🔬 LinkedIn Content Intelligence Report

We analyzed 7,796 posts from 418 creators — here's what actually matters (and what doesn't)

Report Generated: January 22, 2026
Data Range: May 16, 2018 → January 22, 2026

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📊 At a Glance

📈 Engagement Distribution

Minimum:     0
25th %ile:   18     ← Bottom quartile
Median:      60     ← Typical post
75th %ile:   243     ← Good performance
90th %ile:   803     ← Great performance
99th %ile:   5,232    ← Viral territory
Maximum:     25,496

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📋 Executive Summary

🎯 Key Discoveries

1. Analyzed 7,796 posts from 418 creators
2. Median post gets 60 engagement, top 10% get 803+
3. <1K creators have 0.98% engagement rate
4. "CURIOSITY GAP" hooks generate 8,528 avg engagement
5. Optimal word count: Very Long (350+) (124 median engagement)

🧪 Myths Tested

🧪 "Hashtags boost engagement" → BUSTED - Posts without hashtags perform equally well

✅ "Small accounts get better engagement" → CONFIRMED - Small accounts (<10K) have 339% higher engagement rates than large accounts (50K+). The myth is TRUE.

💡 Actionable Takeaways

1. Top 10% creators get 103.2x more likes per post
2. Use IMAGE format - it outperforms others
3. Start with curiosity gap hooks
4. Viral pattern: Strong narrative hook in the first 1–2 lines
5. Opportunity: "Career Journey" has high engagement but low competition

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📏 Engagement Benchmarks

Use these thresholds to evaluate your content performance:

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🏆 Top 10 High-Engagement Posts (By Engagement Rate)

Why these posts? Ranked by engagement rate (engagement ÷ followers), not raw numbers.
This surfaces exceptional content from creators of ALL sizes — not just mega-influencers.

#1: Carmelo Juanes Rodríguez

🔗 View Original Post on LinkedIn

Full Post Content:

This is so relatable and funny!

I love AI coding tools.

They're fast, creative, and can make your code look like art.

But the truth is, a lot of AI-generated code still doesn't work in production.

At Invofox, we see this every day.

We work with highly regulated, financially sensitive, and complex document workflows.

One small hallucination or parsing error can have massive downstream impact, so "almost right" != "good enough".

AI has made it easier than ever to build.

But making that AI production-grade, tested, compliant, explainable, and reliable is where the real engineering happens.

That's exactly what we focus on at Invofox: making AI work in production.

Beautiful code and AI means nothing if it breaks when it matters most.

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#2: Ingrid Rieken

🔗 View Original Post on LinkedIn

Full Post Content:

What can truly unite 15,000 employees?

At Everllence we are all for zero! 🫶

Today marks the launch of our new employer branding campaign. And ‘All for zero’ is more than just a tagline. It is a shared mindset that connects our pioneering spirit, our drive for excellence, and our deep sense of teamwork. It’s how we live our purpose: Moving big things to zero.

💬 Co-created with colleagues from around the world, this campaign is built on real voices and real stories. 
🌍 It’s designed to attract new talent – and to unite us as one team under our new brand Everllence. 
💙 As CHRO, I’m proud of this next chapter. Because a strong employer brand isn’t just about standing out. It’s about standing together.

👉 Watch the video and feel the energy of Everllence. Let’s give it all for zero.

#WeAreEverllence #MovingBigThingsToZero #AllForZero

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#3: Tomer C.

🔗 View Original Post on LinkedIn

Full Post Content:

David AI has raised a $50M Series B to establish the data layer for audio AI.

This round was led by Meritech, with participation from NVIDIA and our existing investors Alt Capital, First Round Capital, Amplify Partners, and Y Combinator.

Audio is the frontend interface for AI. Real-world AI-such as robots, wearables, personal assistants–runs on audio.

However, these systems need far more training data and evaluations. David AI exists to create that data–fueling the models that will bring these use cases to life.

David AI is an audio data research lab. To best serve our customers, we’re bringing a research-driven approach to dataset development.

If you’re excited about our mission, we’d love for you to apply. You can check out our open roles below.

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#4: Yanni Pappas

🔗 View Original Post on LinkedIn

Full Post Content:

I'm calling it right now. The biggest marketing shift in 2026 won't involve AI. It's something much simpler: things that are unmistakably real, honest, and human. Below are some of my favorite examples from 2025 that reflect this concept.

