LinkedIn Reach Is Dropping: Why Your Posts Are Getting Fewer Views – What LinkedIn Says Officially – and How You Can Become Visible Again

If you’ve noticed a significant drop in your LinkedIn reach over the past few months, you’re far from alone. Many users, companies, and marketers report the same trend: despite a consistent strategy, solid content, and an active community, impressions, comments, and interactions have dropped sharply.

So what’s behind these shifts in your LinkedIn metrics?

A closer look shows LinkedIn itself is evolving—both technically and strategically.

The algorithm (the software that decides which posts people see) is becoming smarter, more personalized, and more selective about what it shows as relevant. At the same time, LinkedIn is now openly sharing which factors influence what content is promoted. The platform is shifting away from short, widely appealing posts toward sharing deeper expertise, higher-quality content, and more professional conversations.

In principle, that’s not a bad thing — the platform hasn’t necessarily improved by drifting into the “light entertainment” segment.

Yet for many creators, adapting to these changes presents new obstacles.

Let’s break down the main reasons for these shifts.

Why LinkedIn Reach Is Declining Right Now

More competition — fewer organic slots.

LinkedIn is growing fast: more users, more active creators, more company pages — and more paid placements in the feed. The number of posts increases, but the space in the feed remains the same.

We will see more and more paid content. Not great news.

The effect: Even good posts get less exposure. The algorithm filters harder.

Relevance beats recency.

For a long time, LinkedIn was fairly chronological: New post? Great chance of visibility.

Not anymore.

LinkedIn now prioritizes relevance over recency, reducing visibility for merely recent posts.

This means:

• Older posts can resurface

• New posts go through an initial test phase

• If they don’t perform early, reach drops quickly

  
  

It’s a deliberate platform shift — and it affects everyone who creates and shares content.

Dwell time is a key ranking signal.

LinkedIn confirms: how long people spend on your post strongly affects reach.

This means:

• Scroll-past = negative signal

• Viewed, read, paused = positive signal — even without a like

Posts with strong hooks, clear structure, storytelling, and professional insights outperform shallow, generic motivational content.

Great for readers — more challenging for creators.

Early engagement signals determine success.

The so-called Golden Hour — the first 30 to 90 minutes — is more important than ever.

If your post gets:

• substantial comments

• actual discussion

• profile clicks

• saves

…during that time, your chances of broader distribution rise dramatically.

Old “winning formats” no longer guarantee reach.

What used to work reliably — carousels, generic infographics, short quotes — is no longer a guaranteed hit. The algorithm downgrades patterns associated with low dwell time and low value.

Polls still work if the questions are thoughtful and highly relevant.

What LinkedIn Officially Says About the Algorithm

Compared to Meta, TikTok, or X, LinkedIn is surprisingly transparent — especially from a technical perspective. Three sources matter most:

LinkedIn Engineering Posts on Dwell Time & Feed Optimization

LinkedIn has confirmed multiple times:

• Dwell time is a ranking signal.

• “Silent consumption” (reading without liking) matters

• The feed is filtered through multi-stage ML models.

• Relevance is measured through hundreds of signals, including:

• your past interactions

  • your professional interests

  • your network relationships

  • how closely a post matches your profile and topics

LinkedIn emphasises that demographic factors (like gender or age) are not used for ranking.

LinkedIn Help Centre: How the Feed Chooses What You See

According to LinkedIn:

• The feed prioritizes professionally relevant content.

• Users should see content aligned with their field, interests, and career path.

• The algorithm evaluates both active and passive engagement.

• Content that triggers “meaningful conversations” is preferred.

A clear message:

This is not about entertainment — it’s about professional value.

Sounds good, doesn’t it?

Transparent Communication Around Bias Checks

As public discussions emerged about certain groups receiving less reach, LinkedIn clarified:

• The algorithm is regularly checked for bias.

• Demographic data does not feed into the ranking.

• Any unusual performance gaps are investigated internally.

