How Does the LinkedIn Algorithm Work in 2026? 130,000 Posts Analyzed

You already know the rules the LinkedIn algorithm supposedly rewards. Post Tuesday morning. Use three to five hashtags. Keep it short. Never put a link in the post. End with a question. Open with something contrarian.

Almost none of it is backed by evidence. The articles cite each other, and when you follow the trail back far enough it usually ends at somebody's blog post from 2019.

So we tested it against 130,000 posts. We can't see inside the algorithm. Nobody outside LinkedIn can. But we can measure what it actually rewarded. Here is everything we found.

Change in reactions, compared with the same creator's other posts

Worth doing

• Attach an image+33%

  Worked for 70% of the creators we tested

• Open with "I", "my" or "we"+20%

  Worked for 69% of creators, in every format

Don't bother

• One or two hashtagsNo change
• "Unpopular opinion…" openersNo change
• Opening with a statisticNo change
• Hitting a target post lengthNo change
• Picking the right day to postNo change
• Three or more hashtags−7%
• Writing at the reader ("you should…")−9%
• Ending with a question−10%
• Opening with a question−15%

How we tested the LinkedIn algorithm

One rule separates this from most LinkedIn "studies", and it is worth thirty seconds.

Say you want to know whether hashtags work. The obvious test is to compare posts that use them against posts that don't.

The problem: the people who use hashtags are not the same people who don't. Maybe they are newer. Maybe they post more. Maybe they have smaller audiences. Whatever you find, you have measured the people, not the hashtags.

So we did it the other way round. We found creators who sometimes use hashtags and sometimes don't, then compared their hashtag posts against their own hashtag-free posts. Same person, same audience, same writing ability. The only thing that changes is the hashtag.

A tactic only counts as working if the same person does better with it than without it.

Full detail on the sample, the exclusions and the statistics is in the methodology at the end.

What actually works on LinkedIn in 2026?

Reactions, compared with the same creator's other posts

Attach an image

+33%

Open in first person

+20%

Use a carousel

+13%

Use video

+11%

No change

Table view

Effect on a creator's own typical reactions

Tactic	Reactions vs their own posts	Change in reactions	Creators tested	Who benefited
Attach an image	1.33×	+33%	1,005	70%
Open in first person	1.20×	+20%	1,790	69%
Use a carousel	1.13×	+13%	178	54%
Use video	1.11×	+11%	504	56%

Do LinkedIn posts with images get more engagement?

The same person's image posts earned 33% more reactions than their own text posts. It worked for 70% of the 1,005 creators we could test this way, in every region and at every audience size.

That makes it the most reliable thing we found, and the least clever. No formula, no hook theory.

What kind of image? We don't know, and we won't pretend otherwise. Our data tells us whether a post had an image, not what was in it. That's the next study.

What we can say is that the lift comes from having one at all. So the practical move is simply to stop publishing naked text. A screenshot, a photo of the thing you're describing, or a plain chart all clear that bar. What does matter is the shape you export it at: the LinkedIn image sizes that survive the mobile crop decide how much feed space you take.

Carousels (+13%) and video (+11%) helped, but less, and only for a little over half the creators who used them. Treat those as worth trying rather than as safe bets.

Two things actively hurt. Posts that were mainly a link share earned 16% less than the same creator's text posts. And polls were the worst thing in the entire study, at 58% down.

Only 34 creators qualified for the poll test, so treat that as a strong hint rather than a settled number. But nothing in our data recommends a poll.

Do first-person LinkedIn posts perform better?

Posts whose first line began with I, my, we or our earned about 20% more reactions than the same creator's other openers. That was tested on 1,790 creators, and 69% of them benefited.

This one survived unusually hard checking. First-person posts weren't more likely to carry an image, and weren't any longer, than everything else. So it isn't some other effect in disguise. It held in every format: text, image and video alike.

What it means in practice: LinkedIn readers reward posts that sound like a person describing something that happened to them. Not a brand. Not a coach. A person.

Same subject, same information. The second version of each simply reports something the writer did.

This is why Flypost drafts from your own material rather than generating filler. The thing that works is the thing only you could have written.

What doesn't work on LinkedIn? Nine tactics that failed

Every number below comes from the same test: each creator measured against their own posts.

Reactions, compared with the same creator's other posts

1–2 hashtags

No change

"Unpopular opinion…" hook

No change

Open with a statistic

No change

3–5 hashtags

−7%

6+ hashtags

−8%

Write at the reader ("you")

−9%

Add a link

−12%

Open with a question

−15%

No change

Table view

The tactics that failed. Effect on a creator's own typical reactions.