A24 put an "engagement announcement" in The Boston Globe to promote their upcoming film with Robert Pattinson and Zendaya, titled 'The Drama'

Hulu used real apples in grocery stores to promote Abbott Elementary with stickers slapped on the classic teacher-gift trope

Rachel Karten uses her own handwriting on simple objects, like napkins, to explain social media concepts on her Substack newsletter & LinkedIn

Workshop launched an old-school advice column site called 'Ask Devin' featuring Devin Owens giving real, human advice on internal comms questions

Ramp livestreamed Kevin from 'The Office' working inside a cubicle for 6 hours in the middle of NYC & put up physical flyers to promote the stunt

Canva staged a real billboard stunt, using humor to show when "make the logo bigger" goes a bit too far

Anthropologie started "selling" rocks in stores after a TikTok prank went organically viral

Call it the Analog Renaissance, call it guerrilla marketing, call it an OOH advertising comeback. This 'era' can be called MANY things. This era IS many nuanced things at once. The crave for IRL, tangible experiences, and feeling human again.

But one thing underpins it all. Christina Le calls it a shift towards "intellectual honesty." The idea of social going slow. Less rage bait, less AI slop, less "your attention span is cooked and here's content to perpetuate that brainrot."

The brands that win in 2026 will be the ones that understand that real attention is earned through real honesty.

And for that reason, I have hope for marketing this year.

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#5: Steef Coene

🔗 View Original Post on LinkedIn

Full Post Content:

Met mijn Cold Calling Script kreeg een klant 42 gekwalificeerde afspraken in 5 dagen.

En jij kunt 'm nu gratis ontvangen!

De meeste cold calling scripts zijn veel te lang, focussen op wat je moet zeggen, en hebben nauwelijks aandacht voor mindset.

Want laten we eerlijk zijn: cold calling lijkt op voorhand niet de allerleukste taak om te doen.

Totdat mijn klant 42 gekwalificeerde afspraken boekte en +10 deals sloot.

Het spelletje wordt leuker als je het snapt.

Ik heb nu de GPT Cold Caller Script gebouwd om jouw persoonlijke belscript te maken, terwijl je collega koffie zet.

Dit is wat je kan verwachten:
– Hoe in 3 stappen de gatekeeper jouw vriend wordt.
– De mindset truc die van cold calling je hobby maakt.
– Hoe je consistent afspraken boekt met beslissers.
– Hoe je bezwaren omzet naar JA'S

Kortom, een kort script die jou helpt om afspraken te boeken vanuit koude acquisitie.

Wil je de GPT Cold Calling Script ontvangen?

✅ Comment "Call"
✅ Connecteer met mij (anders kan ik je niks sturen)

Dan stuur ik je het script z.s.m. toe!

PS: Reageer je binnen 24 uur? Dan krijg je mijn exclusieve cold calling training cadeau t.w.v. €350

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#6: Joonhyeok Ahn

🔗 View Original Post on LinkedIn

Full Post Content:

In 2025, Claude became my co-founder.

Not an assistant. A system that runs 40% of my agency operations.

Here's the blueprint I wish existed 6 months ago.

Most people ask Claude questions.

I built Claude into my business infrastructure.

So I packaged everything into one resource.

What's inside:

→ Claude Projects Architecture
Structure that turns chaos into compound knowledge

→ Claude Code Setup
Deploy agents that write and execute code

→ Claude + n8n MCP
Build automations by describing them in plain English

→ Claude Skills Blueprint
Custom instructions that make Claude an expert in your domain

→ Query MCP + SEO MCPs
Connect Claude to live data sources for research at scale

Agencies charge $3K-8K to configure systems like these.

Took me 200+ hours to test and document.
Free for you.

1. Connect with me
2. Like + Comment "blueprint"
3. Repost for priority access

Happy New Year. Make 2025 the year you stop using AI like a search engine❤️

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#7: Julien Renaux

🔗 View Original Post on LinkedIn

Full Post Content:

We made the hard decision to rewrite our entire backend in Rust today. 🦀

Our legacy Node.js architecture just wasn't handling the concurrency we needed for our 2025 roadmap.

We needed memory safety. We needed raw speed. We needed to be "blazingly fast."

It took 48 hours of non-stop coding. No sleep. Just caffeine and documentation.
We migrated everything to a microservices architecture running on a multi-cluster Kubernetes setup.

Is it overkill? Some might say yes.
But when you are building for the future, you can't cut corners.

Now, my personal portfolio page with zero visitors loads 3 milliseconds faster. 🚀

#Engineering #Rust #Scalability #DevLife

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#8: Walid Boulanouar

🔗 View Original Post on LinkedIn

Full Post Content:

We just launched AYn8n.

The most impactful automation library for marketers, founders, and growth teams.
5000+ ready-to-use workflows for marketing, sales, ops, and product.
Updated weekly.
No more hunting across forums, GitHub, or Slack threads.(watch the full video)

One workflow = one transformation.

Example?
Drop 1 product image → get unlimited UGC videos
→ AI analyzes the image
→ Scripts generated in seconds
→ Different actors produced
→ Videos delivered instantly, ready for ads and socials

All you do is drop a link, choose how many videos you want, and AYn8n copied workflow handles the rest.
You can watch the demo in the video below.