Meaning:

Reach differences come from content and networks, rarely from user identity.

Of course, this can’t be independently verified since the exact mechanics aren’t public.

Technical Papers: A Deeper Look into How the Feed Works

LinkedIn’s official research papers offer rare insight into how content is processed, evaluated, and distributed.

LiRank (2024)

A large-scale ranking model replacing older heuristic methods.

Key points:

• Uses deep learning to predict relevant content

• Evaluates posts based on user behavior, network structure, text signals, and interest clusters

• The more clearly your topic is defined, the better the system can classify it

A clear positioning now matters more than post frequency.

Personal branding on LinkedIn makes a lot of sense.

LinkedIn’s LLM Retrieval Model (2025)

A new system using modern language models (LLMs) to analyze users and content.

Key points:

• Text from posts, profiles, and comments is semantically analyzed.

• The algorithm understands which content is relevant to which user — even without prior interaction.

• Relevance is based on thematic proximity, not just network connections.

Clear language, thematic focus, and consistent messaging influence reach much more than they used to.

Dwell-Time Optimization Studies

LinkedIn shows:

• Passive user signals can be more meaningful than likes.

• A post that is read but not “liked” can still rank extremely well.

• About 90% of users consume content silently.

A low like count does not automatically mean poor algorithmic performance.

What You Can Do Now: Practical Steps You Can Implement Immediately

Based on official sources, technical insights, and creator analyzes, here are five concrete actions:

1. Specialize in 2–3 core topics

LinkedIn identifies you by what you post consistently.

The clearer your themes, the more likely you are to:

• be considered an expert

• show up in relevant feeds

• be matched to users who care about your content

Random posts are penalized—focus and precision win.

Holiday pics, quotes, group photos from workshops, and other low-value content should be a thing of the past.

2. Write for dwell time

How to increase reading time:

• strong hook

• short paragraphs

• examples, stories, insights

• skimmable formatting

• real substance instead of “breadcrumb posts”

Dwell time relies on writing skill, not luck.

The good news: you can train it.

3. Optimize the Golden Hour

Not with pods — with real relationships.

• Comment on relevant posts daily.

• Maintain a small group of active professional contacts.

• Respond to comments immediately after posting.

• Post at times when your audience is active

LinkedIn rewards real, not artificial, engagement.

4. Create content that sparks conversation

Questions like:

• “What do you think?”

• “What’s your experience?”

…only work when the entire post delivers genuine value.

LinkedIn detects engagement bait — and ignores it.

5. Use document posts & carousels intentionally

They still work, but only if:

• They contain fewer slides.

• They deliver more substance.

• They avoid generic lists.

A high-quality carousel still has huge potential — but low-quality ones are punished quickly.

How the LinkedIn Algorithm Will Evolve

Based on official documentation, research papers, and current platform trends, several directions are clear.

More personalization through AI

LLM-based models will increasingly:

• predict topic preferences

• match posts to users semantically

• build expert communities algorithmically

Content will be shown more selectively.

Relevance will remain, king.

Expect continued focus on:

• less virality

• more professional value

• deeper content quality

• stronger expert positioning

LinkedIn wants to be the anti-TikTok of social platforms — by design.

Passive signals will matter even more.

Reading time, scroll depth, profile clicks, and saves will outweigh likes.

Paid visibility will grow.

Through Thought Leader Ads, Sponsored Content, and Creator Programs, paid reach will become more central.

Organic visibility remains possible, but it now requires higher-quality content and effort.

The Drop in Reach Is Real — but You Can Adapt

The algorithm has changed — absolutely. But not “against creators”. It’s evolving towards more quality, relevance, and expertise.

If you:

• define your core topics

• deliver high-quality, well-structured content

• write for dwell time

• nurture your network

• encourage real conversation

…you will remain visible — and possibly more visible than before.

And yes, paid content will continue to grow on LinkedIn.

Not exactly beautiful — but economically understandable.