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Algorithme & stratégie LinkedIn 18 min read

The LinkedIn Comment Strategy That Actually Grows Profile Views

| By Patrick de Carvalho

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On a LinkedIn post, a like costs half a second. A comment of 15 words or more costs something real: reading the post, forming a view, writing it down before you move on. Richard van der Blom's Algorithm InSights Report 2025, built from 1.8 million posts across more than 60 countries, found that LinkedIn's ranking system weighs that longer comment 2.5 times heavier than a short one. I have been building a version of this routine since April 2004, back when the platform still called the whole exercise "networking." What changed in 2026 is not the logic. It is the size of the model reading your comment, and how bluntly LinkedIn now penalizes the ones nobody actually wrote. This piece covers what the ranking system rewards, a five-step routine I run myself, and a number I am going to correct rather than repeat: the claim that commenting enough triples your profile views.

In short: LinkedIn's ranking system, built on the 150-billion-parameter 360Brew model, weighs a comment of 15 words or more 2.5 times heavier than a short one (van der Blom, Algorithm InSights Report 2025). Botdog measured a 55% rise in profile views from 5 to 10 strategic comments a day sustained over a month, and Buffer found that replying to comments on your own post lifts that post's engagement by 30%. Fifteen comments a day is the cadence I run personally, not a documented multiplier. No published study measures a tripling of profile views at that volume, and this piece says so directly rather than repeating a number nobody sourced.

What LinkedIn's ranking system actually rewards when you comment

LinkedIn's feed has run on language-model ranking since late 2024, starting with 360Brew, a 150-billion-parameter foundation model built by the platform's Foundation AI Technologies team and described in a research paper published in January 2025. On March 12, 2026, LinkedIn's engineering team published the fullest public account yet of where that work led, in a post titled "Engineering the next generation of LinkedIn's Feed," written by Hristo Danchev: an LLM-based dual encoder that reads the meaning of a profile and its history to pull a pool of candidate posts, then a transformer-based Generative Recommender that ranks them. The core idea across both systems: instead of scoring a post on clicks and account size, the model reads the text against a profile's interaction history, the way an editor reads a submission rather than the way a spreadsheet counts clicks.

That shift has a cost, and it is measured. AuthoredUp studied more than three million LinkedIn posts between mid-2024 and mid-2025 and found median reach down 47%, with 98% of the accounts in the sample seeing a decline. Van der Blom's own report lands close to that figure from a different angle: views down 50% year over year, engagement down 25%, follower growth down 59%. Reach is not disappearing. It is being redirected toward content the model reads as substantive, and a well-formed comment reads as substantive to a system trained to read.

This is why the 2.5x figure for long comments matters more than it looks. It is not a bonus for typing more. It is a proxy for the one thing a language model can actually detect in a sentence: whether it carries a specific claim or just fills space. "Great post!" carries nothing to parse. "We tried this in Q1 and the reply rate dropped after week three" carries a claim, a timeframe and an outcome, three things 360Brew's training data taught it to weigh.

Three things a comment does for your visibility, and only three

Commenting is not a favor to the person who posted. It produces three measurable effects on your own visibility, and no others worth planning around.

You appear in front of the original poster's audience

Your name, headline and comment become visible to anyone reading that post. On a post that reaches 5,000 people, a comment placed among the first replies puts your name in front of a slice of that audience who had never seen you before, at zero distribution cost to you.

The system treats your comment as a subscription signal

Commenting on someone's post measurably raises the odds that LinkedIn will show you their next one. That creates a loop: you comment, you see more of that person's content, you comment again, and your name accumulates inside a specific topical community rather than scattering across the feed at random.

Profile views move as a side effect, not a direct lever

Nobody clicks a comment and gets redirected to your profile. What happens is slower: a reader who found your comment useful clicks your name out of curiosity, reads your headline, and either moves on or looks further. Profile views are the visible trace of a chain that starts with a comment and depends on everything after it, including whether your profile gives that visitor a reason to stay.

What the profile-view data says, and where it stops

Here is what is actually documented. Botdog, a Los Angeles-based LinkedIn tool founded in 2024, measured that leaving 5 to 10 strategic comments a day, sustained over a month, correlates with a 55% rise in profile views and 20% more reach on the commenter's own posts. That is a real, sourced, replicable-sounding number, and it sits at less than half the volume this article's title references.

