Most advice about the LinkedIn algorithm is recycled guesswork. Someone reads a blog post from 2023, adds "updated for 2025" to the title and calls it a day. Then another blogger reads that post, rephrases it with slightly different formatting and publishes "The DEFINITIVE Guide to LinkedIn in 2026." It's a game of telephone where nobody actually checked the numbers.

We took a different approach. We built a dataset of 10,222 LinkedIn posts from 494 active creators. We tracked likes, comments, shares and engagement rates across every post type, length, category and publishing day.

No guessing. No "I heard from someone who knows someone at LinkedIn." Just data.

Here's what we found.

The Algorithm's Core Logic: Test, Measure, Expand

LinkedIn doesn't show your post to all your followers. It never has. But the system has gotten more sophisticated over the past two years, and understanding the mechanics gives you a real edge over creators who are still posting and praying.

When you hit publish, your post goes to a small test audience. Usually around 5-10% of your connections and followers. The algorithm watches what happens next.

If people scroll past it, the post dies quietly. No drama. No notification that says "Sorry, your post was boring." It just fades into the feed graveyard where thousands of posts go every minute.

If people stop scrolling, read the whole thing and engage, the algorithm pushes it wider: second-degree connections, topic feeds, the broader network. Think of it like a series of gates. Each gate only opens if the previous audience responded well enough.

This is fundamentally different from how most people think about posting. They write something, publish it and assume the algorithm either "liked it" or "suppressed it." In reality, the algorithm didn't make any decision at all. Your test audience did. The algorithm just listened to their behavior and responded accordingly.

Pro tip: Your first 100-200 followers matter more than you think. These are the people who form your initial test audience. If they're random connections who accepted your invite out of politeness but have zero interest in your content, your posts will consistently fail the first gate. Be strategic about who's in your network.

The signal that matters most in 2026 isn't likes. It's dwell time.

Dwell Time Is the Primary Quality Signal

Dwell time measures how long someone spends looking at your post. Not just whether they tapped a reaction button, but whether they actually read it. LinkedIn is essentially tracking eyeball-seconds per post, and this metric drives more algorithmic decisions than any other single signal.

LinkedIn started weighting dwell time heavily in late 2023. By 2026 it's the dominant quality signal. The logic is simple: if someone stops scrolling and reads your entire post, the content is probably worth showing to more people. Conversely, if someone sees your post and their thumb keeps moving, that's the clearest "not interested" signal possible.

This explains a counterintuitive finding in our data. Short posts (under 500 characters) get high average likes (376) but a low engagement rate (0.48%). Long posts (2,000-3,000 characters) get fewer average likes (352) but generate 74 comments on average, more than double the short posts.

Short posts get quick reactions. Someone reads it in three seconds, taps a like and moves on. Long posts get actual attention. Someone spends 45 seconds reading, processes the information, then leaves a comment because they have something to say. The algorithm now rewards the second type more.

Pro tip: Dwell time is why "hook + body + CTA" structure works so well on LinkedIn. The hook stops the scroll (buying you the first 2-3 seconds). The body holds attention (generating dwell time). The CTA converts passive readers into active engagers. Every section serves the algorithm, whether you planned it that way or not.

How to Increase Dwell Time Without Writing a Novel

You don't need to write 3,000 characters to generate good dwell time. You need to write something that holds attention for its entire length, whatever that length is. A few techniques that work:

Line breaks. Dense paragraphs are the enemy. Short paragraphs with line breaks between them force the eye to keep tracking down the page, adding seconds to your dwell time.
Open loops. Tease a payoff early ("Here's the one thing that changed everything") and delay the answer. People keep reading because they need the resolution.
Specificity. Vague platitudes are easy to skim. Specific numbers, names and scenarios force people to actually process what they're reading. "We increased conversions by 23% in six weeks" holds attention longer than "We improved our results."
Carousels. This is the dwell time cheat code. Each slide swipe generates additional time-on-post. A 10-slide carousel where someone reads every slide can generate 60-90 seconds of dwell time. That's enormous compared to a text post that gets skimmed in 8 seconds.

Comments Are Weighted 8x More Than Likes

This is the single most important thing to understand about LinkedIn in 2026.

A like is a one-tap action. A comment requires someone to stop, think and write something. LinkedIn treats these actions very differently, and for good reason. If you think about it from LinkedIn's perspective, a comment means a user is spending more time on the platform. A like means they're moving on.

