Updated 5/4/2016: Added some new insights and learnings into the blog post here on the best times to tweet. We’re so grateful for the chance to learn from the community on this!

Imagine removing all guesswork when you schedule your tweets, knowing the best times to experiment with tweeting for maximum clicks and maximum engagement.

As someone who is working on social media marketing strategy or shares frequently to social media, this info would be fantastic to have! We’re always eager to dig up new research into social media best practices—things like length and frequency and timing.

The timing element, in particular, feels like one where we’d love to dig deeper. And we just so happen to have a host of data on this from the 2 million users who have signed up for Buffer!

With a big hand from our data team, we analyzed over 4.8 million tweets across 10,000 profiles, pulling the stats on how clicks and engagement and timing occur throughout the day and in different time zones. We’d love to share with you what we found!

Update: Optimizing your schedule is one of the strategies I cover in the Actionable Social Media Strategies email course. I’d love to share some practical methods on timing your tweets with you there. (Plus, you’ll get pointers on 24 more areas of social media!)

best time for twitter

The best time to tweet: Our 4.8 million-tweet research study

Our key learnings

Wow, we learned so much looking at the awesome stats from those who use Buffer! Here were some of the takeaways we came up with. I’d love to hear what catches your eye, too!

  • Based on all of the tweet data we have collected, the early morning hours appear to be the time in which tweets receive the most clicks, on average.
  • Evenings and late at night are the times when your tweets receive the most favorites and retweets, on average.
  • In some cases, times with the highest amount of average engagement are almost inversely related to the most popular times to tweet.
  • The most popular time to tweet and the best times to tweet for engagement differ across time zones, so it’s still important to experiment and find the times when your audience is most engaged.

What you might do with this data

In some of the results below, you’ll see specific times that we found to be the most popular times to tweet or the best times to tweet for clicks, for example.

What we love to do with specific takeaways like this is use them as the starting points for new experiments.

Over time we’ve come to learn that research studies like these are great for inspiration, not prescription. I’d pause slightly in suggesting that you change your whole Buffer schedule to align with these new Twitter times—unless your data and analysis says so!

What I’d love to suggest is that these new times perhaps give you ideas about what to test out next with your social media sharing, perhaps some counterintuitive suggestions about what to try—tweeting at non-peak times, tweeting at 2:00 a.m. for clicks, for instance.

And we’d love to hear back on how any of these tests turn out for you!

The most popular time to tweet:

Noon to 1:00 p.m.

We’ve taken the data from all tweets sent through Buffer to find the most popular times for posting to Twitter. Looking at all tweets sent across all major time zones, here is an overview of the most popular times to tweet.

  • Noon to 1:00 p.m. local time, on average for each time zone, is the most popular time to tweet
  • The highest volume of tweets occurs between 11:00 a.m. and 1:00 p.m., peaking between noon and 1:00 p.m.
  • The fewest tweets are sent between 3:00 and 4:00 a.m.

What you might do with this data

The most popular time to tweet is also the time when there is the highest volume of tweets, perhaps making it a bit more difficult for your tweet to stand out in someone’s timeline.

What might be great to try here is tweeting at non-peak hours, the times in the early morning and late evening.

Another thought is that the most popular times to tweet could very well correlate to the times when most people are on Twitter. Perhaps it’s worth testing also to see if tweeting during a popular time is worthwhile simply for the amount of people who are online.

(One great stat to look at with this is tweet impressions, which you can find in Twitter’s free analytics.)

**

Here’s the chart for the most popular times worldwide, taken from an average of 10 major time zones (the times represent local time).

Most Popular Time to Tweet Worldwide

Here is the graph for the most popular times to tweet in each of the four major U.S. time zones. 

Buffer social media science study - US popular times to tweet

(We normalized the data to account for daylight’s savings in the U.S. as well.)

Here are the charts for the major time zones in Europe and Africa.

Most Popular Time to Tweet Europe

(Note: The London (GMT) time zone used to be the default time zone for new Buffer users, so our data for GMT is not as clean as we would like it to be. We’ve omitted any takeaways for GMT from the research results here.)

Here are the charts for the major time zones in Asia and Australia.

Most popular times to tweet Asia Australia

It’s interesting to see how the most popular time to tweet varies across the time zones. We’ve shared Buffer’s 10 most popular time zones in the charts above. Here’s a list of each most popular hour for the 10 major time zones.

  • Los Angeles, San Francisco, etc. (Pacific Time): 9:00 a.m.
  • Denver (Mountain Time): noon
  • Chicago (Central Time): noon
  • New York, Boston, Atlanta, Miami, etc. (Eastern Time): noon
  • Madrid, Rome, Paris, etc. (Central European): 4:00 p.m.
  • Cape Town, Cairo, Helsinki, etc. (Eastern European): 8:00 p.m.
  • Sydney (Australian Eastern): 10:00 p.m.
  • Hong Kong (Hong Kong Time): 8:00 a.m.
  • Tokyo (Japan Time): noon
  • Shanghai, Taipei, etc. (China Time): 9:00 p.m.

For any clarification on this or the other research throughout this article, feel free to leave a comment and we’ll get right back to you.

Takeaways & thoughts:

  • The most popular time to post could be due to a number of factors: This is when most people have access to Twitter (perhaps at a work computer), this is when online audiences are most likely to be connected (see Burrito Principle), etc.
  • Should you post during the most popular times? That’s one possibility. Also, you may find success posting at non-peak times, when the volume of tweets is lower.
  • If you have a large international audience on Twitter, you may wish to locate the particular part of the world where they’re from, and adjust your schedule accordingly. You can find the times when your audience may be online with tools like Followerwonk and Crowdfire.

The best times to tweet to get more clicks

We were excited to dig into the specific metrics for each of these tweets, too, in hopes of coming up with some recommendations and best practices to test out for your Twitter strategy.

First up, the best time to tweet for clicks.

Looking at the data, we found the following trends for maximizing your chance to get more clicks:

  • Tweets sent between 2:00 and 3:00 a.m. earn the most clicks on average
  • The highest number of clicks per tweet occurs between 2:00 a.m. and 4:00 a.m., peaking between 2:00 and 3:00 a.m.
  • The fewest clicks per tweet happen in the morning (when tweet volume is particularly high), between 9:00 a.m. and 1:00 p.m.

What you might do with this data

We were fascinated to see that the best time to earn the most clicks on average was the middle of the night. It’s a quite counterintuitive results!

One interpretation here is that with this being the average, there is the possibility that outliers can have a large impact on the data—for instance an tweet that gets 4,000 clicks at 2:00 a.m. would raise the average significantly.

So what I might take away from this is that tweeting at 2:00 a.m. would likely not mean that every 2:00 a.m. tweet will see really high click numbers but that every once in awhile a 2:00 a.m. tweet could really take off. 

** Scroll to the bottom of the post for an updated explanation of this data (as well as some alternate views). We’re very grateful for all the helpful comments on this! **

The data in the below chart is the worldwide average, calculated for the local time in each time zone. So the peak at the 2:00 a.m. hour would hold true as the overall top time no matter which time zone you’re in—2:00 a.m. in Los Angeles, New York, Cape Town, Hong Kong, etc.Best Times to Tweet for Clicks Worldwide

 

For the specifics on each of the best time to tweet for clicks in each of the major time zones in Buffer, here’s a breakdown.

  • Los Angeles, San Francisco, etc. (Pacific Time): 2:00 a.m.
  • Denver (Mountain Time): 7:00 p.m.
  • Chicago (Central Time): 2:00 a.m.
  • New York, Boston, Atlanta, Miami, etc. (Eastern Time): 11:00 p.m.
  • Madrid, Rome, Paris, Berlin, etc. (Central European): 2:00 a.m.
  • Cape Town, Cairo, Istanbul, etc. (Eastern European): 8:00 p.m.
  • Sydney (Australian Eastern): 2:00 a.m.
  • Hong Kong (Hong Kong Time): 5:00 a.m.
  • Shanghai, Taipei, etc. (China Time): noon
  • Tokyo (Japan Time): 8:00 a.m.

