The best time to post on Instagram on Monday, from 844 posts

On Monday the hour you post moves likes less than the noise in the sample does. Of 5,734 Instagram posts from 171 public accounts, 844 went out on a Monday, and each one was scored as its likes divided by its own account's median likes, so a two-million-follower account and a two-thousand-follower account count the same.

Scored that way, Monday's smoothed curve stays between 0.87x and 1.12x all day. The five studies that rank for this question name Monday windows from 5am to 11pm, and the same accounts' Friday posts swung by about 30% between the working day and the evening. Monday doesn't.

At a glance

No Monday hour beats the rest by enough to move a post

Monday posts published between 6pm and midnight ET ran 1.13x posts published between 9am and 5pm, with a 95% interval from 0.90 to 1.43. That's 107 evening posts against 387 working-day posts, resampled by account, and the interval sits on both sides of 1.00.

The four-hour blocks don't hold a step either. Five of the six sit between 0.86x and 0.99x, and the sixth, 8pm to midnight, is the only one above normal.

• Midnight to 4am: 0.86x, from 104 posts
• 4am to 8am: 0.91x, from 145 posts
• 8am to noon: 0.99x, from 230 posts
• Noon to 4pm: 0.91x, from 184 posts
• 4pm to 8pm: 0.99x, from 106 posts
• 8pm to midnight: 1.16x, from 75 posts

The best block against the worst is 1.34x, interval 0.99 to 1.83. Against the rest of Monday, 8pm to midnight is 1.24x, interval 0.98 to 1.54. Both land just short of clearing, and both lean on the thinnest block in the day: 75 posts from 41 of the 160 accounts that posted on a Monday.

The share of posts that beat their own account's median says the same thing from another angle. It's 50% from 8am to noon and between 40% and 45% everywhere else, including 45% in the 8pm to midnight block. On Friday, the strong evening block had 56% of its posts above median. On Monday, the late-evening average is lifted by a few big posts, and most posts in it did no better than usual.

What would make this wrong: a real late-evening effect that this sample is too thin to confirm. The smoothed curve does rise after 5pm, and a bigger crawl could turn a 16% block into a result. On these 844 posts, it isn't one yet.

The morning has no peak, and Monday evening is an ordinary evening

Monday posts from 5am to 9am scored 1.01x the working day, interval 0.81 to 1.27, on 176 morning posts. Later names 5am as Monday's best time, and SocialPilot says Monday mornings run a little weak. Here the morning is flat, with neither a peak nor a dip.

Against the other six days, Monday looks the same in daylight and after dark. Monday daytime posts (8am to 4pm) ran 1.00x other days' daytime posts, interval 0.89 to 1.13, and Monday evening posts ran 1.03x other days' evenings, interval 0.83 to 1.25. On Friday that evening comparison was 1.19x and cleared.

Where Monday does trail the other days is overnight and in the early evening: midnight to 4am ran 0.86x against 1.05x, and 4pm to 8pm ran 0.99x against 1.09x. That early-evening block is where Buffer's 6pm to 8pm and most of Hootsuite's 3pm to 9pm fall, and it opens on the smoothed curve's 4pm low of 0.87x.

Accounts post most in the working morning. About a third of Monday posts went out between 8am and 1pm, and only 13% after 6pm. Unlike on Friday, that morning cluster isn't in a trough: 8am to noon sits at 0.99x, level with 4pm to 8pm.

Read raw, the individual Monday hours bounce between 0.64x and 1.37x on cells of 12 to 68 posts, which is why the chart smooths each hour over its two neighbours on either side. Every smoothed window holds at least 79 posts. The thinnest cells are all in the evening: 6pm has 12 posts, 9pm has 13, and 8pm has 15. The 9pm high of 1.37x raw comes from those 13.

Monday is an ordinary weekday, and it trails the weekend

Across the full week, Monday sat at 0.95x an account's normal likes. Tuesday was 0.98x, Wednesday 0.93x, Thursday 0.99x, Friday 0.98x, Saturday 1.05x, and Sunday 1.08x. Monday against Tuesday to Thursday is 0.99x, interval 0.89 to 1.08: the same.

