The best day and time to post on LinkedIn is not a number someone else can give you, it is the one your own analytics can prove.

What is the best day and time to post on LinkedIn?

There is no hour that works for everyone, so the best day and time to post on LinkedIn is the one you can show in your own analytics. Every published timetable was measured on somebody else's followers, in somebody else's time zones, reading somebody else's posts.

That is an uncomfortable answer, because the question sounds like it should have a number attached. It does not. What it has instead is a method, and the method is cheap: four weeks of deliberate posting and a table you fill in yourself.

This guide explains why the published studies contradict each other, what LinkedIn itself says about how the feed ranks content, how time zones break a single posting hour, and how to run the test. It ends with the things that move results more than the clock ever will.

Why published timing studies disagree with each other

Search the question and you will find confident, precise answers that contradict each other. One points earlier in the working day, another points later, a third reports that the pattern shifted since last year. None of them is lying. They are measuring different populations with different rulers.

Two studies can both be honest and still disagree completely, because the underlying question they answered was never the same question. That is the normal state of vendor research, not a scandal.

What a vendor timing study actually measures

A timing study is a snapshot of one tool's customer base. The tool logs when its users scheduled posts, reads the engagement numbers afterward, and sorts the results into a grid of days and hours. It is real data about real posts. It is just not data about you.

• The sample is self-selected. People who pay for a scheduling tool are already posting on a plan, which is a different habit from posting when something occurs to you.
• The audience is inherited. Engagement depends on who follows those accounts, and that audience has nothing to do with yours.
• Correlation is not a cause. The best hour in a grid may simply be the hour the best posts happened to go out.
• Averages hide the spread. A winning hour can win by a margin so small that any single post would swamp it.
• The incentive is real. The finished chart is content marketing for a scheduling product, which is fine, as long as you read it that way.

What LinkedIn says about how the feed ranks content

LinkedIn publishes a short description of feed ranking in its Help center, and it is worth reading before you optimize an hour. LinkedIn states that its systems consider hundreds of signals to decide what appears in each member's feed, including the context of a post and signals from your profile, network and activity.

LinkedIn also states that its algorithms do not use demographic information such as age, race or gender as a signal for the visibility of content, profiles or posts in the feed.

A separate Help article groups the relevance signals into three families. Publish time is not one of them, but recency appears inside two of them.

Read plainly, that says recency matters and early engagement matters, which is the grain of truth inside the timing advice. It does not say that a particular hour is favored, and LinkedIn publishes no such hour.

The practical consequence is narrow: post when the people who would respond are around to respond, because their reaction is a signal and its recency is part of the signal. That is a much smaller claim than a magic slot.

Most recent first, most relevant first

LinkedIn's relevance article also documents something that timing advice usually ignores. Members can sort their feed themselves. There is a per session option to see the newest posts first or posts organized by relevance, and a setting that makes the preference persist across sessions.

LinkedIn notes that for members based outside the European Economic Area this sorting feature may be available only on desktop.

So part of your audience sees a chronological feed, where publish time matters a great deal, and part sees a ranked feed, where a good post can surface hours later. You cannot know the split for your own followers, which is another reason a single universal hour cannot exist.

LinkedIn also describes what the feed draws from: posts from your connections, from people and companies you follow, from groups you belong to, and relevant updates from outside your network. Your post competes in all four lanes at once.

Time zones and a global audience

A posting hour is only meaningful next to a time zone, and most advice quietly assumes one. If a quarter of your followers work eight hours away from you, then every hour you choose is someone's early morning and someone else's evening.

Before running any timing test, look at where your audience actually is. LinkedIn's audience analytics break your followers down by location, and post analytics show the location of the people who saw a given post.

If your buyers are concentrated somewhere specific, your ideal customer profile already tells you which zone to optimize for. Optimize for them and accept that the rest of the world sees the post whenever it reaches them.

Testing days of the week, not just hours of the day

The day is a coarser question than the hour, and a much easier one to answer. There are seven buckets instead of dozens, so each bucket fills with data faster, and a day-level result arrives while an hour-level result is still noise.