Best Times to Tweet for Clicks - by time zone

Takeaways & thoughts:

  • Clicks was far and away the largest engagement metric that we tracked in this study (compared to retweets, replies, and favorites).
  • Some of the recommended best times for individual time zones show that non-peak hours are the top time to tweet for clicks. This data may reflect some particularly high-achieving posts—some outliers—that bring up the average when the volume of tweets is lowest. Still, it’d be a great one to test for your profile to see what results you get.
  • One neat thing to keep in mind is that a non-peak hour in, say, Los Angeles may correspond to a peak hour in London or Paris. The worldwide audience is definitely one to consider when finding the best time to tweet.
  • The 2:00 a.m. recommendation in the worldwide chart is made by looking at the average of all the data and hence may include the effect of certain outlier accounts. One way I like to look at this is that the potential exists for great leaps in engagement for your tweet by posting at 2:00 a.m., however it may be unlikely to expect that posting at 2:00 a.m. would bring consistently higher click rates on each and every individual tweet.

For more context on this, see our note from Julian, Buffer’s data scientist, below.

The best times for overall engagement with your tweet

We define engagement as clicks plus retweets, favorites, and replies. When looking at all these interactions together, we found the following trends for maximizing your chance to get the most engagement on your tweets:

  • Tweets sent between 2:00 and 3:00 a.m. earn the most total engagement on average
  • The highest amount of engagement per tweet occurs between 11:00 p.m. and 5:00 a.m., peaking between 2:00 and 3:00 a.m.
  • The smallest amount of engagement happens during traditional work hours, between 9:00 a.m. and 5:00 p.m.

Best Times to Tweet for Engagement

Takeaways & thoughts:

  • The best times to tweet for engagement are quite the inverse of the most popular times to tweet. (The late-night infomercial effect—tweet when fewer people are tweeting—seems to be the case here.)

The best times for retweets and favorites on your tweets

Adding together two of the most common engagement metrics, we found some interesting trends for maximizing the retweets and favorites on your tweets, especially for those with a U.S. audience.

Looking at 1.1 million tweets from U.S. Buffer users from January through March 2015, here were some of the notable takeaways we found:

  • Tweets sent at the 9:00 p.m. hour in the U.S. earn the most retweets and favorites on average
  • The highest number of retweets and favorites occurs between 8:00 p.m. and 11:00 p.m., peaking between 9:00 and 10:00 p.m.
  • The lowest retweet-favorite engagement happens at 3:00 a.m.

(Interesting to note, the takeaways from this data compared to the worldwide engagement data differ slightly for a couple reasons: 1) clicks represent a huge portion of overall engagement, and 2) the worldwide vs. US datasets vary.)

Best Times to Tweet for Engagement USA

We’d love to make it easy for you to share these results with your audience, your friends, your clients—anyone you think might benefit from them.

>> Download every chart from this post (.zip) <<

The methodology for our research

We studied all tweets ever sent through Buffer—4.8 million tweets since October 2010!

Based on this sample set, we looked at the number of clicks per tweet, favorites per tweet, retweets per tweet, and replies per tweet, in accordance with the time of day that the tweet was posted to Twitter.

Further, we segmented the results according to time zones, based on the assumption that the learnings might be more actionable if they could be specific to exactly where you live and work.

We had an interesting opportunity to consider whether median or average would be the better metric to use for our insights. It turns out that so many tweets in the dataset receive minimal engagement that the median was often zero. For this reason, we chose to display the average.


 

Thanks for all your great comments on this data. We’re so grateful for your help in improving these results. See below for an update from our data scientist Julian. 🙂

Update: Context & clarifications on the Twitter timing data

Some of the findings in this study are quite counter-intuitive. In particular, our finding of 2:00 a.m. as the best time to tweet for clicks really stands out.

I would love to take this opportunity to try to explain why.

The early morning hours were when tweets received the most clicks, on average, in several of the time zones we analyzed. There are several factors apart from the hour of day that may affect the amount of clicks that a tweet receives, many of which we’ve been grateful to learn from you in the comments and via social and email.

  1. The number of followers a Twitter account has can have a very large influence on the number of clicks, retweets, or favorites a tweet receives.
  2. The type of content, day of week, and messaging can also influence engagement.

When analyzing our tweet data, I did not control for these extraneous factors, and I’m sorry for the confusion this has caused. Analyzing the data as-is means that, when you see a result of 2:00 a.m. to 3:00 a.m. as the hour in which tweets receive the most clicks, this is an average amount of clicks for all of the tweets in that particular timezone.

This is an important consideration for a couple reasons:

  1. It means that large accounts with many followers have an unusually large influence on the average amount of clicks per tweet.
  2. Especially in the early morning hours, these large accounts have a disproportionate effect on the average amount of clicks because of both the high follower count and the relatively low tweet volume from many of the other Twitter accounts.

For example, the graph below shows the total number of tweets posted from accounts in each follower tier in the Eastern European Timezone (EET).

Twitter Timing - CET broken down by follower tier

The largest accounts, those in tier T06 with over 5,000 followers, tweet far more often than all of the other accounts and tweet mostly late at night, when other accounts don’t tweet as much. This raises a red flag in my mind. What I could do here is segment the data, so that data from the large accounts doesn’t confound the findings from the rest of the accounts, which may represent a more typical Twitter user. (I did this below, if you’d like to take a look!)

Another great thought from those of you who read the post is that we could look at the data with another convenient statistic, the median (the middle value in a series of values), to compare the amount of engagement received by tweets sent out at different hours of the day.

The main reasons I chose to stick with the average is that so many tweets in our dataset received no clicks, retweets, or favorites. As a result, most of the medians for the different hours of day turned out to be 0!

More complicated transformations of the data could have also been employed, but the use of such methods make the findings a bit more difficult to interpret, and we’re very keen to provide actionable insight to all of our readers!

I totally understand that, while including all of the accounts gives a full view of all of our Twitter data, it means that some of the data might be skewed by these large accounts tweeting in unusual hours. I definitely don’t want skewed data, and I want to be fully transparent about this and what we’re doing to correct this.

The best time to tweet for clicks: An alternate way of looking at the data

To control for the effect of the large accounts on average engagement, I looked at the total number of tweets posted from accounts in seven separate follower tiers as well as the average likes received from those tweets.

In some cases an outlier in the data was also rather obvious. For instance, seeing tweets from accounts with fewer than 100 followers receive thousands of clicks on average raises a red flag in my mind that it could be an outlier. In other cases, I found that large accounts tweeted much more than other accounts during unusual hours and received an unnatural spike in average clicks.

I found that it might be useful to remove these segments from the data.

An example of a case such as this can be seen in the graph below.

Twitter timing example - outlier

After filtering out accounts with a disproportionate amount of weight that were skewing the data, here is what we found. I’d love to hear your feedback and would be happy to respond to any questions in the comments! 🙂

Best Time to Tweet for Clicks, Worldwide: 6:00 to 7:00 a.m.

(excluding outliers with abnormally volatile average click counts)

  • Los Angeles, San Francisco, etc. (Pacific Time): 10:00 p.m.
  • Denver (Mountain Time): 7:00 p.m.
  • Chicago (Central Time): 2:00 a.m.
  • New York, Boston, Atlanta, Miami, etc. (Eastern Time): 2:00 p.m.
  • Madrid, Rome, Paris, Berlin, etc. (Central European): 5:00 p.m.
  • Cape Town, Cairo, Istanbul, etc. (Eastern European): 5:00 a.m.
  • Sydney (Australian Eastern): 1:00 p.m.
  • Hong Kong (Hong Kong Time): 5:00 a.m.
  • Shanghai, Taipei, etc. (China Time): 7:00 a.m.
  • Tokyo (Japan Time): 8:00 a.m.

We mentioned earlier that these fun stats are oftentimes better for inspiration rather than prescription. We wanted to take a moment to dive into a few different ways to further help us decide what timing we should go for when sending out tweets.

Let’s take a look at four of the most useful experiments that we ran when looking at the timing of Tweets:

1.) The data-driven approach to finding the best time to tweet:

If I had to suggest just one of these approaches to determining what time is best to Tweet, it’d be this one. Social media timing is so hard to pin down exactly that it definitely pays off to do your own experiments and pay attention to the data about when your audience is most receptive.