Against the weekend, Monday is 0.90x, interval 0.82 to 1.01, on 844 Monday posts and 1,453 weekend posts. That's a 10% gap that lands one point short of clearing. The earlier Instagram study, on the same accounts and a fifth of the posts, had Monday at 0.99x on 312 posts, so both samples put Monday at or a little under normal.

Split by account size, the picture is uneven, and the cells get small fast:

• Under 10k followers: Monday ran 0.87x the same accounts' other days, interval 0.76 to 0.99, on 370 Monday posts against 1,983
• 10k to 100k: 0.96x, interval 0.85 to 1.09, on 304 against 1,850
• 100k to 1M: 1.12x, interval 0.91 to 1.36, on 137 against 874
• Over 1M: 1.36x, interval 1.02 to 2.20, on 33 against 183, from 7 accounts

Only the smallest tier clears in the negative direction, and it's one of four cuts, so it could be chance. The top tier's 1.36x rests on 33 posts from 7 accounts, which is too few to act on.

How this compares to what is already published

• Buffer, from 9.6 million posts across 200,000 accounts, names 7pm, then 6pm, then 8pm as the best Monday times, and rates Monday "Moderate" among the days.
• Sprout Social, from nearly 2 billion engagements across about 307,000 profiles, names Monday 2pm to 4pm, and ranks Monday to Thursday as the best days and weekends as the worst.
• Hootsuite, from over 1 million posts, names 3pm to 9pm, and lists Monday among its best days.
• Later, from over 6 million posts, names 5am, with 11pm as the backup, and calls Monday the best day overall.
• SocialPilot, from 7 million posts across about 50,000 accounts, names 1pm to 2pm and 4pm to 6pm, and says Monday mornings run a little weaker than other weekdays.

Later's 11pm sits inside the one block here that ran above normal. Its 5am doesn't; 4am to 8am ran 0.91x. Sprout's 2pm to 4pm and SocialPilot's 1pm to 2pm fall in the noon to 4pm block at 0.91x, and Buffer's 6pm to 8pm falls in a block at 0.99x. Hootsuite's 3pm to 9pm runs from the day's low to its high.

On the day, three of the five put Monday near the top of the week, and this sample puts it about 10% under the weekend. Sprout's weekend-is-worst read comes from three months of winter, from late November to late February, and Buffer's own table rates Monday "Moderate" and Sunday the same.

The methods land in different places because they measure different things. Every one of the five ranks engagement across accounts, so the hour the biggest accounts prefer wins by default, and every one reports times in the audience's local time, which this study doesn't. None prints a per-hour value or a sample size per hour. Scoring each post against its own account and showing the count under every bar is what lets this study say when a Monday gap is too small to trust.

How I measured it

This is the same crawl as the Friday study, cut for Monday. It ran through one Instagram endpoint on AnyAPI, instagram.user_posts, in 657 calls, and cost $0.53. The Monday cut needed no new calls.

1. Start from the accounts already in the sample. The 211 accounts came from the earlier Instagram study, which found them through 40 creator-niche searches and picked them round-robin across four follower tiers.
2. Pull deeper. instagram.user_posts returns twelve posts per call with a timestamp and a like count, plus a cursor for the next page. Each account was paged up to four times, stopping early once a page reached back past the window. The median account contributed 38 posts.
3. Apply the cutoffs. Posts had to be published between 2025-09-22 and 2026-09-08, so every like count had at least 14 days to settle. Accounts needed five scorable posts. That dropped 1,969 posts as too recent or too old, 10 posts with zero likes, and 40 accounts that fell under five, leaving 171 accounts and 5,734 posts, published between 2025-09-23 and 2026-09-08. 160 of those accounts posted on a Monday.
4. Score each post against its own account. Divide each post's likes by that account's median likes over the window, and cap the result at 6x so one viral post counts once. 433 posts hit the cap.
5. Bucket and average. Convert every timestamp to US Eastern. Group by weekday, by four-hour block, and by hour, and take the geometric mean of the scores in each group. Hourly values are smoothed over a five-hour window. Every interval in this post comes from resampling accounts, not posts, 1,000 times.