Based on engagement patterns in our dataset and what multiple LinkedIn engineers have confirmed publicly, comments carry roughly 8x the algorithmic weight of a like reaction. Shares sit somewhere in between, roughly 4x a like. Saves (bookmarks) are becoming increasingly important too, though LinkedIn hasn't been as transparent about their exact weight.

Look at what this means in practice. A post with 50 likes and 2 comments is algorithmically weaker than a post with 20 likes and 10 comments. The second post gets pushed to more feeds. It's not even close. Those 10 comments are worth 80 "like-equivalents" in algorithmic terms, plus the 20 actual likes. The first post has 50 + 16 = 66. The second post has 20 + 80 = 100. The algorithm sees the second post as 50% more engaging.

This is why some posts with modest like counts end up reaching tens of thousands of people while posts with flashy like numbers plateau quickly. The algorithm doesn't care how many thumbs you got. It cares how many conversations you started.

Our data backs this up. The categories with the highest engagement rates aren't the ones with the most likes. Software Engineering posts have a 2.57% engagement rate. Social Media Marketing hits 1.34% with an average of 210 comments per post, the most commented category in our dataset. These are topics where practitioners love to argue about best practices, share war stories and correct each other. The comment sections are active, which is exactly what the algorithm wants.

Meanwhile, Personal Development posts get the highest raw likes (1,222 average) but only a 0.39% engagement rate. Lots of passive reactions, fewer actual conversations. Someone reads an inspirational post about never giving up, double-taps the heart reaction and keeps scrolling. The algorithm registers that behavior as shallow engagement.

Pro tip: Want more comments? End your posts with a genuine question that's easy to answer but hard to resist. Not "Thoughts?" (which is the LinkedIn equivalent of a shrug emoji). Something specific like "What's the worst advice you got in your first year?" or "Has anyone else noticed this trend, or is it just my industry?" Give people a prompt they can answer from their own experience without having to think too hard.

The algorithm rewards conversation. Write posts that make people respond, not just react.

The Comment Reply Multiplier

Here's something a lot of creators miss: your own replies to comments count as additional engagement signals. When someone comments on your post and you reply, that's two comments on the post, not one. If you reply to 15 comments, that's 30 comment interactions the algorithm sees.

This creates a virtuous cycle. More comments trigger more distribution. More distribution brings more readers. More readers leave more comments. Your replies add even more engagement signals. The algorithm keeps pushing the post wider.

This is also why the first hour is so critical, which brings us to the next section.

The Golden Hour: Your First 60 Minutes

The initial test audience gets your post right after you publish. What happens in that first 60 minutes determines everything. And I mean everything. Not "sort of influences the outcome." Literally determines whether your post reaches 500 people or 50,000.

If engagement is strong in the first hour, the algorithm moves your post to the next distribution tier. If it's weak, the post flatlines and never recovers. You can't rescue a post that bombed in the first hour. No amount of engagement later in the day will convince the algorithm to give it a second chance. (LinkedIn has hinted at some exceptions for posts that get sudden comment activity hours later, but it's rare enough that you shouldn't count on it.)

This is why timing matters. You don't want to publish when your audience is asleep or in meetings. You also don't want to publish and then disappear for two hours. That first hour is your window to reply to comments, engage with early reactions and signal to the algorithm that there's an active conversation happening.

Pro tip: Prepare 2-3 "conversation starter" replies in advance. When the first comments roll in, don't just say "Thanks!" Ask a follow-up question. Challenge their point gently. Bring in a new angle. Each reply is another comment the algorithm counts, and it keeps the conversation going, which attracts more participants.

Our data shows clear patterns by day of the week:

Tuesday: 0.92% average engagement rate (the best day by a wide margin)
Monday: 0.72%
Thursday: 0.71%
Wednesday: 0.64%
Sunday: 0.55% (but interestingly, highest raw engagement: 377 avg likes, 69 avg comments)
Friday: 0.52%
Saturday: 0.46% (worst day)

Tuesday dominates because the professional audience is active, engaged and not yet burned out from the week. Saturday is dead because people are offline, or at least pretending to be. (We see you scrolling at brunch. We all do it.)

Sunday is interesting. The raw numbers are high but the rate is low. This suggests fewer people are posting on Sunday, so the ones who do post reach a less crowded feed. But the overall audience size is smaller. It's like being the best restaurant on a street where half the shops are closed: less competition, but also fewer people walking by.