You can test this out with a bunch of different tools, but I’m going to use Buffer to show you some examples, since it’s so easy to do within Buffer.

1. Pick 4 times to test
You can pick any number of times to test, of course, but any more than four would be too much for me to keep track off so I’ll start there.

buffer time

2. Schedule Tweets for each of these times
To keep the data as consistent as possible without annoying our followers with the exact same Tweet four times a day (we do post the same links multiple times, but we spread them out more), I’m going to post simple Tweets with a headline + a link each time.

buffer post

3. Examine your analytics to compare
Once these have all posted, I can take a look at Buffer’s analytics the following day and see how the Tweets compare for clicks, favorites and Retweets. Here’s our queue with my posts added:

buffer sched

And here’s an example of what our analytics would look like:

buffer analytics

4. Keep testing
There are lots more factors to test if I want to get useful data out of this experiment. Next, I’d keep doing this test on different days of the week, including weekends, and see how the results are affected by the day of the week.

We’ve also seen higher engagement recently with inline images on Twitter, so I’d do a follow-up study to test how Tweets including images perform at different times and on different days.

5. Refine your approach
Once you’ve got some useful data, you can refine your approach based on this. If you’re using Buffer, you can easily update your schedule so that you Tweet at better times based on your research.

Then, you can repeat the process on a regular basis, especially as your content changes and you get more followers, to make sure you’re always Tweeting at the most optimal times.

2.) The tools-based approach to tweet time optimization

There are a number of tools that help you come up with the best times to Tweet. Tweriod is a great example, which lets you run analysis on your own Tweets and those of your followers to see when you should Tweet more often.

tweriod

Followerwonk is another tool that we love at Buffer. I’m going to give you a run-down of how Followerwonk works and how it integrates into Buffer as an example, but you can obviously use whichever tool suits you best.

To start with, head over to Followerwonk and click on “Analyze followers”

fw analyze

Next, pop your Twitter username into the box and select “analyze their followers” from the drop-down:

fw start

You can also choose to analyze the habits of people you follow, but in this case we’re looking for the best timing to reach more of our followers. When your report is done, you’ll see a bunch of graphs to tell you more about where your followers are from, what language they speak and how many followers they have. The really useful one, though, is the one below which shows when your followers are most active:

fw chart1

If you use Buffer, you can take advantage of this by creating a Buffer schedule based on your Followerwonk report. Just choose how many times you want to post each day, and hit the “Schedule at Buffer” button.

fw buffer

I also find the graph of how active I am really useful. As you can see by comparing the two, most of my followers are active when I’m asleep:

fw chart

Guess I’d better get my Buffer account filled up again!

3.) The research-backed approach

Twitter is such a popular network for mobile users that it can be a bit tricky to lock down exactly when the best time to post is. Here are some suggestions from the research I’ve found:

Twitter engagement for brands is 17% higher on weekends.

If you’re tweeting from your company account, you might want to keep this in mind, especially if engagement is what you’re looking for. Buffer can help you spread out your tweets to post at the optimal times, so you don’t even have to work weekends to take advantage of this! Click-through rates are generally highest on weekends, as well as mid-week, on Wednesdays.

For B2B marketers, it’s not surprising to see in this Argyle Social study that weekdays provide 14% more engagement than weekends.

When we look at the time of day, retweets have been shown to be highest around 5pm.

When optimizing for clicks, research from bit.ly showed that 1–3pm is the best time to Tweet.

This study also found that Twitter gets the most traffic from 9am–3pm, which could be good or bad, depending on whether you can get your voice heard amongst the crowd.

Research from KISSmetrics, on the other hand, says noon and 6pm are the best times.

This could be due to lunch breaks and people looking for something to keep them occupied on the commute home after work.

There are lots of Twitter users who primarily use a mobile device—rarely loading up Twitter on their desktops. Twitter did an interesting study of these users and found that they are 181% more likely to be on Twitter during their commute.

They’re also 119% more likely to use Twitter during school or work hours.

4.) The “What do the Pros do?” approach

Lastly, you can try learning from the habits of others. We’re big fans of this at Buffer, and we try to keep track of what our favorite marketers are doing on Twitter.

If you follow successful people in your industry on Twitter, you can easily get an idea of how often they Tweet and which times lead to more engagement for them.

Guy Kawaksaki is a great example here, as he has some controversial Tweeting habits, but they are certainly working out for him, judging by his massive following.

In particular, Guy is known for posting the same content multiple times, and one reason he advocates doing this is to reach your followers in different time zones. He’s found that this increases the traffic to his content, particularly when Tweeting the same link several times:

The reason for repeated tweets is to maximize traffic and therefore advertising sales. I’ve found that each tweet gets approximately the same amount of clickthroughs. Why get 600 page views when you can get 2,400?

So posting your content in eight-hour intervals like Guy does might be an experiment you can try on your own Twitter account.

Of course, with this one, there’s a big caveat. The followers of people you look up to might be completely different to yours, making this approach less than helpful. But if you discover there is an overlap in followers, you can try copying their approach to see if it works for you.

 

Over to you: What are your takeaways on the best time to tweet?

We’re so grateful for the chance to dig into the stats from the many tweets that people choose to share with Buffer. The data is super insightful, both for sharing with others and for impacting our own social media marketing plans!

What did you notice from the stats here?

Did any of the results surprise you or get you thinking about your plans in a different way?

I’d love to hear your take on this! Feel free to share any thoughts at all in the comments!

Want more social media tips? Take our free email course!

I’ve put together a list of 25 practical social media strategies that work for us here at Buffer—and I’d love to share them with you via email. (We’ll also keep you in the loop with more social media tips!)

Join for free here –>

Image sources: IconFinder, Blurgrounds, Death to the Stock Photo, UnSplash

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Written by Kevan Lee

Content crafter at Buffer. You can find me online, tweeting about my writing process, or at home, second-guessing football coaches. Live simply, give generously, beat cancer.

  • http://www.travisbernard.com/ Travis Bernard

    This is great! Thanks Kevan!

    • http://blog.bufferapp.com Kevan

      Thanks a million, Travis!

  • https://pitcherific.com/ Anders from Pitcherific

    Added to our marketing insights list! Thank you so much Kevan (and the rest of the team)

    • http://blog.bufferapp.com Kevan

      Thanks so much, Anders! Really appreciate the kind words. Glad to know this might be helpful for you!

      • https://pitcherific.com/ Anders from Pitcherific

        Definitely is, I’m still quite new to marketing (that’s what happens when a designer/coder/founder needs to wear yet another hat) so I’m learning a lot from you guys 🙂

  • Xibis Ltd

    Really interesting.

    Just one note though, your text on best time to post for clicks contradicts the image for Central/Eastern European. I’m not sure which is right?

    Madrid, Rome, Paris, Berlin, etc. (Central European): 7:00 p.m.
    Cape Town, Cairo, Istanbul, etc. (Eastern European): 2:00 a.m.

    • http://blog.bufferapp.com Kevan

      Oh, thanks so much for the catch there! Apologies for the confusion I caused. Yes, you’re exactly right. The image has the correct times. I’ve just updated the text to match. The corrected text should be:

      Madrid, Rome, Paris, Berlin, etc. (Central European): 2:00 a.m.

      Cape Town, Cairo, Istanbul, etc. (Eastern European): 8:00 p.m.

  • Marlee Joseph

    Great tips! Thanks for sharing! Excited to try these with my business.

    • http://blog.bufferapp.com Kevan

      Hi Marlee! Thanks so much! Excited to be able to share this with you, and wishing you the best with your business!

  • http://www.marketingforowners.com/ Jon Butt

    Kevan, that is a fabulous post – as always – but, you seem to have forgotten to mention the UK or London. It’s quite a popular place, lol.

    • http://blog.bufferapp.com Kevan

      Great point, Jon! Definitely, so sorry to have left out the UK here. We found in the data that many Buffer users started out with a default time zone set to London – regardless of whether they lived in London or not! We felt this might have skewed the data a bit to include London/GMT – we just weren’t 100% sure we had accurate data for that time zone. Again, really sorry to have missed out on adding value for you and our GMT friends!