This is just one of thousands.
Everything is built, documented, and reference-backed.

AYn8n isn’t just about workflows.
It’s the library you open when you want results fast.(ai-powered search)

We’re opening free access for early users.

We’re opening access for early users.

1. ❤️ Like
2. 💬 Comment “ayn8n”
3. 🔄 Repost( if you want for sure)

…and I’ll share the link with you.

This is the platform we’ve been waiting for.
And this is just the beginning.

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thanks for the support you can check the website here: ayn8n.com

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#9: Ariel Cohen

🔗 View Original Post on LinkedIn

Full Post Content:

🚨 BREAKING: The man who built Tesla's AI brain just released the architecture for mass-producing executive decisions.

Karpathy built a $50M executive team for $0.02 per decision.

Yet most CEOs are still paying for one opinion.

It's called LLM Council. And it makes asking one AI look like asking one intern for strategy advice.

Your question goes to 4 of the world's smartest AIs at once.

Each answers independently.

Then they review each other's answers, anonymously. They rank them. They call out weak reasoning.

Then a Chairman AI delivers one final verdict.

I fed it 6 months of revenue, offer suite, and pipeline data.

In one session, the Chairman delivered:
→ A GTM motion chasing buyers who never close (and the ICP that does)
→ A positioning gap letting cheaper competitors win our deals
→ A competitor using AI in a way we hadn't considered
→ The one process costing us 30 hours/week (fixable in a day)
→ The hire we thought we needed (we didn't)

It didn't give me 4 opinions. It gave me one verdict. ICP rebuilt. Positioning fixed. Hiring plan killed.

This isn't a chatbot. It's a shadow board that never plays politics.

And unlike a $400K strategist, it never defends its own recommendations.

I packaged the full implementation:

✅ The Multi-Model Consensus Prompt Pack
✅ The 4-AI Peer Review Template
✅ The Chairman Synthesis Framework
✅ The Plug-and-Play Config (ready to run)

Four minds. One decision. Zero politics.

Want it?

1. Comment "COUNCIL" below
2. Connect with me (so I can send it)
3. Like this post

P.S. Repost for priority access

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#10: Adam Janes

🔗 View Original Post on LinkedIn

Full Post Content:

I finally understand that old $10,000 engineering invoice joke.

You know the story.

A giant machine breaks down.

An expert comes in, looks at it for a minute, and taps one specific spot with a hammer.

The machine starts working perfectly.

He sends an invoice for $10,000.

The manager is furious and asks for an itemized bill.

The expert writes:

• Tapping with hammer: $1
• Knowing where to tap: $9,999

This is exactly what's happening to software development right now.

Tools like Cursor have made the "tapping" nearly free.

The actual writing of syntax costs pennies.

You can generate thousands of lines of code in seconds.

But the "knowing where to tap"?

That just became the most valuable skill on the planet.

You can't effectively direct an AI if you don't understand system architecture.

You can't spot a hallucination if you don't know what the code is supposed to do.

We are moving from being typists to being directors.

The question isn't "Can AI write this code?"

The question is "Do you know enough to tell it what to write?"

Are you preparing for that future?

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1️⃣ Engagement Patterns

Comment-to-Like Ratio by Topic

High ratio (🔥) = conversation starters | Low ratio (👀) = passive consumption

Insight: Topics with high comment ratios (>0.3) are "conversation starters" that fuel the algorithm. Posts in these categories get more visibility because comments signal high engagement quality.

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Engagement Rate by Follower Tier

Does the "small accounts get better engagement" myth hold up?

✅ Myth Verdict: CONFIRMED

Small accounts (<10K) have 339% higher engagement rates than large accounts (50K+). The myth is TRUE.

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🏅 What Top Performers Do Differently

Comparing creator tiers by performance:

Key Insights from Top 10% Creators:

• 1.8x higher engagement rate than bottom 25%
• Average 2,580 likes and 316 comments per post
• Prefer IMAGE format posts
• Average post length: 959 characters

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2️⃣ Content Structure

🎣 Hook Types That Work

First line patterns from top-performing posts:

Takeaway: CURIOSITY GAP hooks outperform by 31485% compared to the lowest performer.

🎯 Hook Templates You Can Steal

Curiosity Gap: "I discovered something that changed everything about [topic]. Here's what nobody tells you..."

Emotional: "I almost gave up on [goal]. This is what kept me going..."

Story: "3 years ago, I was [situation]. Then [catalyst happened]..."

How-To: "How to [achieve result] in [timeframe] (without [common pain point])"

Statistic: "[Surprising number]% of [group] fail at [thing]. Here's why..."

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📝 Word Count vs. Engagement

Is there a sweet spot for post length?

