Across 516,000 posts analyzed, 34.8% flop at under 10 likes. The good news: the signals of a flop are readable before you publish.
In short
→ 1 in 3 posts is nearly invisible — median engagement sits at 18 likes across our corpus of 516,144 posts, and 34.8% of posts fall below 10 likes. → A flop is not random: a weak hook, wrong format, insufficient length, missing tactics — these signals are detectable cold, before you publish. → The LinkPost virality score analyzes 33 criteria and 300+ factors before you publish. → In practice: users who fix their post based on the score get an average of 1.93× more likes over 60 days, and their best post improves by 3× in median. → 1 in 4 users multiplies their personal record by 10× or more.
Why 1 in 3 posts flops — even from good creators
It's not a talent problem. It's a missed-signals problem.
Our analysis of 516,000 LinkedIn posts confirms it: engagement follows a power law distribution. Median at 18 likes, 90th percentile at 151, 99th at 1,226. The same person can publish a 500-like post one week and an 8-like post the next.
That's not random. Flopping posts share common, measurable signals — visible before you publish:
→ a hook that creates no tension in the first 200 characters → a format mismatched to the reach you're targeting (plain text where a carousel would have multiplied impressions) → length too short to generate dwell time → no writing tactic that anchors the post in reality (quantified proof, personal story, vulnerability)
The problem: without outside feedback, you can't see these things in your own text.
What the virality score actually analyzes
The LinkPost virality score evaluates your post across 33 criteria grouped into 300+ factors, weighted against patterns measured in our corpus:
| Criterion | What the score checks | |---|---| | Hook | Do the first 200 characters create a pattern interrupt? | | Format | Does your format match your reach objective? | | Length | Is the post long enough to hold attention and generate dwell time? | | Tactics | Are you stacking at least 2–3 high-performing writing tactics? | | Anchoring | Is there quantified proof or a real-world reference? |
You get a score plus the exact points to fix — before you publish. The correction rarely takes more than 5 minutes.
The tactics most predictive of a strong score
Our study on writing tactics isolates the patterns most correlated with engagement across our corpus of 516,144 posts:
→ social proof: median 36 likes → vulnerability: median 33 likes → quantified proof: median 32 likes → stacking: viral posts layer 4 to 6 tactics — never just one
This is exactly what the virality score looks for in your text. If one of these tactics is missing, it tells you — and suggests how to weave it into your existing post.
The 27 personalized factors in the engine also adapt to your own writing style: your score evolves as you publish more, not just against a generic benchmark.
What changes in practice
LinkPost users who revise their post based on the score get an average of 1.93× more likes over 60 days. Their best post improves by 3× in median. And 1 in 4 users multiplies their personal record by 10× or more.
This isn't magic — it's the feedback loop you didn't have when you were publishing blind.
More than 1 million posts have already been analyzed through the LinkPost engine. The dataset grows with every analysis, continuously refining the weightings.
What to do before your next post
- Write your post as you normally would.
- Paste it into the free analyzer — you get a score plus the points to fix.
- Adjust in 5 minutes.
- Publish.
Repeat this over 30 to 60 days and it transforms your growth curve.
Try the Post Analyzer on your next post — no account needed, it's free.
Observational study by LinkPost on 516,144 posts (2020 to April 2026, 62% French-language content). Findings are correlations: correlation does not imply causation, sample bias possible. Methodology and limitations detailed in the full study.
About the author

Yannis Haismann
Co-founder of LinkPost
Yannis writes about LinkedIn content creation, virality prediction and the algorithm. He builds LinkPost, calibrated on more than a million analyzed posts.
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