This isn't a bug. It's structural. And once you understand why, you'll stop treating engagement as the one metric that matters.
Watch the full breakdown of LinkedIn's algorithm changes and audience quality data
The Engagement Mirage: Who's Actually Liking Your Posts?
Most LinkedIn advice boils down to: post consistently, provide value, be helpful. The metric that supposedly validates this? Engagement—likes, comments, shares.
That advice isn't wrong. But in 2025, it's just baseline. Thanks to AI, content has become commoditized. Posting consistently and providing value is no longer the edge.
The problem: engagement is a democratic vote. Buyers and non-buyers both click like, and right now you have no way to tell which is which from your notifications.
The Audience Quality Breakdown
We analyzed 500 recent leads and classified them by ICP (Ideal Customer Profile) fit. Here's what we found about who's actually engaging with LinkedIn content:
- 53% are noise (Score 0-25): Wrong industry, wrong seniority, no real buying intent—just scrollers and likers
- 20% are peers (Score 26-50): Other founders, fellow marketers, people doing the same thing you do—essentially your competition trying to work with your audience
- 16% are near-ICP (Score 51-75): Close, but not quite your buyers
- 11% are genuine ICP (Score 76-100): Actual buyers, people who could purchase from you
That last number—11%—is the one worth sitting with.
The Painful Part: Your Competitors Engage More Than Your Buyers
Here's what really hurts: The peer tier (your competitors on LinkedIn) have the highest average interactions:
- Peers: 5.0 interactions per post, 1.0 comments on average
- Actual ICP: 1.9 interactions per post, 0.3 comments
Translation: The people most likely to buy from you are less engaged. The people who engage most visibly are often the people least likely to buy from you. Your actual buyers are mostly quiet.
But here's the thing: the silence from your ICP isn't rejection. It's due diligence. They're reading. They're watching your profile. They're just not commenting "Great post!"
The Content Type Paradox: Why High Engagement Doesn't Equal High Quality
We analyzed 160 posts with full tracking, categorized by content type: growth, authority, proof, and personal. First, let's look at raw engagement—because this is what fools you.
Raw Engagement Scores by Content Type
- Growth content (tips, reach hacks, how-to lists): 125 average engagement score
- Authority content (opinions, frameworks, industry takes): 44 average engagement score
- Proof content (case studies, results): 23 average engagement score
By engagement alone, growth content wins every time. 3-to-1. Clear winner, right?
But here's what the engagement score isn't showing you:
Audience Quality Score (AQS) Reveals the Real Story
We developed an internal metric called AQS—Audience Quality Score—that rates every post from 0 to 100 based on who actually engages with it.
- Growth posts: For every 100 engagements, only 15 are high-quality leads (score 60+)
- Authority posts: For every 100 engagements, 21 are high-quality leads
That's 40% more buyer-quality engagement per post—for content that gets three times less raw engagement.
Of course growth content attracts more people. It just attracts fewer buyers per 100 engagements.
Why This Happens
The reason becomes obvious once you say it out loud. If I post:
"How to get 10x your LinkedIn reach: 5 things I wish I knew"
"The posting schedule that works"
This type of content—if I don't specifically frame it for my ICP (founders, solopreneurs)—heavily attracts peers. People who sell LinkedIn stuff on LinkedIn. They're not my buyers.
Authority content, on the other hand, filters.
The people who stop and engage with "Here's why I think conventional advice on X is broken" are more likely to be in your world. Not all of them, of course. But more. The data shows this very clearly.
Real-World Case Study: When High Engagement Masks Low Quality
One of our users was posting every day, getting 50-70 likes per post. They felt like it was working—until we introduced the AQS and pulled 90 days of their data.
The reality: 62% of their engaged audience were peers—people trying to sell the same stuff on the platform and hijack their followers, not buyers. Below the surface, they'd built an audience of competitors.
They didn't delete the growth content. They just started mixing in more authority posts after we surfaced this insight.
Three months later:
- Raw engagement dropped
- AQS average went from 35 to 49
- Profile visits from ICP leads tripled
Let that sink in.
LinkedIn's 360 Brew Update: Why Audience Quality Matters More Now
With LinkedIn's latest algorithm updates, all of this becomes more urgent.