      • http://www.marketingforowners.com/ Jon Butt

        Thanks, Kevan. Your posts are one of 6 blogs in my fav Feedly group and you always deliver classics. Sorry that I sometimes scan through them too fast and miss the details 🙂

      • Pedro dos Santos

        Too bad. 🙁 Although, honestly I feel pretty conformable in assuming that at least for Portugal (same timezone as the UK) is pretty much the same as Central Europe. Similar behavioural patterns.

    • Thomas

      He mentioned how the London data isn’t clean in the European section because London time used to be the default Timezone for new Buffer users.

    • markokovic

      LOL!!! 🙂 btw he forgot to mention Ljubljana, Slovenia as well

  • http://learnit2earnitwithlynn.com Lynn Brown

    Appreciate the effort that went into this study. Interesting though that any time is a good time to communicate. Although knowing your audience will certainly determine what the best time is to share and engage. So focus on your marketplace, as you will get the general feel for when people are most responsive and receptive.

    • http://blog.bufferapp.com Kevan

      Great point, Lynn! Yes, there’s a lot of variation in the best times here. Love your perspective that it’s great to consider your specific market and audience. We thought it might be valuable to have the time zone data here for just this reason! Perhaps it might help if you were to know where your audience lives?

      • http://learnit2earnitwithlynn.com Lynn Brown

        Most certainly Kevan and for small business owners with local shops, that’s an easy one. But for me and other online marketers and entrepreneurs we reach out to audiences all over the world. I’m finding that using Buffer is a great way to ‘schedule’ the same valuable content or information across those time zones. So technology today brings a wonderful way to stay connected even on a 24/7 basis.

        • http://blog.bufferapp.com Kevan

          Right on, Lynn!

  • interviewactionkit

    Very valuable update to often debated issue – thanks for taking a data-driven approach! Looks like the bulk of activity is still in the late night/early morning hours (ie. not engaged with work/school). Now it’s up to us marketers to create content that would be attention-span-friendly for users at those particular times.

    • http://blog.bufferapp.com Kevan

      Great conclusion! Yep, love your takeaways here. 🙂

  • Scott Jones

    ER, UK? You’ve kinda missed one of twitters most active countries

    • http://blog.bufferapp.com Kevan

      Definitely! So sorry about that, Scott. Our data for the UK wasn’t quite as accurate as we would have liked; the UK used to be the default time zone for Buffer users, whether they were based there or not. We chose to omit it from this study, and I can totally see how that might leave things a bit incomplete!

  • http://www.slopefillers.com/ Gregg Blanchard

    Kevan, were the data points total engagement or engagement rate (i.e., favorites/followers)?

    • http://blog.bufferapp.com Kevan

      Thanks for the great question, Gregg! We went with total engagement for this.

      Love the idea to do engagement rate also! Maybe a future study? 🙂

      • http://www.slopefillers.com/ Gregg Blanchard

        Maybe, you’ve obviously got a massive sample size, but using rate tends to better represent the smaller fish in the pond. As is, larger accounts will have greater influence on the findings but with the vast majority of your users being smaller it might be worth some thought.

  • Denis m

    This is great statistics. I am developing my site http://saharatalk.com and i wil be needing traffic for it. I wanna employ this skills with buffer

    • http://blog.bufferapp.com Kevan

      Sounds great, Denis! Best of luck!

  • Andy Vale

    Interesting, I especially like how you’ve segmented it into types of response. The real best time to Tweet will still depend on your target audience though. For example, if you’re targeting chefs then you could Tweet until you’re blue in the face at lunchtime, you won’t reach them. A mix of tools+analytics & your own experimenting will help you find the one that works best for your own brand.

    • http://blog.bufferapp.com Kevan

      Great stuff, Andy! Yep, you make a really wonderful point – it’s best to know your audience and to discover the best times for you. Hopefully this data might give a few folks a good starting point!

  • http://www.LyndalCairns.com Lyndal Cairns

    Wow, that’s some brutal time-shifts for those of us on PST. Will try more 2am posts. Thanks!

    • http://blog.bufferapp.com Kevan

      Yes, great one Lyndal! Definitely grateful for social media scheduling tools! 🙂

  • http://www.datareign.com/ varma

    Super great insight on Twitter activity.

    Can you please share the information specific to Indian Standard Time (IST) ?

    • http://blog.bufferapp.com Kevan

      Hi there Varma! Thanks for the question! I got some advice from Julian on this one. We’ve not much volume of data for the Indian Standard Time zone, so our takeaways are a bit lean there. What it looks like from a high level view is that the most popular times to tweet are in the evening, if that’s helpful to know!

      • http://www.datareign.com/ varma

        That’s some valuable data. Really thanks for sharing the information.

        I think interpreting the available data from neighbouring Asian countries won’t be that correct in case of India.

  • http://www.mrsthreeinthree.com/ Karly Gomez

    Wow, I would have never imagined 2-3am being the best time for clicks and overall engagement! Looks like I will be altering my schedule…good thing I don’t have to actually be awake to post! LOVE Buffer.

    • http://blog.bufferapp.com Kevan

      Thanks for the note, Karly! Yes, we’re big fans of scheduling, too. 🙂

      • tracysestili

        But don’t you think it’s the trolls that are clicking at that hour?

        • chsweb

          Those “late night clicks” may be coming from a different country, where it is the beginning of their day. If you haven’t done it already, add bit.ly to your Buffer account so you can see where your clicks are coming from in your Bit.ly analytics.

          For example, here is where my clicks have come from over the past 7 days – these data comes from Bit.ly.

    • Dylan Enderlein

      High because that is also the time with one of the fewest Tweets. People up late have nothing better to do than scroll and click.

  • http://www.stevevance.net/ Steven Vance

    I’m curious about the division of weekday vs. weekend tweets.

    • http://blog.bufferapp.com Kevan

      Hi there Steven! Thanks for the great question. We’ve not quite done the analysis on day of the week for this data. We’d love to publish more studies like this, and I think day of the week is one that’s high on our wish list! Thanks for the nudge!

  • RJ Morrison

    Great post; surprised that 2:00 a.m. is the best time to tweet for clicks.

    • http://blog.bufferapp.com Kevan

      Definitely, RJ! Thanks! Yes, we’re looking forward to testing and scheduling some tweets then. 🙂

  • http://www.binaryoptioneurope.com/ Opzione Binaria Europa

    Wow super article!

    • Julian Winternheimer

      Thanks Opzione! 🙂

  • http://socialhighrise.com Mark Sorenson

    Thank you for sharing your insights! This is very interesting, indeed. We’ll be putting this feedback to the test to see if we see an increase in engagement for our http://socialhighrise.com clients.

    • http://blog.bufferapp.com Kevan

      Hi Mark! Excited for you to test this out. I’d love to hear what comes of it!

  • @cao_miguel

    Any data about Latin America? We have a lot of twitter users over here.

    • http://inversephase.bandcamp.com/ Inverse Phase

      Since Latin America shares time zones with other places in North America, you could probably adapt those statistics to the most appropriate scenario.

      And even though Brazil is an hour ahead of US/Eastern, you could probably add an hour to that time and call it good if you’re trying to reach that audience.

      • http://blog.bufferapp.com Kevan

        Yes, great question about Latin America. The data should be the same for all the North America time zones that overlap with Latin America. Sorry I only listed certain cities there, I can see how that might be confusing!

  • Katie Ferraro

    Super insightful study! Thanks so much for conducting this research – I will definitely be employing these findings in my social media plan. I am excited to see the results!

    • http://blog.bufferapp.com Kevan

      Yes, wishing you the best, Katie! Let us know how it goes!

  • Bhavesh Patel ✌️

    this is awesome and very insightful! great job Kevan!

  • terrinakamura

    Great article. Kevan, I didn’t realize you write for Buffer. Thanks for making this information available.

    • http://blog.bufferapp.com Kevan

      Indeed! Thanks for giving this post a look. Great to hear from you!

  • http://overviewbible.com/ Jeffrey Kranz

    Gents, this is fantastic. Thank you!