Fifteen comments a day is the cadence I have settled on for myself: two blocks of roughly ten minutes, enough to stay present across a working list of accounts without it eating the morning. I recommend it because it fits inside a founder's actual calendar, not because a study measured its exact multiplier on profile views. I looked for one while writing this piece and did not find it. What exists at higher volumes is directional, not measured: Salesforge's 2026 commentary on founder engagement notes that 10 to 20 strategic comments a day gives a "noticeable edge," without attaching a profile-view figure to that range at all.

So the honest statement is this. A cadence of 5 to 10 comments a day, held for a month, is associated with roughly a 50% lift in profile views, on Botdog's numbers. Above that volume, the trend almost certainly continues, because more well-placed comments mean more exposure events, and the mechanism does not change with the number. But "almost certainly continues" is reasoning, not a citation, and a tripling of profile views specifically at 15 comments a day is a claim I cannot source to a controlled study. Treat 15 a day as a workable target volume for a busy founder, not as a number backed by a multiplier anyone has measured.

The All In Engagement Routine: a five-step framework

This is the structure I run, built around five decisions: who you comment on, when, how, how fast you close the loop, and what you check weekly.

Step 1: Build a list of 20 to 30 accounts

The accounts you comment on determine the audience you reach. Split the list into three groups: 10 clients or prospects who post regularly and whose feed you want to stay inside, 10 recognized voices in your field whose posts draw real conversation, and 5 to 10 peers at a comparable stage where reciprocal commenting builds an actual relationship, not just reach. LinkedIn's native list feature, live since 2024, is enough to track them; a spreadsheet with name, profile URL and posting frequency works just as well.

Step 2: Set a fixed cadence, not a target count

Two ten-minute sessions beat one twenty-minute scroll. A morning block, roughly 7:30 to 8:30, catches posts inside the 30- to 60-minute window when 360Brew is still deciding how far to distribute them, the window where a comment carries the most weight. An evening block, 6 to 7 p.m., catches posts from earlier in the day that are still drawing engagement. Comments that arrive 24 to 72 hours after publication and still add something perform disproportionately well, because a model reading for durable value treats that kind of late engagement as a signal the content held up.

Step 3: Structure each comment with IEQ

A comment worth 2.5x weight rarely happens by accident. IEQ stands for Insight, Experience, Question, three components you rotate rather than force into every comment. Insight is an observation or a missing angle on what the post said. Experience is a line from your own practice: what actually happened when you tried this. Question is an open prompt that invites the author to respond, which is what turns a single comment into a thread. You do not need all three every time. An insight paired with a question works; an experience on its own works. The one rule that does not bend: clear the 15-word threshold and say something a reader could not have guessed before reading it.

Step 4: Reply to your own comments inside 15 minutes

The routine runs both directions. Buffer's data scientist Julian Winternheimer analyzed 72,000 LinkedIn posts across roughly 25,000 accounts and found that replying to comments on your own post raises that post's overall engagement by 30%, with 83% of the accounts in the sample showing a positive effect once compared against themselves over time. The faster the reply, the stronger the signal: a response inside the first 15 minutes lands while the model is still in its evaluation window for that post. Turn on mobile notifications for your own posts and answer with something worth reading, not a one-word thank you.

Step 5: Track three numbers, weekly

Profile views is the headline metric: watch the weekly trend in your LinkedIn dashboard rather than any single day. Incoming connection requests tell you whether your comments are creating curiosity, and worth noting who is sending them: prospects, peers, recruiters. Search appearances, the count LinkedIn shows you directly, correlate with how visible your activity has made you across the platform. Revisit your account list every two weeks: drop accounts that have gone quiet, add the ones you discovered through your own comment threads.

Why LinkedIn is now suppressing generic and automated comments

On May 20, 2026, LinkedIn announced ranking changes aimed squarely at what it calls AI slop, across posts and comments alike. Laura Lorenzetti, VP of Product, said the target is content that "lacks the authenticity and originality," and the company drew an explicit line: AI-assisted writing stays welcome when it carries original perspective or opens real discussion, while fully automated output built to summarize or pad gets suppressed, kept from spreading past the poster's immediate network. One detail is worth pausing on. Among the formulaic patterns LinkedIn's own engineering and editorial teams flagged is the "it's not X, it's Y" construction, the same throwaway rhetorical move newsroom style guides have been cutting for years, now called out by a platform's ranking system rather than an editor's red pen.