Run the day test the same way: two days far apart, everything else held constant, alternating weeks. Resist the published verdicts about which weekdays win, because those best times were measured on other people's audiences in another industry.

Every row there is a trade-off rather than a verdict. Fewer readers with less competing content can beat more readers with more, and which way it falls for your account is exactly what the test is for.

Morning or afternoon?

The morning against afternoon argument is the same argument at a smaller scale, and the published data splits on it. Pick one slot in the morning and one later in the day as your two windows, then let four weeks of your own engagement numbers settle it.

One caution about mornings: a post published before your readers arrive competes with everything that arrives after it. A post published while they are already reading competes with less, but has fewer hours left in the day. Neither is obviously better.

The day by day questions, answered honestly

People search for the best times to post on LinkedIn one day at a time: Tuesday, Wednesday, Thursday, then the awkward days at each end of the week. Here is what can honestly be said about each, without borrowing another company's numbers.

Is Tuesday, Wednesday or Thursday the best day?

Tuesday, Wednesday and Thursday are the days most often named as the best times to post, because they are full working days for most professionals in most industries. That is a good reason to test them first. It is not evidence that your own audience behaves that way.

Those three days also share a problem. Everyone else has read the same advice, so competing content is thickest on Tuesday, Wednesday and Thursday, exactly when the readers are there. Whether the extra readers outweigh the extra competition is an empirical question about your audience.

Is Monday or Friday worth posting on?

Monday and Friday sit at the edges of the working week, and both usually carry less competing content than a Wednesday. Monday attention is fragmented by the backlog. Friday attention thins through the afternoon in many industries, and disappears early in some.

Neither day is a lost cause. If your test shows a Friday morning holding its own against a Thursday morning, that is a real finding about your readers, and it is worth more than any published grid of times.

What about Saturday and Sunday?

Weekend posting has the clearest trade-off of the week: far fewer professionals reading, far less competing content in the feed. Some audiences open LinkedIn on a Sunday evening while planning the week. Plenty of others do not open it at all until Monday.

Weekend volumes are small, so weekend data is noisy. Give a Saturday or Sunday test more weeks than a weekday test before you conclude anything from it.

How your industry changes the answer

The same posting times behave differently across industries, because the working day itself differs. Shift-based industries, field teams, agencies and globally distributed engineering organizations do not share an inbox rhythm, and the content that suits each of them is different too.

• Office-hours industries. Finance, professional services and software tend to produce a clear working-day window, which makes timing tests fast to read and easy to act on.
• Shift and field industries. Healthcare, logistics and retail spread attention across the whole day, so day-level tests work better than tests of specific times.
• Global teams. When the audience spans continents, no single slot serves everyone, and the engagement data across windows will look flat whatever you do.
• Seasonal industries. Conference weeks, quarter ends and holidays distort a month of data, so note them in the table and repeat the test in a normal month.
• Small niches. A few thousand relevant professionals produce little data per post, so test days rather than times, and be patient with the result.

Published industry breakdowns of the best times to post do exist. Like the rest of the vendor data, they describe that vendor's customers in that industry, not your audience. Use them to choose which windows to test, never as the answer itself.

Why LinkedIn timing differs from other social media

Posting-time advice travels between social media platforms and loses its meaning on the way. LinkedIn is used mostly by professionals in a work context, and its feed mixes your connections, the people and companies you follow, your groups, and relevant updates from outside your network.

Engagement itself means different things on each social media network. A reaction, a comment, a repost, a save and a send are separate metrics in LinkedIn post analytics, and a timing test that collapses them into one number throws most of that signal away.

A social media calendar that publishes the same content everywhere at the same times is optimizing for the tool, not the audience. If you run several networks, give each one its own posting times and its own test, and expect the answers to differ.

The engagement data arrives differently too. LinkedIn's post analytics separate impressions from members reached, and report the share of impressions from members who follow or are connected to you against the share from members who do not. That split says more than any total.

When to post on LinkedIn before you have data

You still have to publish something on day one, so you need a starting position that is defensible without pretending it is proven. The starting position is not an hour from a chart. It is a guess built from what you know about your readers.