For most creators, Tuesday through Thursday is the sweet spot. If you're going to invest extra effort in one post per week, make it your Tuesday post.

What Time of Day Works Best?

The data varies by audience location, but general patterns hold:

7-8 AM in your audience's timezone catches the morning commute scrollers
11 AM-1 PM hits the lunch break crowd
5-6 PM catches the end-of-day check

If your audience is primarily in one timezone, test posting at 7:30 AM on Tuesday and track results for a month. If they're spread across time zones, morning Eastern time tends to perform well since it catches both US morning and European afternoon.

Pro tip: Whatever time you pick, be consistent. The algorithm learns your posting patterns. If you always post at 8 AM Tuesday and your regular readers start expecting it, they'll engage faster, which boosts your golden hour performance. Irregular posting schedules don't give the algorithm (or your audience) any pattern to work with.

External Links Cut Your Reach by ~60%

LinkedIn wants people to stay on LinkedIn. This shouldn't surprise anyone. Every platform that depends on advertising revenue has the same incentive: keep users on the platform where you can show them ads.

Posts with external links get significantly less distribution, roughly 60% less reach based on industry benchmarks and what creators in our dataset consistently report. That's not a minor penalty. That's your post reaching 4,000 people instead of 10,000. The same content, the same quality, just a URL in the body, and your reach gets cut by more than half.

The algorithm detects outbound URLs and actively suppresses them. This isn't subtle. It's one of the most aggressive penalties in the system.

If you need to share a link, put it in the first comment. It's not a perfect workaround (the algorithm may still detect it) but it performs measurably better than embedding links in the post body.

Pro tip: Better yet, stop linking out entirely. If you're sharing an article, summarize the key points in your post. If you're promoting a tool, describe what it does and tell people to DM you. If you're referencing research, quote the stat directly. The most successful creators on LinkedIn deliver all the value inside the post itself. The link is for the people who want to go deeper, and you can always say "link in comments" or "DM me for the link."

The First-Comment Link Trick: How It Actually Works

When you put a link in the first comment instead of the post body, the algorithm's URL detector has less reason to suppress the post. Your main post stays "clean" in the algorithm's eyes. Your followers still see the comment with the link, especially if you mention "link in comments" in the post itself.

However, this trick has gotten less effective over time as LinkedIn's detection improved. Some creators report that even first-comment links now result in slight reach penalties, though nowhere near the 60% hit you get from putting the URL in the post body.

The nuclear option (and the most effective one): don't link at all. Just deliver the value and let interested people come to you. This is counterintuitive if you're used to driving traffic to a website, but it's how the platform works now.

Engagement Bait Gets Detected and Penalized

"Like if you agree. Comment YES if you want this."

If you've used these phrases in the last year, I have some bad news. Actually, if you're still using them in 2026, the bad news is that you're roughly two years behind on LinkedIn strategy. But better late than never.

LinkedIn's spam detection has improved substantially. Posts that use obvious engagement bait patterns now get flagged and suppressed. The algorithm looks for:

Generic call-to-action phrases designed to inflate comment counts
"Agree?" or "Thoughts?" tacked onto the end of every post
Comment-for-content mechanics used excessively (the "Comment PLAYBOOK and I'll DM it to you" move)
Repost chains and tag-a-friend patterns
Identical emoji reactions flooding in from the same group of people within minutes (hello, engagement pods)

The system wants genuine engagement. A comment that says "Great post!" carries less weight than a comment that adds perspective or asks a follow-up question. LinkedIn can distinguish between the two. It's looking at comment length, comment uniqueness (are 15 people all saying the same generic phrase?) and whether the commenter actually engages with other content or just shows up to support their pod members.

Pro tip: If you want to invite engagement, do it with substance. Instead of "Agree?", try "The counterargument here is [X], what's your take?" Instead of "Comment YES for the guide", try "I wrote a full breakdown of this process. Drop a comment about which step you'd want more detail on and I'll share it." The second version generates genuine engagement. The first version gets flagged as spam.

The Engagement Pod Problem

Let's talk about pods for a second, because they're still surprisingly common. An engagement pod is a group of people (usually 10-50) who agree to like and comment on each other's posts immediately after publishing.