That policy sits alongside the "Seems like AI slop" reporting button LinkedIn shipped on July 30, 2026, which I examined in detail in a separate piece on what that button actually measures. The two moves are related but distinct: May's update reshapes what the ranking system amplifies, July's button lets any member flag a specific post or comment by hand. Louise Brogan, a London-based B2B content marketing consultant, reports the same pattern from the practitioner's side: comments carrying real value, past roughly 10 words, now draw noticeably more algorithmic weight, while generic replies and engagement bait such as "Comment YES if you agree" actively hurt the poster rather than helping.

The takeaway for a comment routine is simple and it does not require gaming anything. A comment built on the IEQ structure, grounded in something you actually know, was never going to be classified as slop in the first place. The suppression targets emptiness, not effort, and effort is what this whole routine already asks for.

Five mistakes that quietly kill a comment strategy

Commenting on autopilot. "Great post, thanks for sharing" is now read as engagement noise rather than engagement. It costs you the time without the 2.5x weight and, past May 2026, risks classification as low-value output.

Only commenting on large accounts. A post that already has 80 comments buries yours. A post with five comments gets read by its author, and a reply from that author is far more likely, which is where the real distribution happens.

Going silent when someone replies to you. Every additional exchange inside a thread re-triggers distribution for that post. Dropping the thread after one comment leaves value on the table you already paid to generate.

Commenting without a topical center of gravity. If your comments jump from logistics to marketing to sports without pattern, the model has nothing consistent to associate with your name. Keep roughly 80% of your activity inside your actual domain.

Skipping weekends. Saturday and Sunday posts draw fewer comments, which means less competition for visibility in the same slot. Two or three well-placed weekend comments can outperform a weekday's worth of effort.

Matching the cadence to your actual calendar

Fifteen comments a day is not the only workable number. Match the volume to the time you actually have, and expect the documented range at the lower end rather than an unverified multiplier at the top.

Profile Comments/day Time/day Documented or reasoned outcome
Time-constrained founder 5-7 10 min Close to Botdog's documented 55% rise in profile views at 5-10/day
Consistent operator 10-15 20 min Above the documented range; directionally positive, not independently measured
Launch-phase founder 20-30 30-40 min Undocumented at this volume; Salesforge notes a "noticeable edge" without a figure

The point of diminishing returns sits somewhere past 20 to 25 comments a day. Beyond that, comments start to read as mechanical even when a human wrote every one of them, and LinkedIn's own May 2026 policy gives the system explicit license to treat high-volume, low-substance activity as suppressible.

What a comment strategy can realistically do for pipeline

The honest answer to whether commenting generates business is: it moves the first step, and the rest of the chain has to hold up on its own. Buffer's fixed-effects analysis of 72,000 posts is the closest thing to controlled evidence in this piece, and it measures a 30% lift in engagement from replying to comments, not a revenue outcome. Van der Blom's report measures reach and distribution, not deals closed. I did not find a controlled, named case study connecting a specific comment cadence to a specific pipeline number that I would put my name behind, and I am not going to manufacture one to make this section land better.

What I can tell you from 26 years of doing this by hand: the mechanism is visibility, then credibility, then a decision by someone else to act on it. A comment puts your name in front of people who did not know you. A pattern of specific, well-sourced comments over weeks builds more credibility than a single well-produced post, because it shows up repeatedly rather than once. The prospect who has read six of your comments over a month clicks through to your profile already halfway convinced, and that is where a comment strategy hands off to a profile that has to close the rest of the distance on its own. If the profile does not carry a clear reason to reach out, the visibility a comment routine buys you gets spent on nothing.

What I don't know

I don't know the exact profile-view multiplier at 15 comments a day, and I said so above rather than rounding the number I use myself into a documented finding. I don't know how long 360Brew's evaluation window actually lasts down to the minute; sources describe it as roughly 30 to 60 minutes, and LinkedIn has not published an exact figure.

I don't know LinkedIn's false-positive rate on its May 2026 AI-slop suppression system for comments specifically, and neither does anyone outside the company, as far as I have found. I don't know whether the 47% reach decline AuthoredUp measured between mid-2024 and mid-2025 has stabilized, worsened or reversed since 360Brew's March 2026 update; no follow-up study has crossed my desk as of this writing. If one does, it will be covered in the All In newsletter.