• Start inside their working day. If your readers are professionals in one region, publish while they are at work rather than while they sleep.
• Be there afterward. Pick a slot when you can answer comments within the hour, because replies are engagement and its recency counts.
• Avoid your own convenience trap. Late at night suits the writer, rarely the reader.
• Keep the slot stable. A moving target cannot be tested, and the test is the point.
• Write down the guess. Record why you picked it, so the results mean something when they arrive.

Treat that as version zero. Deciding when to post on LinkedIn is a question you answer once with a guess and then again, properly, with four weeks of your own numbers.

How to run your own LinkedIn timing test

The test below was written for this page. It compares posting windows against each other using only the analytics LinkedIn gives every member for free. It takes four weeks and a spreadsheet.

1. Pick two windows, not seven

   Choose two posting windows that are far apart in the working day and plausible for your audience. Two options produce a readable comparison. Seven produce a table nobody can interpret.

2. Fix everything except the time

   Same format, similar length, same topic family, same number of posts per week. If the format changes with the hour, the test measures format instead of timing.

3. Alternate the windows week by week

   Week one uses window A, week two uses window B, then repeat. Alternating protects the test from a good week or a quiet holiday landing entirely on one side.

4. Record every post the day after

   Open each post's analytics and copy the numbers into the results table. Do it the next day so the collection lag is the same for every row.

5. Wait a full two weeks after the last post

   Late engagement is real, especially for readers in other zones. Re-record the final numbers once every post has had the same amount of time to settle.

6. Decide, then hold the winner for a quarter

   If one window wins clearly, keep it and stop testing timing. If neither wins clearly, the honest conclusion is that timing is not your constraint.

The results table you fill in

Copy this table into a spreadsheet and add one row per post. The columns are chosen so that the comparison survives an unusually good post, which a raw impression count does not.

Use the median of each window rather than the average. One post that travels far will drag an average across the line on its own, and that post tells you about the post, not about the hour.

Keep a notes column too. A post that coincided with an industry announcement, a launch or a holiday is worth flagging, because you will not remember six weeks later.

How to read the results without fooling yourself

The hardest part of a timing test is refusing to see a pattern that is not there. Post performance varies enormously between posts on the same topic in the same slot, so a small gap between two windows means nothing at all.

Remember that LinkedIn states the numbers in post analytics are estimates and may not be precise. Small differences between two windows are well inside that fuzziness, which is another argument for medians and for patience.

Where the numbers live in LinkedIn analytics

Everything the test needs is in the free analytics. LinkedIn documents post analytics for individual posts, creator analytics for the combined picture, and Page analytics for company pages.

Two documented details matter for a timing test. LinkedIn says your own views and engagements count toward your content's analytics, so stop refreshing your own post. It also says demographic data is not available for content shared only with connections or in groups.

Data does not live forever either. LinkedIn documents that video performance analytics are available for 365 days, article analytics for two years, discovery and social engagement counts for 1,000 days, members reached for 400 days and demographic breakdowns for 180 days. Export before the window closes.

If the metric names are unfamiliar, our guide to LinkedIn analytics walks through each tab, and the entry on LinkedIn impressions explains what an impression is and is not.

Scheduling posts, and what LinkedIn's own scheduler allows

A timing test only works if posts actually go out in the chosen window, which usually means scheduling them. LinkedIn has a built-in scheduler and it has documented limits.

The time zone note deserves attention. Because the scheduled time is anchored to your device's settings, a laptop that travels with you can move a post without you noticing, which is exactly the kind of noise a timing test cannot absorb.

Third party schedulers add queues, approvals and cross-network publishing. They do not have privileged access to feed ranking, whatever the marketing says. If you use one, read our note on LinkedIn automation and stay on the supported side of the line.

Posting frequency beats posting hour

Most accounts asking about the best hour are posting too rarely for the hour to matter. Two posts a month cannot produce a timing signal, and they cannot build an audience that would show one.