    Just curious: did you capture data on optimal tweeting times by day of the week? I ask because I notice people bringing similar behavior to both their Twitter feeds and their inboxes. And we all know that a Saturday morning email is different from a Monday morning email! Any awesome insights you can share on this?

    Thanks again for such a cool resource!

    • http://blog.bufferapp.com Kevan

      Hi Jeffrey! Great to hear from you. 🙂 Day of week would be a really awesome one to dig into. We’d love to do more data studies like these; day of week feels like a great one to tackle soon!

  • ADOLF WITZELING

    Interesting stats-could definitely be very helpful. Although 5 years seems quite a long period for statistics, especially since things are changing constantly in social media. Thanks for making the stats available for download.

    • http://blog.bufferapp.com Kevan

      You got it, Adolf! And yes, that’s a great point about the longevity of the study. We’ll definitely keep that in mind for future research!

  • http://inversephase.bandcamp.com/ Inverse Phase

    Lots of great data here. As it has been said before, it’s very important to take a look at the big picture (which is presented here) as well as your own personal results to reach the audience you’re targeting in social media. Thanks for all the work you put into this, Buffer!

    • http://blog.bufferapp.com Kevan

      Great stuff! Thanks so much for the comment!

  • http://www.lifeaslolly.com/ LollyJean

    You’ve done it again Kevan and Buffer team! Always sharing incredible insights. Now time to test for myself and hopefully see great results.

    • http://blog.bufferapp.com Kevan

      Woop! Thanks so much for the encouragement! Hoping for some great results for you!

  • Chris Bramley

    Interesting article and something I have been thinking of recently. I tweet x 3 a day, mostly related to my writing (as I’m at work for the rest. It was at what i thought was a sensible spacing – 10.30, 15.15, and 8.20 every weekday.

    I’ll give a try to 2.30, 20.15 & 23.30 and see how it works on UK timezone… but an interesting consideration is how it will interface with the Twitter passthrough to Facebook, which DOES have a different interaction level.

    • http://blog.bufferapp.com Kevan

      Yep, great point Chris! I’d love to hear what you discover with the Facebook crossover.

  • http://www.crazygeektalk.com/ Darin

    All of this data is useless without being able to target followers by time zone. So until then twitter post times are still a dart board.

    • http://www.crazygeektalk.com/ Darin

      .. and I don’t mean to negate the awesome stats just shared. Very cool.

      • http://blog.bufferapp.com Kevan

        Totally understand your point, Darin! My best workaround for the time being is to put my Twitter account through a tool like Followerwonk and see where all of my followers are geographically, then I can try to base some tweet times off that. It’s somewhat inexact still!

        • http://www.crazygeektalk.com/ Darin

          If only twitter had circles we would be in good shape!

  • Bhavesh Patel ✌️

    this is VERY insightful! thanks and great job @kevanlee:disqus

    • http://blog.bufferapp.com Kevan

      Thanks, Bhavesh! Cheers!

  • http://www.SocialQuant.net SocialQuant

    This is an amazing study.

    We’re always testing and watching our data/analytics to see what gets the best results. I’m blown away at the middle of night time for clicks. Though we Tweet 24 hours a day, our highest click times are during daytime hours and decrease as the night progresses. Likewise our conversion for email captures are highest during the day from Twitter and decrease as the day moves into night (except Fri night into Saturday morning).

    Twitter sends us around 6000 visits a week to our site so we monitor this closely. After reading this I’m going to run a few more CTA tweets in the later evening to see how they do the next 7 days. Again awesome post.

    • http://blog.bufferapp.com Kevan

      Awesome stuff, I’d love to hear how those experiments go!

      Yeah, the late-night click data was really interesting to us also. Those times have always been quite high for our Buffer tweets, so the data seemed a bit validated in our specific case. One thought I had also is that the volume of night tweets is a bit lower so there’s more chance for an outlier to skew the average higher. We ran some additional data views (medians and whatnot) and what we’ve shared here seemed to be the strongest takeaway.

      Thanks for the comment!

  • http://brilliant-insane.com/ Mark Barnes

    I wonder if niche audience has anything to do with this. Most of my followers are educators, and I find the best times to tweet for link clicking are 4PM and 7PM ET. I’ll have to run a more thorough test. Thanks Kevan. This is very cool info.

    • http://blog.bufferapp.com Kevan

      Hi there Mark, thanks so much for the comment. Really interesting observation. Would the theory be that educators might have more bandwidth for checking Twitter after the school day is over? I’d love to hear more about what you find!

  • Janet Ursel

    Very interesting! Looking forward to your analysis of Facebook and Google+ too. I seem to recall you had similar results for engagement on your own Facebook page, late evening being a great time for engagement. I’m guessing that on both those platforms, late-night posts are high in the feed of both night owls and early risers.

  • Allison Cooper

    Love this study, thank you so much for writing it up and sharing the data and your insights!

    One thought/question — sorry if I missed this in the post, but I’m curious since this is studying tweets sent through Buffer, I wonder if other users (who use Buffer for personal use) have similar behaviors to myself that involve posting tweets I find during my lunch break through buffer, but posting most tweets during other times of day NOT through Buffer? Would this affect the findings at all? Are there many users who use Buffer more at certain times of the day, and tweet without any buffering at other times of day? Were the sample tweets only from users who exclusively tweet through Buffer, or do many users do a mix of buffered and direct tweeting? Of course, this wouldn’t affect the engagement data, just maybe the popular-times-to-post rates. Again, thanks so much for sharing, I’ll pass this on to some friends for sure; the linked tools etc are also very cool, and I’m excited to learn where further research about this goes.

    More about my usage in case my description above didn’t make sense: I love buffer because I can spread out my irregularly-concentrated lunchtime tweeting-time (when I’m catching up on articles and want to share them, etc.) to not overwhelm my followers’ feeds (legit problem — friends would text me to stop tweeting because a bunch of my tweets in a row would clutter their feed — now fixed, thanks to Buffer!!). As for other tweets, I might post about an event I’m at in the evening and intentionally not share it through buffer because I want it to be realtime to participate in the event.

    • http://blog.bufferapp.com Kevan

      Hi there Allison! Thanks so much for the thoughtful comment. It’s so neat to hear your use case here, and yes, my sense is that many people share a similar workflow as you’ve described! One way that I’ve observed is that some folks use Buffer to schedule content-related tweets (tweets with a link, or a quote, or an image) and then tweet directly via the Twitter app their more stream-of-consciousness or live event thoughts. (There’s an option in Buffer to “Share Now” in case you’d ever want to see the stats for these real-time tweets in your Buffer dashboard!)

      The data here did not make any distinctions between these different types of users – we looked at all Buffer users regardless. 🙂 What I tried to do with some of the interpretations here was to split out engagement stats like favorites/retweets from engagement stats that included clicks. I thought this might possibly show some different best practices if you’re simply sharing thoughts or real-time tweets as opposed to content-driven tweets. Not sure if I was terribly clear here, I’d love to know how that sounds to you!

  • http://www.BenBrausen.com/ Ben Brausen

    Great data! This really helps illustrate a number of points I was recently discussing with some other social media marketers. The top times for activity aren’t always the best times to get response. Posting times can be chosen based on what the desired outcome from the messaging is (clicks, retweets, etc).

    What do you believe the reason is that posts so late in the night see such high performance? Is it because these are some of the first we see in our timeline when we first load it in the morning (assuming we don’t follow a crazy number of people)? Competition is much less? Or a combination of both?

    • http://blog.bufferapp.com Kevan

      Hi Ben! Thanks so much for the comment. Cool to hear you were just discussing these topics! 🙂

      Yes, I think you’ve got a great intuition for this. My best guess is that it’s likely due to a combination of things – 1) lower volume of tweets at non-peak times, leading to greater visibility, 2) possibly more engaged users spending time logged into Twitter in mornings/evenings, 3) Twitter’s “what you missed while away” feature, 4) the late-night tweets being on top of your timeline first thing in the a.m.

      If I had to say one factor that was largest, my gut would be to go with the volume of tweets theory!

      • http://www.BenBrausen.com/ Ben Brausen

        Makes sense to me. Thanks again for taking a look into this huge pile of tweets to find all of this.