LinkedIn now reads your full activity context, not just your latest post. Your last 60-90 days of posts, comments, engagement, who you interact with—it builds what they call a "topic footprint" for your account.
The implication: If your content consistently attracts the wrong people—peers, noise, other founders doing the same thing—LinkedIn's model adapts to that pattern.
Who engages with you becomes part of how LinkedIn classifies you and who it shows your next post to.
You're not just wasting likes on the wrong audience. You're training the algorithm on the wrong audience.
This started last year when they introduced the 360 algorithm, and they've been tightening that loop considerably since.
The Winning Combination: Content Type + Angle
Authority content attracts better audiences—but that's only part of the answer. We also tracked the angle, not just the content type, but how you frame it.
Average AQS by Content Angle
- Data/evidence angle: 55 AQS
- Industry take: 50 AQS
- Story: 46 AQS
- Methodology: 45 AQS
- Mythbusting: 40 AQS
There's a 15-point gap between the best and worst angle. The type of post matters, but how you frame it matters almost as much.
The Data Ceiling: Authority + Evidence
The best combination we've found: Authority content with data/evidence = 57.4 AQS on average.
That's the data ceiling we're seeing across all our users.
This means you're sharing an opinion or framework AND backing it up with real numbers—not made-up stats, but your actual data, client results, platform metrics, something you measured yourself.
This combination does two things at once:
- It signals you're in the field, not just talking about the field
- It gives your buyers something concrete to evaluate—which is exactly what due diligence looks like from the buy side
That's how you build authority and pipeline simultaneously.
Interestingly, growth content with a data/evidence angle comes in at 55.8 AQS. The angle matters almost as much as the content type. Even growth content attracts better audiences when it's grounded in real data.
What This Means for Your Content Strategy
If your results look anything like this data, you don't need to delete your growth content or stop doing it altogether. That's not the lesson.
The lesson: If you're writing authority content to attract buyers and measuring its success by engagement, you will always think it's failing—because it gets three times less engagement than the growth content next to it.
That comparison is misleading. The founders who figured this out stop measuring authority posts against growth posts on raw engagement. They're two different things. One is reach, one is buyer attraction.
You want both. You just need to know which metric applies to which.
The Practical Audit (Even Without Tracking Software)
Look at your last 10 posts. Count:
- Growth angle posts: Tips, reach advice, how-to lists, anything that attracts a broader audience or invites your peers to comment
- Authority angle posts: Opinions backed with data, frameworks from your actual experience, industry positions that might push back on conventional wisdom
If the ratio is something like 7-to-3 in favor of growth (or worse), that's your answer. You're growing an audience, but you might not be growing the right one.
You could track this manually—go through your last three months of posts, count content types, look at who's commenting. That works. We built the AQS system because at scale, you can't do that manually across every post, and it's hard to funnel those insights back into your content strategy.
That's what AI is really good at. But the output is the same: a clear view of whether your posts are reaching buyers or reaching peers.
The Bottom Line: Engagement Isn't a Lie, It's Incomplete Information
Engagement is not a lie. It's just incomplete information.
A post that gets 50 likes and 10 comments from the right 10 people is doing more work than a post that gets 200 likes from people who will never buy.
You can't see that in your notifications. You need to know who's in the room and who's actually engaging.
Most founders are writing for the loudest audience—it's just human bias. We want big numbers. But the buyers are quieter. And they're watching. The content that keeps them watching and nurtures them is not the same content that gets you the most likes.
The metrics you're optimizing for are shaping who shows up.
Right now, for most founders, that metric is likes. And likes are a democratic vote.
Your Action Steps
- Count your last 10 posts: How many are authority angle with real data behind them? If the answer is fewer than 4, that's the ratio to fix.
- Review who's commenting: Are they peers, competitors, or potential buyers?
- Test the authority + data combination: Share an opinion or framework backed by your actual numbers in your next post
- Track audience quality: If you want to see the actual quality breakdown of your own audience, check out Contentin (link in the video description for a free trial)
Coming next week: Commenting strategy—not generic "engage your audience" advice, but specifically which posts to comment on, what to say, and why strategic commenting is one of the highest ROI activities a founder can do on LinkedIn right now. The data is actually pretty surprising.