The theory: if 20 people like and comment in the first 5 minutes, the algorithm thinks the post is hot and pushes it wider.

The reality in 2026: LinkedIn's detection is good enough to spot the pattern. The same 20 accounts engaging with each other's content within minutes, every single day, with generic comments? That's not organic behavior. LinkedIn knows it. Accounts that participate in pods now face reduced reach, and in some cases, shadow bans where the creator has no idea their content has been suppressed.

If your "community" engagement seems weirdly consistent (always the same 15 people, always within the first 10 minutes), you might be in an unintentional pod. Consider diversifying your engagement sources.

Images Get 87% Higher Engagement Than Text

This is one of the clearest signals in our entire dataset. No ambiguity, no "it depends." Images just win.

Image posts: 0.93% average engagement rate, 468 average likes, 85 average comments
Text posts: 0.50% average engagement rate, 191 average likes, 33 average comments

Image posts outperform text on every metric. The engagement rate is 87% higher. Average likes are 2.45x higher. Comments are 2.6x higher.

Images also go viral at nearly twice the rate. Out of 10,222 posts, 142 image posts went viral compared to 79 text posts. Text had 1.8x more total posts in our dataset, yet images produced almost twice as many viral hits. If we normalize for volume, images go viral at roughly 3.2x the rate of text.

Why? Images stop the scroll. They increase dwell time. They give people something visual to react to. And carousels (which LinkedIn categorizes as document/image posts) are particularly strong because people swipe through multiple slides, generating massive dwell time signals.

What Counts as an "Image Post"?

You don't need to be a graphic designer. Here's what qualifies:

Screenshots of data, results or interesting content
Simple charts and graphs (even from Excel or Google Sheets)
Carousels (PDF uploads that appear as swipeable slides)
Photos of you at events, at work, with your team
Infographics with a framework or process laid out visually
Memes (yes, professional memes do well on LinkedIn, which is a sentence that would have sounded insane in 2019)

The bar for "image quality" on LinkedIn is surprisingly low. A clean screenshot with a red circle around something interesting will outperform a beautifully designed text post. The visual element is what matters, not the production value.

Pro tip: If you're not sure whether to add an image, add an image. The 87% engagement advantage means that even a mediocre image post tends to outperform a good text post. The exception is personal stories and hot takes, which sometimes work better as raw text because the format signals authenticity.

The Sweet Spot: 500-1,200 Characters

Post length affects performance in predictable ways, and knowing the sweet spot is one of the easiest optimizations you can make.

Length	Engagement Rate	Avg Likes	Avg Comments
Under 500 chars	0.48%	376	35
500-1,200 chars	0.83%	-	-
1,200-2,000 chars	0.77%	222	-
2,000-3,000 chars	0.66%	352	74

The 500-1,200 character range hits the highest engagement rate at 0.83%. It's long enough to deliver real value but short enough that people actually finish reading it. This is roughly 80-200 words, or about the length of a decent email.

Very long posts (2,000-3,000 chars) are interesting. They have a lower engagement rate but generate the most comments. If your goal is sparking conversation rather than maximizing rate, longer works. These tend to be the "I have a strong opinion and here's my reasoning" posts that invite debate.

Short posts (under 500) get high likes but low engagement rate and fewer comments. They're easy to like, hard to discuss. Think of them as the LinkedIn equivalent of a mic drop: fun, but there's nowhere for the conversation to go.

Pro tip: Check your character count before publishing. Most writing apps show this. On LinkedIn's native editor, you can paste into a character counter tool first. If you're at 400 characters, see if you can add one more supporting detail or example. If you're at 1,500, see what you can trim. The difference between 0.48% and 0.83% engagement rate is significant, and it's often just 100-200 characters of editing.

Why Polls Are Dead

Polls used to work. They don't anymore. If you're still posting them, this section is going to sting a little.

Our data is brutal: poll posts average 0.07% engagement rate. That's not a typo. Compare that to images at 0.93% or even text at 0.50%. Polls perform at roughly one-thirteenth the rate of images.

Average likes on polls: 25. Average comments: 23. These numbers are tiny. For context, the median text post (the lowest-performing non-poll format) still gets 40 likes and 8 comments. Polls can't even beat the median.

LinkedIn likely deprioritized polls after they became overused in 2022-2023. Every second post was a poll asking something pointless. "What's more important for success: A) Hard work B) Smart work C) Both D) Coffee." Groundbreaking stuff. The platform got flooded with low-effort polls that generated surface-level engagement (someone taps an option in 0.5 seconds) and zero actual conversation.