Tactic	Reactions vs their own posts	Change in reactions	Creators tested	Who benefited
1–2 hashtags	1.00×	No change	782	49%
"Unpopular opinion…" hook	1.00×	No change	365	48%
Open with a statistic	1.00×	No change	170	51%
3–5 hashtags	0.93×	−7%	959	44%
6+ hashtags	0.92×	−8%	703	43%
Write at the reader ("you")	0.91×	−9%	1,303	38%
Add a link	0.88×	−12%	1,302	40%
Open with a question	0.85×	−15%	446	32%

Do hashtags work on LinkedIn?

One or two hashtags did exactly nothing. Three to five cost about 7%. Six or more cost about 8%.

35% of posts still use them. That is an enormous amount of effort going into something that, at its very best, does nothing at all.

This is also a good example of why the fair test matters. Compared across different people, one or two hashtags looked helpful. Compared within the same person, the effect vanished entirely.

Does LinkedIn penalise posts with links?

Half true, and wildly oversold. Adding a link to an otherwise normal post cost about 12% of reactions, and 40% of creators actually did better with links.

Worth separating two different things here, because they get muddled:

• A post that is mainly a link share, a headline and a URL, does clearly worse: 16% down.
• A normal post that happens to contain a link costs about 12%, and often earns it back.

So it is a trade-off, not a rule. If the click is the point of the post, 12% is a fair price.

Does ending a post with a question get more comments?

This is the most confidently repeated tip on LinkedIn. It is also the one we tested hardest.

The typical post that ends with a question gets exactly zero extra comments.

Across 723 creators, the typical change was no extra comments and about 10% fewer reactions.

To be fair to the tactic: those posts were slightly more likely to gain a comment than lose one. But comments come in ones and twos, and the typical post moved by zero. In that test, a normal post got about 4 comments and 32 reactions, so you are giving up something real for something you probably won't get.

Should you open a LinkedIn post with a question?

15% down, the worst opener we tested. Only 32% of creators benefited. Questions underperform at both ends of a post.

Do "unpopular opinion" hooks work on LinkedIn?

Exactly nothing. 365 creators, 48% benefiting: a coin flip.

Does opening with a statistic get more engagement?

Also exactly nothing. 170 creators, 51% benefiting. Another coin flip.

Should you write "you" in a LinkedIn post?

Openers built on you and your, such as "You need to stop doing this", cost about 9%. Only 38% of creators benefited.

What is the ideal LinkedIn post length?

Length barely matters, and the famous 1,300-character figure appears nowhere in our data.

For text-only posts there was no measurable difference at all: 48% of creators did better long, 52% better short. Across all formats, long posts did earn about 13% more. But that's a fraction of the gap the raw numbers first suggested, and most of that turned out to be long posts carrying images.

If you want an anchor rather than a rule: a typical post in our sample ran to about 1,000 characters. Our full post-length analysis walks through how this one came apart.

What is the best time to post on LinkedIn?

For the same person, posting at the weekend instead of midweek changed engagement by about 2%. That is noise. Of the 759 creators who post on both, 52% did better at the weekend: a coin flip.

What is solid is where everyone crowds. 60% of B2B posts go out on weekdays between 8am and 2pm. Weekends are just 4% of US and UK output.

The tempting conclusion is to post into the empty room at the weekend. Our data says that doesn't work either. The gap closes once you compare a creator against themselves. Post when it suits you.

How do you get more engagement on LinkedIn?

If you change one thing, make it the first item.

1. Write about something you did, in the first person. The strongest opener we measured, and it works in every format.
2. Attach an image. The most reliable single lift in the study. Export it at the right LinkedIn image size so it isn't cropped.
3. Drop the hashtags. One or two are harmless but pointless. Three or more cost you.
4. Skip the poll. The worst-performing format we measured.
5. Put the link in if the click is the point. It costs about 12%. Often that's worth it.
6. Stop engineering questions. Not at the start, not at the end. Ask when you actually want an answer.
7. Write to the length the idea needs. Around 1,000 characters is typical, but there is no target to hit.
8. Post when it suits you. Then spend the time you saved on the post itself.
9. Aim for three to four posts a week if total reach is what you're after. Expect each individual post to earn less.
10. Judge yourself against people your own size. A typical 10,000-follower account gets about 33 reactions a post, not the 143 an influencer gets.

How often should you post on LinkedIn?

Post more often. Each post will get fewer reactions, but your total for the week goes up sharply, and the weekly total is the number that grows an audience.