  • Jyoti Arora

    Great information. I’m definitely going to use it to set up my new Tweeting schedule. Thanks!

    • http://blog.bufferapp.com Kevan

      Wonderful to hear, Jyoti! Thanks so much. 🙂

  • dklebedev

    This is a game of dazzling numbers. Any given audience varies by habits and only experimenting will help. Entertaining post with no practical takeaway.

    • http://blog.bufferapp.com Kevan

      Thanks for the thought here! Totally understand your point, and agree that yes there’s lots of variability here for best practices when it comes to individual profiles. Love your advice for experimenting. That’s key! Thanks for sharing this perspective. 🙂

      • dklebedev

        Thanks for the reply. Loved the article and the study.

  • CT

    Does your study differentiate between B2B, B2C and non-business?

    • http://blog.bufferapp.com Kevan

      Hi there CT! Great question, we didn’t segment the list between B2B/B2C/non. Sounds like a great one to dig into with further studies!

  • Annie Craton

    Interesting info! Thanks!

    • http://blog.bufferapp.com Kevan

      Thanks, Annie!

  • http://simplyvarnell.com/ Hotty Toddy

    Did you capture any data regarding these times as they relate to industry or type of audience? For businesses, each target audience is different and can’t be lumped into global times like those in the article. However, it is very interesting data and a great article.

    • http://blog.bufferapp.com Kevan

      Thanks for checking on this! Yeah we didn’t quite segment by industry or type for this study. We’d love to do more studies in the future, and this feels like a great area to explore deeper! Thanks for the idea!

  • Lisa Calhoun

    Hey, since we like sharing at my PR firm Write2Market, this will move our tweet schedules a bit later in the day to early evening when we really want engagement. Thank you for sharing. A lot of this is about Tweeting specifically–sure would be curious to see comparisons with other platforms. Hint, hint!

    • http://blog.bufferapp.com Kevan

      Haha, hint hint wink wink. 🙂 Yes, we’d love to do more studies like this. Any platforms you’d be especially keen to see?

      • Lisa Calhoun

        I’m in b2b tech PR, so LinkedIn pushes a lot of sales for our clients at Write2Market. I wouldn’t be surprised if post sharing/click-thru was contra-cyclical to Twitter but you never know… Wait, you DO know! 😀

  • Priyanka Agarwal

    Could you please share the best tweeting times for India? Thanks

    • http://blog.bufferapp.com Kevan

      Hi Priyanka! Sure thing, we don’t have a very large set of data for the India time zones, so it’s a bit hard to draw any conclusions there. From what I’ve seen of the data, it appears that the evening is the most popular time to tweet in India, if that might be helpful to know!

  • Mireille HILGENBERG

    Can help and save waste time ! Thank you very muche for this very interesting investigation….

    • http://blog.bufferapp.com Kevan

      Hi Mireille! Wonderful to hear from you. Thanks so much for the comment!

  • http://www.bridgetwillard.com Bridget Willard

    Why are people clicking on blogs at 2am?

    • http://blog.bufferapp.com Kevan

      Great question, Bridget! Yeah that one has us really curious also. One thought that comes to mind, since the data here is localized there might be some instances where 2am local time is a bit more of a reasonable hour elsewhere – e.g., 2am in New York is 11pm in San Fran. That’s one theory that’s been floating around in my head (I’d love to hear any ideas of yours also.) Thanks for the comment!

      • http://www.bridgetwillard.com Bridget Willard

        Or 2am PST is 5a EST. curious.

  • http://seedfunnel.net/ Patrik Larsson

    This is perfect! Will definitely let me try new things with Buffer 🙂
    Thanks, Kevan!

    • http://blog.bufferapp.com Kevan

      Awesome, so happy to hear it Patrik! Thanks!

  • http://www.musttriumph.com/ Sam Yang

    Please do one on Facebook next!

    • http://blog.bufferapp.com Kevan

      Definitely, Sam! We’re excited to do lots more of these. Facebook feels like a great one to explore!

  • Kristin Austin

    Would love to see a just Australia. We’re a very different market from Asia.

    • http://blog.bufferapp.com Kevan

      Thanks for the comment, Kristin. Great point! We’d love to see what we can do with country/state-specific research moving forward. Thanks for the nudge!

  • http://longboardsusa.com/longboards/ Longboards USA

    lots of insightful numbers, thanks for sharing.

    go shred and have fun,
    Rene

    Longboards USA

    • http://blog.bufferapp.com Kevan

      Thanks, Rene!

  • Kwei Quartey

    2 a.m. to 4 a.m! Wait, these are people actually awake at these times and are on Twitter??

    • http://blog.bufferapp.com Kevan

      Hi Kwei! Thanks for the comment. Excellent question! Yeah, seems a bit counterintuitive to me also. I think one theory I’ve thought of is that 2am to 4am can often mean a bit more reasonable of a time in other time zones – 2am in New York is 11pm in San Francisco, for example. Not sure if that’s the reason why, just an idea!

      • Paul Hile

        Could it also be that between 4 am – 8 or 9am (whenever usage begins to pick back up) there is minimal activity, therefore anyone logging on in the morning are seeing those tweets?

  • Mariellen Ward

    You left out India?

    • http://blog.bufferapp.com Kevan

      Hi Mariellen! Thanks for the comment. Yes, sorry we didn’t include India here – our dataset for those time zones wasn’t quite deep enough for us to find any confident takeaways. If things turn up later on, we’d be happy to share!

  • Viv McDonald

    I had to re-read some of the sections to make sure I was seeing it right – 2am the best time – for clicks and engagement! So less competing noise I suppose. Most popular time is really interesting – here in Australia it’s quite different to elsewhere. Thanks for the article, lots of food for thought.

    • http://blog.bufferapp.com Kevan

      Hi Viv! Thanks for taking such a close look here. Yes, from what we saw, there were some counterintuitive suggestions here for sure. A few thoughts that came to mind for me: – 1) lower volume of tweets at non-peak times, leading to greater visibility, 2) possibly more engaged users spending time logged into Twitter in mornings/evenings, 3) Twitter’s “what you missed while away” feature, 4) the late-night tweets being on top of your timeline first thing in the a.m.

      • Viv McDonald

        My goodness – you are a dedicated responder! A reply to everyone’s comment is monumental I think! That’s engaging with your audience 😀 And I think you might be right about the ‘what you missed while away’ feature. lots to think about. cheers

  • Ian Gray

    thanks for this information. Very solid and some surprises.

    • http://blog.bufferapp.com Kevan

      Thanks, Ian!

  • Lucy

    love this! am curious though… what’s the best time to tweet for clicks in just an aussie market?

    • http://blog.bufferapp.com Kevan

      Hi Lucy! Great question. Sorry we don’t quite have country-specific data here. It’s something we’d love to explore fully later on! (We’ll for sure let you know when we do.)

  • JBR

    This is fantastic information. As a new business user of twitter, this is extremely helpful and I navigate my way. Thank you!

    • http://blog.bufferapp.com Kevan

      Thanks, JBR!

  • http://www.iamjoycee.com/ J.P. Bibby

    Thanks for sharing this. Aboslutely helpful.

    • http://blog.bufferapp.com Kevan

      Sure thing JP! Glad you enjoyed it!

  • http://tatumweb.com/blog/ Rich Tatum

    I’ve long noticed that my late-night tweeting seemed to garner more interactions, but never gave it much thought. Now I know why, thanks!

    • http://blog.bufferapp.com Kevan

      Awesome to hear this, Rich! Great to know there’s some validation for this data in your experience. 🙂

  • http://www.naotech.com.ph Naotech Inc.

    Wow. Thank you. This is so helpful especially for a starting business like us.

  • http://ab27.co AB

    Whoever said ‘a dog is a man’s best friend’ should have looked at a corollary: ‘data is a marketer’s best friend’!

    Personally, I was always wary of the automated schedule because I worried whether it would be effective. At Buffer’s suggestion, I even used Followerwonk and Tweriod, which are integrated with Buffer, but didn’t get quite the results I’d hoped for. The best engagement I’ve had has been since I used the Buffer Optimisation beta tool to synchronise my schedule. So, kudos on that!

