There is no single best posting time for every page. Get starting windows to test, a 14-day experiment sheet, and a way to read the result from your own Insights.
The best time to post is different for every page. So this article does not give a posting-time chart that claims to work for every page. It gives you starting windows to test, a 14-day experiment you can follow, and a way to read the result from your own Insights. By the end you can pick the windows to test, log the results, and decide when your page should post, using data from the people who actually follow you.
Why there is no single best time for every page
Plenty of articles, videos and posts name a best time. But those numbers come from other pages, other audiences and other periods. Your page has its own kind of customer, and the time they scroll may not match the average across everyone.
Three reasons a universal answer fails
Customer groups are free at different times. Students, office workers and night-shift sellers each live to a different rhythm
Platforms can change how they rank feeds. What worked once may not work this year, and nobody warns you
Different post types perform differently. A funny clip, a sales post and an educational post may each do better at different times
The most reliable answer comes from your own page data. Everything else is a starting point to try.
How far can outside data go
Reports and articles from outside can help you choose windows to start testing, but they are not the answer. When you use one, check whether the source states the date of the data, the group studied and the country. If it states none of the three, treat it as opinion.
Starting windows to try, by time of day
The windows below are hypotheses based on the rhythm of everyday Thai life. They are not confirmed facts for your page. Test them using the next section.
5 windows to try
Morning before work or school. People pick up their phone on waking or on the commute. Test it with short, easy-to-read content
Lunch break. Office workers and students are free at the same time. Try posts where you want people to message or save for the evening
After work or school. The trip home and the time after arriving. Try posts with more detail
Before bed. People scroll for longer. Try clips that are pleasant to watch, or story-style posts
Saturday and Sunday afternoon. People have more free time than on weekdays. Try posts that need more time to read or watch
Using these windows on each platform
Instagram: on a business or creator account, Insights often shows when your followers are online. Use it as a starting point. Menu names and details may change with app versions, so search the app for "Insights"
TikTok: with a creator or business account you get analytics pages with audience information. Use them to see when followers are active
Facebook: a Page has an Insights section with follower data and post reach. Use it to compare posts published at different times
All three show data about your own account, which beats a universal chart that someone else summarised. Still, it is only a starting point, because it tells you when people are online, not when posting gets the best result.
Table by customer group
Pick the row closest to your customers and use windows from that row as your starting point. Every row is a hypothesis.
Students
Windows to try: after school, before bed, and weekend afternoons
Why the hypothesis: phones are often off-limits during class, so free time clusters outside class hours
Watch out: exams and school breaks change behaviour, so test separately
Office workers
Windows to try: the morning commute, lunch break and after work
Why the hypothesis: there are short, clear breaks in the day when a phone comes out
Watch out: around month-end and payday people may buy more, so note the dates to compare
Homemakers and family carers
Windows to try: mid-morning after the school drop-off, afternoon, and evening after tidying up
Why the hypothesis: free time tends to come in short blocks that do not match office hours
Watch out: try weekdays and days off, because the rhythm differs a lot
Shift workers and night-time sellers
Windows to try: late night and early morning, windows that others might consider odd
Why the hypothesis: free time for this group is shifted from the usual
Watch out: this group is very varied, so ask real customers in chat when they usually scroll
Just ask your customers
The cheapest method is to ask in a story or in chat. Sample message:
When do you usually check our shop? (pick one) A morning B lunch C evening D before bed
You get direct data from people who actually buy. Use it alongside the experiment, and you have a better starting point than guessing without waiting 14 days.
A 14-day experiment: sheet of time × result
To get a reliable answer you must change only one thing, the time. Keep everything else as similar as possible.
Setup steps
Pick 3 windows from the ones above, for example lunch, after work and before bed
Decide to post the same type of post throughout, for example a product photo with the same style of caption, since different post types make comparison unfair
Plan 12 to 14 posts across 14 days, rotating through the three windows. Do not put one window entirely on weekdays and another entirely on days off
Decide in advance which numbers you will watch. Three or four is enough
Change nothing else in the same period. For example do not boost some posts, since that will mix with the effect of time
What to record
Choose numbers that relate to the shop's real goal.
Reach: how many people saw the post. Shows how widely the post was delivered
Saves and shares: signals that people found the post useful. They often show interest more directly than likes
Messages and link taps: the numbers nearest to sales. If your shop sells through chat, note how many people message after each post
When you record: record each post at the same interval after posting, for example 24 hours, because a new post and an old one cannot be compared
The log sheet: copy and fill
Create a table in a notebook or spreadsheet with these columns and add one row per post.
Date and weekday = ______
Time posted = ______
Post type = ______
Reach at 24 hours = ______
Saves = ______
Shares = ______
Messages = ______
Notes, such as holiday, promotion, rain = ______
A worked example (invented numbers to teach reading, not real data from any shop)
An invented home-baked treats shop tests 3 windows, 4 times each. The post type is always a photo of a treat with a question-and-answer caption.