The algorithm adjusted. And it adjusted hard.

Pro tip: If you have a poll idea, turn it into a text post instead. "I asked my network what's more important, X or Y. Here's what I think, and why most people get it wrong." Same premise, but now you're creating dwell time, inviting comments and giving the algorithm something to work with. A question posed as a text post will outperform the same question as a poll by 7x or more, based on the engagement rate difference.

Creator Mode and Newsletters

LinkedIn's creator mode (now largely rolled into the default profile experience) affects distribution in a few ways:

Your posts can reach people who follow you but aren't connections
Your profile emphasizes content over the traditional resume layout
You can add topic hashtags to your profile

The practical impact of creator mode is modest for most people. It's not going to transform your reach overnight. But it does remove one friction point: the connection vs. follower distinction. Without creator mode, people need to connect with you (which you can decline) to see your posts reliably. With it, they can follow you like they'd follow a publication. This matters once you cross roughly 5,000 followers and start attracting people outside your direct network.

Newsletters: The Algorithm Bypass Nobody Talks About

Newsletters are a separate distribution channel entirely. When someone subscribes to your newsletter, they get email and in-app notifications. This bypasses the algorithmic feed completely, giving you a direct line to subscribers.

Read that again. Bypasses the algorithm completely. In a world where everyone is complaining about reach drops, newsletters give you a channel that the algorithm can't throttle.

For creators who publish consistently, the newsletter feature is one of the strongest tools available. It converts algorithmic reach into owned audience. Every newsletter subscriber is someone who will see your content regardless of what LinkedIn's algorithm decides to do next month, next quarter or next year.

Pro tip: Start a newsletter even if you think you don't have enough followers. LinkedIn sends a notification to your entire network when you publish your first edition. That's free distribution that doesn't go through the normal algorithmic filter. Some creators report getting 500-2,000 subscribers from that initial notification alone. It's one of the few "free reach" mechanics left on the platform.

What an Ex-LinkedIn Employee Actually Said

One of the most engaged posts in our dataset came from a former LinkedIn employee explaining why impressions dropped across the platform. That post got 2,144 likes and 688 comments, putting it in the top 1% on both metrics.

The post confirmed what many creators suspected: LinkedIn intentionally reduced reach for certain content patterns while boosting "professional knowledge sharing." The algorithm shifted from rewarding popularity to rewarding expertise. In other words, LinkedIn doesn't want to be Instagram. They want to be the place where professionals share actual professional knowledge, not the place where people post sunrise photos with captions about hustle culture.

(Though let's be honest, there's still plenty of hustle-culture sunrise content. The algorithm just doesn't reward it like it used to.)

This aligns with everything in our data. Categories tied to specific professional knowledge (Software Engineering at 2.57% engagement, Sales at 1.01%) outperform generic motivational content on engagement rate, even though motivational posts sometimes get more raw likes. The algorithm is deliberately boosting the professional stuff and quietly suppressing the generic stuff.

Pro tip: This is good news if you have genuine expertise. You don't need to be a celebrity or have a huge following. You need to know something specific and share it in a way that other professionals find useful. The algorithm is literally built to amplify that kind of content right now. If you've ever felt like "I'm not interesting enough for LinkedIn," the data says you're exactly what the platform wants, as long as you share real knowledge instead of recycled platitudes.

Personal Stories Still Win on Raw Numbers

Despite the algorithm's push toward professional expertise, personal stories consistently generate the biggest raw engagement numbers. There's a tension here, and understanding it is key to a smart content strategy.

Personal Development posts in our dataset average 1,222 likes per post. The highest of any category. Leadership content averages 710 likes. Career Advice hits 588.

People respond to human stories. A founder talking about their family, a career pivot story, a vulnerable moment about failure. These posts trigger emotional reactions that drive massive like counts. There's something about reading a genuinely personal story on LinkedIn, a platform known for corporate jargon and humble-bragging, that makes it feel extra authentic. Like finding a handwritten note in a pile of junk mail.

But remember: high likes don't always mean high engagement rate. Personal Development has a 0.39% engagement rate despite those huge like numbers. The audience reacts but doesn't always comment. They feel moved, they tap the heart, they scroll on. Lovely sentiment, but the algorithm wants more than sentiment.