Frequency also fixes the sample size problem. A timing test needs enough posts per window to compare medians, and at one post a week that takes months. At two or three posts a week the same test finishes inside a month.

• Consistency creates the baseline. Without a steady rhythm you have no normal to compare an experiment against.
• Cadence is a content problem, not a calendar one. Pick a rate you can sustain with posts worth reading, then hold it.
• More posts, more data. Every extra post per week shortens the time to a trustworthy answer.
• Do not stack posts. Two posts hours apart compete with each other in the same feeds.

A workable rhythm comes out of a plan rather than inspiration. Our LinkedIn content strategy guide covers how to build one that survives a busy quarter.

Does the best time change by content format?

Formats behave differently over time, which quietly breaks timing tests that mix them. A text post gathers most of its engagement quickly. A document or video can keep collecting views for days, so the publish hour is diluted by everything that happens afterward.

• Short text posts reward being present to reply, so the window you can staff matters more than the window on a chart.
• Documents and carousels are read slowly and often saved, which flattens the effect of the hour.
• Video has its own metrics: LinkedIn counts a video view at two or more continuous seconds and also reports watch time and average watch time.
• Polls run for a set period, so the closing time matters as much as the opening one. See LinkedIn polls.
• Newsletters notify subscribers rather than relying on the feed alone, which is a different distribution problem. See LinkedIn newsletter.

Run your timing test on one format. Once you have an answer for that format, you can ask whether it transfers, but do not assume it does.

What matters more than timing

If you are choosing between spending an afternoon on a posting schedule and an afternoon on the post itself, spend it on the post. The variation between two good posts is larger than the variation between two reasonable hours.

Length, formatting and a clear ask do more work than the clock too. If you write long, check the LinkedIn post character limit before you publish, and keep the payoff above the fold.

Timing is a tie-breaker between two versions of a post that are otherwise equal. It is not a growth strategy, and no posting hour has ever fixed a weak LinkedIn marketing strategy.

Company pages and personal profiles differ

A personal profile and a company page do not reach the same feeds. Page posts reach followers of the page, while a personal post also travels through connections and the comment activity of everyone who engages.

That changes the timing question. A page with a mostly local follower base has a tighter window than a founder whose network is scattered across regions, and the two should be tested separately rather than sharing a schedule.

Page analytics support the same test: content analytics by date range, follower and visitor demographics, and search appearances. If you run both, keep two tables. Growing the page audience first is usually the higher-value work, and our entry on LinkedIn followers covers that side.

Common mistakes with LinkedIn posting times

• Copying an hour from a study whose audience has nothing in common with yours.
• Changing the posting time every week, which makes any result unreadable.
• Comparing a video in one window against a text post in the other.
• Judging a window on impressions alone, when reach and appeal are different things.
• Calling a winner after three posts, inside the noise of normal variation.
• Scheduling into a window when nobody on your side is available to reply.
• Running a timing test while also changing topic, length and format.
• Optimizing the hour for an account that posts twice a month.
• Forgetting that the scheduler anchors to your device's time zone when you travel.

A one page brief for the test

The brief below was written for this page. Fill it in before the first post, share it with anyone else who posts from the account, and keep it next to the results table so the rules do not drift halfway through.

LINKEDIN TIMING TEST

Account: {{accountName}}
Owner: {{ownerName}}
Start date: {{startDate}}
Decision date: {{decisionDate}}

Audience we are optimizing for: {{audienceSegment}}
Primary time zone: {{timeZone}}
Why this zone: {{zoneReason}}

Window A: {{windowA}}
Window B: {{windowB}}
Schedule: week 1 A, week 2 B, week 3 A, week 4 B

Held constant for all posts:
Format: {{format}}
Length: about {{wordCount}} words
Topic family: {{topicFamily}}
Posts per week: {{postsPerWeek}}
Who replies to comments, and within how long: {{replyRule}}

Metric we decide on: median {{metric}} per window
We will ignore any single post flagged as an outlier.
We will not change format, length or topic during the test.

Notes column for: launches, holidays, industry news, anything unusual.

Frequently asked questions