one with the most likes.
To find a competitor's best-performing Instagram posts, rank a consistent recent sample by the public metric that matches your question, then compare each post with that account's normal performance. Use raw Views, Likes, Comments and available Shares first; use engagement rate or an outlier multiplier as context rather than replacing the raw metrics.
Why “most likes” is not enough
A post can have the highest like count because the account is large, the post has been live longer, or the content format naturally receives more exposure. If your goal is to find ideas that are unusually effective for a particular account, you need both absolute performance and relative performance.
Which post has the most Views / Likes / Comments / Shares?Which post most exceeded this account's comparable baseline?Both questions are useful. They simply identify different types of winners.
A 6-step method for finding top posts
Use the latest 10, 50 or 100 posts, or a fixed recent time window. A consistent sample prevents you from comparing one competitor's last month with another competitor's entire history.
If Reels dominate view counts while carousels produce stronger comments, compare like with like before declaring a universal winner.
Use Views for visible distribution, Likes for lightweight interaction, Comments for public response, and Shares when the value is available.
When follower count is available, a consistent follower-based engagement rate can add account-size context. If you have first-party reach data for your own posts, reach-based engagement answers a different question.
Compare each post with a relevant baseline. A post at 3× its account's typical performance can be more interesting to study than a larger absolute post that is normal for a huge account.
Review hooks, topics, visual formats, caption angles and timing across several winners. The goal is to find patterns that repeat, not to overfit to one exceptional post.
Which metric should you sort by?
| Sort by | Best for | Do not assume |
|---|---|---|
| Views | Finding posts with the strongest visible distribution. | That high views mean high retention or conversion. |
| Likes | Finding posts with high lightweight interaction. | That likes alone indicate unusual account-relative performance. |
| Comments | Finding posts that triggered more visible conversation. | That all comments are positive or high quality. |
| Shares | Finding content with visible evidence of being passed onward. | That share data is consistently exposed on every public post. |
| Engagement rate | Adding denominator-aware context to interactions. | That two rates are comparable without checking the formula. |
| Outlier multiplier | Finding posts that depart from an account's typical range. | That a high multiplier predicts future virality. |
Example: raw winner vs relative winner
Imagine a competitor's recent Reels usually receive about 20,000 views. One Reel reaches 48,000 views and another reaches 70,000. The 70,000-view Reel is the absolute winner. But now imagine the 48,000-view Reel belongs to a second competitor whose Reels usually receive only 8,000 views. Relative to its own baseline, that second Reel may represent the more unusual content event.
This is why account-relative analysis can reveal ideas that a simple “sort all competitors by likes” spreadsheet misses.
What to inspect after you find a winner
- Opening idea: What promise, question, conflict or visual appears first?
- Topic: Is the post educational, entertaining, promotional, opinionated or reactive?
- Format: Reel, carousel or image—and is that format typical for the account?
- Specificity: Does the post make a concrete claim rather than a generic one?
- Caption: Does the caption add context, storytelling or a call to action?
- Timing: Was the post tied to a launch, trend, event or seasonal moment?
- Repeatability: Did similar posts also perform well, or is this a one-off exception?
Turn those observations into hypotheses. For example: “specific before/after examples may outperform broad advice in this niche.” Then test the idea with original creative.
How RJNS approaches top-post research
RJNS starts with public primary metrics instead of hiding them behind a black-box score. You can analyze a public account, sort recent posts by Views, Likes, Comments or Shares, and then use derived Engagement, ER and Outlier Multiplier as additional context.
Missing Share data is kept explicit rather than automatically treated as zero. For Reels-specific research, see Instagram Reels competitor analysis.
FAQ
Use a sample large enough to represent the account's current content strategy without mixing very old and current behavior unnecessarily. A recent fixed sample is often easier to compare across competitors.
Choose the metric based on the question. Views are useful for visible distribution; Likes indicate interaction. Looking at both is usually more informative than forcing one metric to replace the other.
An outlier post materially exceeds or falls below a relevant account baseline. The baseline should be explicit and comparable, such as recent posts of the same format.
No. It tells you what deserves investigation. Use competitor winners to generate hypotheses, then create and measure original tests for your own audience.
Build the full workflow
Rank a competitor's recent posts.
Enter a public Instagram account in RJNS, then sort the recent sample by the metric you want to investigate.