The strongest approach combines personal narrative with professional insight. Tell a story, then connect it to something actionable. You get the emotional likes and the thoughtful comments. "I almost got fired at my first startup. Here's what that taught me about giving feedback to executives" works better than just "I almost got fired at my first startup" because it gives people a reason to comment with their own experiences.

Pro tip: The 70/20/10 content split works well for most creators. 70% professional insight and educational content (what the algorithm favors). 20% personal stories (what gets the big numbers). 10% hot takes and opinions (what drives comments). This balance feeds the algorithm's preference for professional content while keeping your profile human and relatable.

Only 2.16% of Posts Go Viral

Here's the reality check that every LinkedIn creator needs to read and then probably read again.

Out of 10,222 posts in our dataset, only 221 went viral. That's 2.16%.

If you post once a week, you might get one viral post every 10 months. Statistically, you need about 46 posts for one to break through. That means roughly 46 weeks of posting (almost a year) before math says you'll get one viral hit.

And even that's an average. Some creators post 100 times before going viral. Some get lucky on post number 5. The distribution is random in a way that feels deeply unfair when you're the person who just posted their 47th post with no breakout.

This means the other 97.84% of your posts need to do their job without going viral. They need to build credibility, start conversations, stay visible to your network and establish you as someone worth following. These "normal" posts are your actual content strategy. The viral hit, if it comes, is a bonus, not the plan.

Pro tip: The creators who obsess over going viral tend to produce worse content, not better. They start optimizing for shock value, emotional manipulation and clickbait hooks instead of actual substance. The algorithm has gotten smart enough to penalize that approach. Ironically, the best way to eventually go viral is to consistently post high-quality content that builds a genuinely engaged audience. Those audiences share your stuff because it's actually good, not because you tricked them into reacting.

The creators who win on LinkedIn aren't the ones chasing viral moments. They're the ones who post consistently, optimize for comments over likes and treat every post as a chance to deepen relationships with their audience.

The algorithm rewards that behavior over time. Consistent engagement signals tell LinkedIn you're a valuable creator, which gradually increases your baseline distribution. Your "floor" rises. Even your worst posts start performing better because the algorithm trusts you to produce content worth distributing.

What This Means for Your Strategy

The LinkedIn algorithm in 2026 isn't mysterious. It's complex, sure, but the signals are clear:

Write for dwell time. Give people a reason to read the whole post. Use hooks, open loops, specific details and formatting that guides the eye down the page.
Optimize for comments. Ask genuine questions. Share opinions people want to debate. Leave intentional gaps in your argument that invite others to fill in with their experience.
Use images and carousels. The 87% engagement advantage is too large to ignore. Even a simple screenshot outperforms a well-crafted text post, on average.
Stay in the 500-1,200 character range for the best engagement rate, or go long (2,000+) if you want deep conversation. Avoid the no-man's land of under-500 characters unless you have a genuinely punchy one-liner.
Post Tuesday through Thursday. Especially Tuesday. The engagement rate difference between Tuesday and Saturday is 2x. That's free performance you're leaving on the table if you're posting on weekends.
Kill the external links. Keep people on the platform. If you must share a URL, put it in the first comment and mention it in the post. Or better yet, just deliver all the value right there in the post.
Skip the polls. They're done. Turn poll ideas into text posts instead.
Be consistent. One viral post won't build your presence. 46 solid ones might. The algorithm rewards creators who show up regularly with content that generates real engagement.
Reply to comments in the first hour. Your replies count as additional engagement signals. They also keep the conversation alive, which triggers wider distribution.
Start a newsletter. It's the only major distribution channel on LinkedIn that bypasses the algorithm entirely.

The algorithm isn't trying to suppress your content. It's trying to surface content that keeps professionals on the platform longer. Give it what it wants: posts that make people stop, read and respond.

That's it. No secret hacks. No magic formulas. Just an understanding of what the machine is actually measuring and a commitment to producing content that scores well on those measurements. The creators who understand this will keep pulling further ahead. The ones still posting "Comment YES for my free guide" on a Saturday afternoon will keep wondering why their reach dropped.

The data in this article comes from ViralBrain's analysis of 10,222 LinkedIn posts across 494 creators. If you want to see how your own posts compare to these benchmarks, ViralBrain tracks your performance and shows you exactly where you stand.