    I find a couple of things interesting:
    * Hong Kong time is a (Top 10) popular timezone – which means you’ve got quite a few users in this general area.
    * If we know the best times are x, what would it take for Buffer to change it’s suggested schedule for first time users to the same x?
    * Could the Buffer product add the scheduling tool as the first step when a new user signs up?

    • http://blog.bufferapp.com Kevan

      Hi AB! Awesome to hear the optimization tool has worked for you! That’s so great to hear!

      And yes, totally love your suggestions here for incorporating this data into the schedules with Buffer. That feels like a great one for us to explore further! I’d love to know what would be most helpful: Would you see it as suggesting the best local times for you to tweet given a certain number of queue slots you’ve chosen?

      • http://ab27.co AB

        Hey!

        Considering the optimisation tool does have the capability to analyse my audience & the number of times I’d want to tweet – to suggest the best times to do so; that would indeed be perfect.

        When are you going live with the new layout of slots to be filled that we saw on Joel’s twitter, if at all?

        Cheers!

  • Ishita Ganguly

    Great article Kevan. Clicks are the most important factor for content marketers and the time slot between 2 and 3 am is something that I never tried. I will surely change my strategy based on the study.

    Cheers!

    • http://blog.bufferapp.com Kevan

      Glad to hear it, Ishita! I’d love to know how the 2am test goes for you!

  • lovarzi

    Hi Kevan, Thanks for this post. Could not come at better time as I have just subscribed to Buffer. May I know if there is any such thing as a Guide / Feature List or How to Guides which I can read. Or list of most popular posts on this blog ? I could not find anything other than FAQ page.

  • http://mindleadersuganda.blogspot.com Mwebya Fred

    Huge Thanks Kevan. I would have known the best time to tweet in Africa. Great job done.

    • http://blog.bufferapp.com Kevan

      Thanks, Mwebya!

  • http://pennyspoetry.wikia.com/wiki/R.K._Singh R.K.Singh

    I have been using Noon to Night time for tweets yet I haven’t received as many clicks as I always desired.

    • http://blog.bufferapp.com Kevan

      Hi there RK, thanks so much for sharing your experience here. Definitely makes sense, we’ve found on an individual level that results may vary based on audience. I’d love to hear how things go for you if you end up testing other times!

  • http://www.mattantonino.com Matt Antonino

    I think for the difference in Aussie times vs others, it’s mainly because we’re well aware of the time difference between us and the US. So 10 am here is still 8 pm EST. If we’re posting for two audiences, that window between 8 am and noon is best for us. That 12-1 window that is so popular worldwide is 10 pm EST for us so we avoid that.

    Interesting stats all the way around. I will have to test some of these for my own audiences.

    • http://blog.bufferapp.com Kevan

      Great insights, Matt! Makes a lot of sense. Happy testing!

  • Eric Mwangi

    I am very impressed with the statistics. Out of curiosity any data in regards to best time to tweet or best time to get engagement in Africa (To be specific Kenya).

    • http://blog.bufferapp.com Kevan

      Hi Eric! Great to hear from you. 🙂 Thanks, yeah we have a small data set for that part of Africa, so my best guess is that the recommendations would be similar to the ones for the Eastern European time zones mentioned above. Hope that helps!

  • Overy1954

    < ✜✱✪✪✲✜.+bufferapp+ ********* ….. < Now Go R­e­­a­d M­o­r­e

    14

  • Yasser

    Thank you Kevan for the awesome information.
    As a news provider here in Dubai (Middle East), we tweet 24hrs covering the local and world news. We found the best time for tweet engagement between 11:00am and 02:00pm. Most of the retweets came at 08:00pm till 01:00 am.
    Thanks again.

    • http://blog.bufferapp.com Kevan

      Really cool to hear your stats, Yasser! Thanks so much for sharing!

  • Rory

    I think saying that posting at 2am for best click engagement is a bit misleading don’t you think? This needs to be cross referenced with user profiling to make it really relevant, ie what age are these people and what do they do? The people up at 2am are unlikely to be most people target audience.
    BTW I think the research is great and worthwhile, it just needs some further data to go with it to make it really excellent.

    • http://blog.bufferapp.com Kevan

      Ah, thanks so much for the thoughts here, Rory! Makes a lot of sense. Yes, the data is quite demographic-blind in that sense, so I can see that adding some more detail could be quite helpful. We’ll see if we can dig any of this up and report back!

  • Omer Yarkowich

    Is it just me, or nights just got more interesting now?

    • http://blog.bufferapp.com Kevan

      Indeed!

  • Sandra Alvarez

    Great data here although I am disappointed at the lack of UK information. I understand you have to clean it up but maybe you could’ve waited until you had it cleaned up to present this. I live in London as was hunting through this article for a good time to tweet…so now what? I tweet in European Central time? That’s not really accurate, is it? I run a business that is in North America (EST time zone) and the UK, so this factor is important. I can only apply some of this to our business and I’m still left in the dark as to when to post to my UK users (which, is a substantial amount of my traffic!). Thanks for trying. I’d love to see the UK GMT stats someday. The rest of it was great information. Well done.

    • http://blog.bufferapp.com Kevan

      Hi there Sandra! Yes, so sorry we failed to deliver the UK times, I know that’s a very key part of the social media landscape. We’re looking for ways to improve this data moving forward, and your feedback is so very helpful!

  • sportpassion.de ⚽

    Great study, but I’m curious about the results. You
    wrote that posts between 2am and 3am get the most engagements. Does this mean
    percentage wise, or by sheer number?
    Percentage wise could be the result of
    fewer tweets in general in that time frame, so the percentage for engagements
    goes up. If your results are based on numbers, they are really astounding.

    • http://blog.bufferapp.com Kevan

      Yep, great question! Thanks so much for digging into the specifics here. 🙂 My interpretation of the data is that the “most engagements” is on a per-tweet basis, so generally-speaking you could expect more clicks+faves+RTs+replies by tweeting later at night/early morning. From what we could tell from the data, there are more overall (total) clicks and retweets to go around during the day and also more tweets to split those among, which makes for a smaller per-tweet engagement.

  • http://www.matthewbarby.com/ Matthew Barby

    As always, fantastic article, Kevan.

    I thought the analysis was really interesting but I think it’s important here that people people put these results into the context of their own campaigns. Simply sharing out content at a time that, on average, gets more engagement will not always be the right thing to do.

    Each Twitter following is different and each campaign should be treated accordingly. I’d love to see a study that segments each individual audience group or industry to get a better profile of when is best to speak to certain types of people, rather than a generic ‘best time’.

    Great article though, thanks.

    • http://blog.bufferapp.com Kevan

      Hi Matthew! Great to hear from you! Thanks so much for the thoughts here. Yes, keen to improve this data moving forward and to make it as helpful as can be. I’d love to know if there are any specific types of segments you think could be useful. I see you mentioned industry as one idea. Would bucketing the results by follower count be useful at all?

  • okewole olayemi samu

    This gives a lot of insight for all time zones except Africa and Nigeria in particular. Please can you share your research outcome in our time zone?

    • http://blog.bufferapp.com Kevan

      Yes, so sorry we weren’t able to relay any results from those areas in particular. Our data for Africa/Nigeria is a bit lean, so we couldn’t quite get any takeaways we felt fully confident in sharing. My intuition is that the Central & Eastern European times would be the best bet for any recommendations here!

  • http://sandcurves.com/ Vernon Swanepoel

    I’m always curious about what this kind of data tells you.

    I’m closest to Cape Town time (in Namibia). Since favorites and retweets can be from a global audience (which interests me), I’d rather see data that isn’t corrected for local time. What I mean is, no matter where you are on the planet, what time (pick any time zone) is the overall best for engagement.

    I wonder if data for somewhere like Cape Town isn’t affected by factors elsewhere. My best time for engagement might reflect a good time in New York, for example.

    Just sharing my thoughts. I guess that goals vary. Who you hope to engage with varies. And getting to those kinds of numbers would be rather tricky.