Finding: Very Long (350+) posts have the highest median engagement.

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📷 Format Performance

🏆 Best Format: IMAGE with 562 avg engagement

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#️⃣ Hashtag Impact Analysis

Do hashtags actually help? Here's what the data says:

Verdict: 🤷 Hashtags don't matter. Posts with 0 hashtags (81) perform about the same as posts with hashtags (81). Don't stress about them.

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3️⃣ Timing & Frequency

⏰ Best Time to Post (UTC)

Best Hours: 22:00, 12:00, 16:00 UTC

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📅 Best Days to Post

Best Days: Sunday, Wednesday

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📊 Posting Frequency vs. Engagement

Does posting more often lead to better results?

📉 Quality > Quantity: Occasional (<1/week) posters have 4.0x higher engagement rates than Daily (7+/week) posters.

Why? Mega-accounts often post daily, diluting their per-post engagement. Creators who post less frequently tend to put more effort into each post — and the algorithm rewards quality over volume.

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🎯 Timing Verdict

Posting time matters, but only moderately: engagement varies a lot by hour (110% variance) and clusters around clear peaks. Aim for 12:00–16:00 UTC (highest sustained averages) or 22:00 UTC (strong spike), and secondarily 03:00 UTC; avoid low-performing windows like 02:00, 04:00, 07:00, 10:00, and 23:00 UTC. Day-of-week effects are weaker, but Sunday (best) and Wednesday are safer bets than Saturday (lowest).

Variance between best and worst times: 110%

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📈 Engagement Trends Over Time

How has engagement changed month-over-month?

Trend: 📉 Engagement is DOWN 1% over the past 12 months.

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4️⃣ Niche Deep Dive

🎭 Performance by Category (Top 20)

Top Performers:

1. Personal Development - 1,525 avg engagement
2. Startups - 1,075 avg engagement
3. Software Engineering - 782 avg engagement

Highest Viral Rate: Software Engineering (11%)

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5️⃣ The Spicy Insights 🌶️

🎯 Underserved High-Opportunity Topics

Low competition + high engagement = opportunity

How Opportunity Score Works:
Opportunity = (Topic Engagement ÷ Average Engagement) × log(Average Posts Per Category ÷ Topic Posts)
Higher score = high engagement + low competition. A score of 30+ is exceptional.

💡 Example Post Ideas (Steal These)

1. Career Journey — "Everything you know about career journey is wrong. Here's what the data actually shows..."

2. Communication — "I used to think being smart was enough. Then I learned the 3-second rule for every message..."

3. Marketing Automation — "Everything you know about marketing automation is wrong. Here's what the data actually shows..."

Strategy: These topics are underexplored but audience interest is HIGH. Early movers win.

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🚀 What Makes Posts Go Viral

Key Insight: Analysis partially extracted due to response formatting issues.

Viral Patterns Found:

1. Strong narrative hook in the first 1–2 lines - undefined
2. Human story + emotion (specific scene, not a concept) - undefined
3. High specificity (names, numbers, timeframes, constraints) - undefined
4. Timely novelty or “new capability” with clear stakes - undefined
5. Audience-first framing (benefit, dilemma, or transformation) - undefined

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Viral Patterns Identified

1. Strong narrative hook in the first 1–2 lines (50% of viral posts)

   • Example not available

2. Human story + emotion (specific scene, not a concept) (50% of viral posts)

   • Example not available

3. High specificity (names, numbers, timeframes, constraints) (50% of viral posts)

   • Example not available

4. Timely novelty or “new capability” with clear stakes (50% of viral posts)

   • Example not available

5. Audience-first framing (benefit, dilemma, or transformation) (50% of viral posts)

   • Example not available

6. Readable structure (short paragraphs, deliberate pacing) (50% of viral posts)

   • Example not available

7. A distinct POV (not just information) (50% of viral posts)

   • Example not available

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📚 Methodology

Data Collection

• Source: ViralBrain harvested posts database (real LinkedIn data)
• Time Period: 5/16/2018 - 1/22/2026
• Total Posts: 7,796
• Total Creators: 418

Analysis Methods

• Quantitative: SQL aggregations, percentile calculations, correlation analysis
• Qualitative: GPT-4 pattern recognition on post content

Statistical Notes

• Median vs. Average: We use median for most comparisons as it's less affected by outliers
• Minimum Sample Size: 20+ posts required for category-level insights
• Percentiles: P50 = median, P75 = top quartile, P90 = top 10%, P99 = top 1%

Limitations

• Data limited to posts scraped by ViralBrain users
• Engagement metrics are point-in-time snapshots
• Category classifications are AI-generated
• Sample size varies by niche (minimum 20 posts required)

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This report was generated on January 22, 2026 by ViralBrain Analytics.

For questions or feedback, contact the ViralBrain team.