Lunch: reach 180, 210, 170, 200 / saves 6, 9, 5, 8 / messages 2, 3, 1, 2
After work: reach 240, 260, 200, 250 / saves 12, 15, 9, 14 / messages 4, 5, 2, 4
Before bed: reach 150, 190, 210, 160 / saves 5, 8, 10, 6 / messages 1, 3, 3, 1
The numbers above are invented, to practise reading a table.
How to read the result: a real difference, not luck
Data from a handful of posts always wobbles. One post can do well for a reason that has nothing to do with time. So set reading rules before you conclude.
3 reading rules
Win consistently, not once. A good window should beat the others in most posts, for example 3 out of 4, not just have an average pulled up by one big post
Differ enough to see. If two windows differ by a small amount, call it a tie and do not change your schedule
Numbers near sales matter more. If one window has high reach but few messages, and another has lower reach but more messages, choose by your shop's goal
These three rules are a simple way for a shop owner to read results. They are not a statistical test. For high precision you need more data.
Reading the example above
In the invented example, after work beat lunch in all 4 posts and beat before bed in 3 out of 4, on reach, saves and messages alike. By rule 1, it can be your main window. Lunch and before bed are close, so call it a tie. Next, shift the after-work slot earlier or later by half an hour and run another round.
Things that distort the result
Holidays or payday: these can make more or fewer people online, regardless of time
A post that gets shared: one post shared into a group can lift a whole window. Note it and consider excluding it
Boosting: if you boost some posts, the numbers no longer reflect posting time alone
Very small accounts: numbers so small they wobble a lot. Stretch the test to 3 or 4 weeks, or run more posts
Three sample weekly schedules
Once you know your good windows, use these as a frame. All are invented examples. Put your page's windows in.
Option 1: 3 posts a week
Monday: an educational or behind-the-scenes post at {winning window}
Wednesday: a main product post at {winning window}
Saturday: a post that takes longer to read, at {winning weekend window}
Option 2: 5 posts a week
Monday: educational or behind-the-scenes
Tuesday: main product
Thursday: answering a customer question
Friday: announcement or promotion
Sunday: story post or a look at finished work
Every post uses your winning window from the test, and now and then you swap in a second window to keep testing.
Option 3: 7 posts a week
Monday to Friday: one post a day, rotating types as in option 2
Saturday: a post people save, such as a checklist or product roundup
Sunday: a relaxed story or short clip
Posting daily needs prep time. If content gets repetitive or quality drops, go back to 5 a week.
Limits of this article and of outside data
This article cites no verifiable statistic saying which window is best. Every suggested window is a hypothesis
Your test result applies to your page at that time, and may change as your audience or the platform changes. Repeat the test once or twice a year
Time is one factor among many. Content that fits your customers, an eye-catching image and a clear caption often matter more. For the signals platforms can see, read Instagram algorithm and engagement
If an account has very few followers, Insights holds too little data to conclude much
If the account has too little data to test
New accounts tend to have few viewers, so reach per post wobbles too much to read. Your options are to lengthen the test, or to get the profile in front of more people first and then test. If you choose the second, see Instafollow services for Instagram, TikTok and Facebook. It needs only a public username, no password. Results vary by account, and adding numbers does not make those followers care about your product, so you still need to read your own page data. To learn how, read how to read social analytics and decide where to invest.
FAQ
What is the best time to post on TikTok?
There is no single answer for every account. Start with two or three windows, such as lunch, after work and before bed, and compare them with the 14-day sheet above.
When should I post on Facebook?
Start from the window that your Page Insights says followers are online, and test it against two others. Other pages' results are only hypotheses.
Is posting on IG daily better than three times a week?
Not necessarily. The right frequency is what you can keep up while the content stays good. More posts with worse content is often worse than fewer, better posts. Compare using your own page numbers.
How long must I test before I trust the result?
14 days is a practical starting point. If the numbers wobble a lot, or one post is unusually big, continue for 3 to 4 weeks.
An article recommends a time and my test disagrees. What now?
Trust your page data. Recommended times come from other audiences. If your result differs, your customers differ from that group.
Should I post at the same time every day?
Posting at similar times helps people get used to you, but it is not a rule. If your test shows weekdays and days off differ, use two windows.
Do I need extra analytics tools?
Not to begin with. The Insights page in the app and an ordinary spreadsheet are enough for this experiment.
Summary
There is no best posting time for every page. Start from a few hypotheses, run a 14-day test that changes only the time, record three or four numbers, read the result with the three rules, and turn the winning windows into your weekly schedule. Repeat the test from time to time when your audience changes.