Here's one page of the crawl, on one account in the sample:

curl -sS -X POST https://api.getanyapi.com/v1/run/instagram.user_posts \
  -H "Authorization: Bearer $ANYAPI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"handle":"_garden.ing"}'

{"output":{"data":{"posts":[{"id":"3988678296405120718","createdUtc":1789707527,"likes":804,"comments":217}],"nextCursor":"..."}},"costUsd":0.0008}

The sample: 69 accounts under 10k followers, 63 between 10k and 100k, 32 between 100k and 1M, and 7 over 1M. The typical account's typical post had 112 likes.

The limits of this data

• Likes only. Nothing here speaks to reach, saves, shares, comments, or follower growth, and Instagram's ranking leans on sends and saves more than likes.
• US Eastern for everyone. Accounts were found globally and no account was mapped to its audience's time zone. Monday 9pm in New York is Tuesday morning in Singapore, so the late-evening block mixes two different days for some audiences.
• Thin evening cells. The block closest to a result holds 75 posts from 41 accounts, and three of its raw hours hold 12 to 15 posts each. Only a larger crawl would settle it.
• Observational. Content, format, and promotion all confound this. An account that saves its best post for Sunday and fills Monday with lighter posts makes Monday look weak.
• Four tier cuts. One of the four clears, which is about what chance alone can produce. Treat the small-account result as a lead to check on your own account.
• A convenience sample. The accounts came from 40 niche searches a year ago. A different set of niches could shift a result this size.
• Current follower counts. An account that grew during the year is labeled by today's size, and the tier cuts have 7 accounts at the top.

The biggest hour gap on Monday, best block against worst, is about a third, and even that doesn't clear its interval. On this sample, the Monday hour is inside the noise.

What to do with it

1. Keep your Monday slot wherever it suits your week. No block of the Monday day beat another by a margin that cleared.
2. If you want something to test, test 8pm to midnight in your audience's time zone. It's the only block above normal, and it's the one most likely to turn into a result with more data.
3. Don't move a Monday post to the morning for a morning peak. The 5am to 9am posts scored the same as the working day.
4. If you can choose the day, pick the weekend. Saturday and Sunday ran about 10% above Monday, one point short of clearing. Give it a second sample before you move.
5. Check your own account once it has thirty Mondays. Pull your posts with instagram.user_posts, page past the newest twelve so you're not scoring posts that are still collecting likes, divide each post's likes by your median, and group by hour in your audience's time zone. Ignore any hour with fewer than about ten posts. Four calls is about a third of a cent.

Frequently asked questions

What is the best time to post on Instagram on Monday?

In this sample, 8pm to midnight US Eastern came closest, at 1.16x an account's normal likes on 75 posts, and the single best smoothed hour is 9pm at 1.12x. Neither clears its interval, so treat it as the slot to test.

What is the worst time to post on Instagram on Monday?

Midnight to 4am, at 0.86x an account's normal likes, with 4am to 8am and noon to 4pm at 0.91x. The lowest smoothed hours are 4am and 4pm, both at 0.87x.

Is Monday a good day to post on Instagram?

It's an ordinary weekday. Across 5,734 posts, Monday sat at 0.95x, level with Tuesday to Thursday and about 10% under Saturday and Sunday. Accounts under 10k followers did worst on it, at 0.87x their other days.

Why do other studies name a different Monday time?

They rank raw engagement across accounts, so the hour the biggest accounts favour wins, and they convert to each audience's local time, which this study doesn't. With a Monday hour effect this small, any method will find a "best" hour, and the five studies found five different ones.

The Friday study found the hour effect that Monday doesn't have, the Instagram study across all seven days uses the same method on the same accounts, and the Instagram endpoints are what you'd use to rerun it on your own account.

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