Reactions per postReactions per week

Under 1.5/week

30

18

1.5–4 per week

20

46

4+ per week

13

57

Each post earns less than half as much. The week earns three times more.

Table view

Posting frequency for creators with similar-sized audiences. Accounts under 10,000 followers.

Group	Reactions per post	Reactions per week
Under 1.5/week	30	18
1.5–4 per week	20	46
4+ per week	13	57

Going from once a week to four times a week cuts each post from 30 reactions to 13. It lifts the week from 18 to 57. You lose per post and win overall, by roughly 3×. The same shape holds at every audience size.

So the trap is judging yourself on the wrong number. Per-post engagement drops when you post more, and it feels like something has gone wrong. Nothing has.

Can you post twice in one day on LinkedIn?

Yes, though the two posts do eat into each other a little. This one was fair-tested, by comparing each creator's posts that followed a short gap against their own posts that followed a long gap.

It runs in both directions. A post that follows another within a day earns about 10% fewer reactions. And the earlier post loses about 8% when another one follows within two days.

Should you vary your LinkedIn post formats?

The advice: mix up your formats to keep the algorithm interested.

No support at all. We compared each creator's posts that changed format from their previous post against those that repeated it. Switching was about 4% worse, across 1,975 creators tested, with only 44% benefiting.

Don't force variety for its own sake. Find what works for you, usually images, and keep doing it.

How many reactions is normal on LinkedIn?

The most common question we get isn't about tactics at all. It's whether your numbers are any good.

The typical B2B post earns 34 reactions and 3 to 4 comments.

5k–10k

27

10k–25k

33

25k–50k

43

50k–100k

78

100k–500k

143

middle half of creators median

The bands overlap: a top-quarter creator with 10,000 followers (59 reactions) beats a bottom-quarter creator with 50,000 (41).

Table view

Reactions per post by follower count

Followers	Lower quarter	Median	Upper quarter	Typical comments
5k–10k	14	27	53	2
10k–25k	15	33	59	3
25k–50k	21	43	90	5
50k–100k	41	78	174	11
100k–500k	61	143	287	17

Three things worth noticing.

Comments are the scarce currency. The typical creator under 25,000 followers gets between one and three comments per post. If one of your posts gets ten, that is genuinely good, and it puts all that "end with a question" advice in perspective.

Your reach per follower falls as you grow. Reactions and comments together come to roughly 0.4% of followers for accounts under 10,000, dropping to about 0.1% above 100,000. A small account works its audience around four times harder than a large one. Those figures are approximate because follower counts were captured early in 2026 and have grown since.

The spread inside every band is enormous. That is what the shaded bars are really showing. The gap between a weak and a strong creator at the same follower count is routinely five to ten times. Your audience size sets a floor, not an outcome.

Methodology

For the sceptics, and for anyone citing this.

Who we looked at. 2,500 English-speaking B2B creators, spread across region (US, UK/CA/AU, EU, rest of world) and follower band (1,000–500,000), with country caps so no single market could dominate. Individuals only, no company pages.

What we collected. All posts captured in one sweep in July 2026, covering July 2025 to July 2026. Around 130,000 posts collected, and 86,725 used in the analysis. Reposts, 12% of everything, are excluded throughout, because the engagement belongs to whoever wrote the original.

What we measured. Reactions and comments only. We never measured impressions. Nobody outside LinkedIn can, and any study claiming otherwise is estimating. Nothing counts until a post is at least 14 days old, because the numbers are still moving before that. We use typical figures (medians) rather than averages throughout, so one viral post can't drag a result upward.

How we tested. Every cause-and-effect claim compares a creator against their own posts, with at least three posts on each side. Creators who tied exactly are excluded from the "who benefited" percentages rather than counted as losses. Sample sizes are stated with each finding and vary because not every creator qualifies for every test.

Timing. Post times come from LinkedIn's internal post IDs rather than the "3 months ago" labels, which are unreliable, then converted to each author's local time. Author-local is a proxy for audience-local, which is a real limitation on any timing claim.

What we're less sure about. Follower counts date from early 2026, so the reach-per-follower figures are mild over-estimates. The poll and carousel findings rest on small samples (34 and 178 creators). Posting frequency is the one finding we couldn't fair-test. The double-posting result covers people who occasionally post twice a day. Habitual double-posters are excluded by the method, and three or more posts a day is untested. We also can't see comment threads, so anything involving replies or first-comment links is outside what this data can answer. Several other tactics didn't produce a result we trusted, and we left them out.

Spot a flaw? We would genuinely like to know. Tell us and we will correct it here.