FAQ

Does commenting on LinkedIn actually triple your profile views?

No published study confirms that claim at any comment volume. The documented figure comes from Botdog: 5 to 10 strategic comments a day, sustained over a month, correlate with a 55% rise in profile views and 20% more reach on the commenter's own posts. Higher volumes plausibly extend the trend, but no controlled study measures a tripling.

How long does a LinkedIn comment need to be to count?

Van der Blom's Algorithm InSights Report 2025 found that comments of 15 words or more carry 2.5 times the algorithmic weight of shorter ones. In practice, the strongest comments run 30 to 80 words: long enough to state a real claim, short enough to be read in full inside a scrolling feed.

How many LinkedIn comments a day is too many?

Diminishing returns start somewhere past 20 to 25 comments a day. Past that point, comments begin to read as mechanical, and LinkedIn's May 2026 policy against low-substance, high-volume activity gives the ranking system explicit grounds to suppress the pattern, whether or not each comment was typed by hand.

Do AI-generated comments still work on LinkedIn?

LinkedIn's May 20, 2026 policy update distinguishes AI-assisted writing, which stays welcome when it carries original perspective, from fully automated comments posted without human review, which get suppressed. A comment built on real experience and a specific claim was never at risk under that policy, regardless of what tool helped write it.

What is 360Brew and why does it matter for a comment strategy?

360Brew is LinkedIn's 150-billion-parameter ranking model, live since late 2024 and detailed further in the company's engineering blog in March 2026. It reads posts and comments for substance rather than scoring surface metrics like length or hashtags, which is why a specific, well-formed comment now outperforms a generic one by a wide and measured margin.

Should I reply to every comment I get on my own posts?

Buffer's analysis of 72,000 posts found that replying to comments lifts a post's overall engagement by 30%, with the strongest effect when the reply lands within the first 15 minutes. Replying with a substantive answer, not a one-word thanks, is what produces that effect.

Sources

  1. Richard van der Blom, "Algorithm InSights Report 2025," LinkedIn, 2025-2026: analysis of 1.8 million LinkedIn posts across more than 60 countries.
  2. Hristo Danchev, "Engineering the next generation of LinkedIn's Feed," LinkedIn Engineering Blog, 03/12/2026: dual-encoder retrieval, Generative Recommender ranking, 1.3 billion members.
  3. AuthoredUp, "LinkedIn 360Brew: What Actually Changed," 2026: reach study of more than 3 million LinkedIn posts, mid-2024 to mid-2025, median reach down 47%, 98% of sampled accounts in decline.
  4. Julian Winternheimer (Buffer), "Replying to Your Comments on LinkedIn Boosts Engagement by 30%," 2025: 72,000 posts, roughly 25,000 accounts, fixed-effects analysis.
  5. Botdog, "LinkedIn Algorithm 2025: Complete Guide to Mastering LinkedIn Changes," 2025: 5 to 10 comments a day, 55% profile-view increase, 20% more reach.
  6. Louise Brogan, "LinkedIn Comment Strategy 2025: The Ultimate Guide to Visibility and Engagement," 2025: comment length weighting, deprioritization of generic and AI-generated comments.
  7. Engadget, "LinkedIn doesn't want your AI slop anymore," 05/20/2026: Laura Lorenzetti quote, AI-assisted vs. fully automated distinction, "it's not X, it's Y" flagged pattern.
  8. TechCrunch, "LinkedIn adds a button to report AI-generated slop," 07/30/2026: context for the "Seems like AI slop" reporting button, covered separately in this analysis.
  9. Salesforge, "5 LinkedIn Commenting Strategies That Generate Pipeline in 2026," 2026: directional note on 10 to 20 comments a day, no attached profile-view figure.

All In: fifteen minutes a day that put your name in rooms you are not in

A comment strategy is not a publishing shortcut. It is distribution you earn one specific, sourced sentence at a time, and the data behind it is worth reading before you copy someone else's number.

All In is the B2B media that decodes LinkedIn, expert blog, weekly podcast and newsletter for SME leaders and sales directors who want to turn LinkedIn into measurable growth. An original creation by Patrick de Carvalho, on LinkedIn since 2004. Motto: "I Never Lose."

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