    • http://blog.bufferapp.com Kevan

      Hi there Vernon! Thanks for the comment, it’s great to hear from you. Yes, I think what we hoped to show here with these worldwide chart is that they’d be relevant to whatever time zone you’re in. So in general, the best time to tweet for clicks is 2am, whether that’s 2am in San Fran, New York, Berlin, or Cape Town. Sorry if I wasn’t clear in the blog post! I’d love to answer any questions that might bring up. 🙂

      • http://sandcurves.com/ Vernon Swanepoel

        Kevan,

        Your blog post is very clear. It was me who wasn’t clear.

        You say:

        “Further, we segmented the results according to time zones, based on the assumption that the learnings might be more actionable if they could be specific to exactly where you live and work.”

        My question is, what if you didn’t. Let’s say I live in the most remote time zone on the planet. Or, even better, I was tweeting from the international space station.

        And, theoretically, I don’t have a target audience beyond “people on twitter”. It would be interesting to know when globally each day is the best time for engagement.

        I’m sure for a local business you want to say “what is the best time to get engagement in my region”. But if you’re in global news, an expat or in a global market, what would be the one or two times GMT when absolutely the most retweets are happening on twitter.

      • http://sandcurves.com/ Vernon Swanepoel

        Kevan,

        I’ve been holding myself back from asking this, but I’m sure it’s on the minds of thousands of readers of this post.

        Would there be any way you’d consider sharing the raw data? It would need to be cleaned for privacy and you could choose some subset if the data.

        From a purely business point of view there can’t be much benefit for you. Though you could ask people who use it to share their scripts on github where you might get some unexpected insight yourself.

  • Amy

    This is very interesting. Often, we see trends for our clients that are outside the norm largely due to the niche our clients fall into. However, pretty much every tweet we’ve ever sent for ourselves our a client is included in this study! We’re going to play with schedules a little bit based on this and see what happens. Appreciate the insights!

    • http://blog.bufferapp.com Kevan

      Wonderful to hear, Amy! I love your approach with the data – take it as some good food for thought and try some tests. Such an excellent idea. I’d love to hear what you notice in your findings!

  • Albert Freeman

    I can see how these findings would be incredibly useful for global brands. But I work in local government, and most of our target audience are on the same time zone. I’ll try scheduling a few tweets between 2am and 4am, but I very much doubt I’ll find we get many clicks. I’m prepared to be proved wrong though.

    It would be useful to know how you analysed the tweets, Kevan, so I can do a similar analysis of our tweets and find exactly what would be best for us. Did you crunch the numbers in a spreadsheet?

    • http://blog.bufferapp.com Kevan

      Hi there Albert! Thanks for the comment, it’s great to hear from you. Totally understand where you’re coming from with this – it’s possible that the people clicking from 2am to 4am might not be your target audience (since your audience – very local – is likely asleep!). Is that right?

      For data analysis, I was very grateful to work with our data scientist Julian to get the results. It’s all a bit beyond me! I believe he used a program called R (http://www.r-project.org/). If it’s helpful at all, we did run a similar analysis for just Buffer’s tweets awhile back. Methodology is here: https://blog.bufferapp.com/twitter-analytics (and it does involve spreadsheets!)

      • http://sandcurves.com/ Vernon Swanepoel

        The r project link needs fixing.

      • Albert Freeman

        Right. Most people here will be asleep, and people here are our target audience. We may get nocturnal clickers, but what really matters to us us relevant clicks – quality over quantity.

        Project R looks a bit beyond me too to be honest..! I’m happier with Twitter analytics and spreadsheets. I did read your Twitter stats blog post last year, but now seems like a good time to re-read it. Thanks.

      • cheryl moody

        Great report – awesome starting point for more analysis. I love the aggregate overview, but I’d also like to see a breakdown by industry since I think that “News” “B2B” and “Ecommerce” etal sites might have significantly different engagement results.

  • Jim Wilbourne

    This is an excellent report.
    It looks like I should do a bit more experimentation for my social strategy. It also goes to show that you should adjust your times based on the particular form of engagement you’re looking for and who you’re looking to get it from.
    Excellent report and I hope you guys create some follow up articles that further dissect this data and what it means for buffer users.

    • http://blog.bufferapp.com Kevan

      Definitely, Jim! Thanks so much for the vote of confidence, and we’d love to explore some further studies here. Anything in particular you’d be keen to see?

      • Jim Wilbourne

        I’m not sure if it’s possible based on the kind of data you can access, but it would be interesting to breakdown content types (links, text, images) or more specific demographic information.
        It may also be interesting to look at specific profile case studies for accounts at various levels of popularity (with permission, of course).
        I would also appreciate this same type of data for G+ and Linkedin if that’s not in the plan.

  • http://danscharch.com/ Dan Scharch

    People act much different between the workdays and weekends. I’d imagine social media is much different outside the cubicle. Can you speak to that a bit?

  • Ryan Sawrie

    Any insight into the type of content that is receiving clicks between 2:00 and 3:00am?

    • chsweb

      Ryan, recently I’ve been using unique hashtags to tag my Tweets so I can identify them in the CSV downloads provided by http://analytics.twitter.com. For example, I’ve been testing out how well a “Verb, Target, Outcome” tweet composition performs by tagging them with #vto. Once the CSV is downloaded, I can run it through a few filters to see how the #vto tweets do vs the same tweet without the #vto composition.

      The Twitter Analytics website also shows you your most engaging Tweets from the past 6 months. While that will only be specific to your Tweets, and not the nearly 5 million assessed here, you will find very similar results to the rest of us.

      Come up with a simple, short hashtag you can use to identify your tweet types and it will help you learn what works best when it comes time to crunch your Twitter data.

      All that said, I second your question – what content did the best. The first next step would be to identify and categorize “content” into something that can be measured against – perhaps along the lines of how analytics.twitter.com organizes the interests.

  • http://hedstrominternetconsulting.com/ Steve Hedstrom

    I really like your point on how the best time in a time zone most likely corresponds to a high engagement time in other countries. Your data-backed research is awesome Kevan/Buffer! Thank you and have a fun Friday! 🙂

    • http://blog.bufferapp.com Kevan

      Cheers, thanks Steve!

  • http://ipankajsharma.com iPankajS

    Awesome research and statistics Kevan!

    1 Tweet – 3.6K Impression – 107 Engagements

    Hadn’t I been using @Buffer for my social media campaigns, I could never have achieved these wonderful numbers. Though the impression count is little less as my tweets get 5K impressions in general (those posted
    by me, not automatically curated and scheduled.)

    I’ve been using Buffer for couple of years now. Once I got introduced by Kevin about best time to schedule and using followerwonk to sync with the best time to tweet. Since then, I had been using it and it brings wonders.

    I wrote 12 ways to use twitter as social media marketing tool http://hackinterns.com/twitter-as-social-media-marketing-tool/1005 and it got wonderful response from the readers. Besides my efforts to write the wonderful post, buffer did amazing job in scheduling for all four media
    (twitter, facebook, google plus & linkedin) for 7 times in next two weeks, that too in one click – Greatest ease that I could have ever got.

    It is important to make your ideas reach to the right audience (twitter does it) and at the right time (buffer makes it great). Besides great content, these two things work magnificently well.

    PS: I don’t endorse any app in any way. Just sharing the love that I have for the app I use by Buffer. 🙂

    • http://blog.bufferapp.com Kevan

      Great to hear this, and thanks so much for sharing your results! Awesome to hear you’ve found success with an optimal schedule, that’s such great validation.

  • http://www.meudinheirominhasregras.com.br Daniel

    Amazing research, as always!
    Next step: let me choose if I want to share in Buffer for clicks, engagement or views, and then Buffer will buffer my post for the appropriate time.

    • http://blog.bufferapp.com Kevan

      Whoa! (mindblown) Thanks for the awesome idea, Daniel! That’s fascinating!

      • SicaBixby

        When tweriod worked I adjusted my posting schedule monthly. But it’s not worked in years and the other tools out there are worthless. Daniels suggestion is much needed.

    • Jim Wilbourne

      This is a great idea, Daniel!
      I’m in love with it!

    • Troy

      +1

    • John Santin

      Yes! +1

  • http://sarahannehayes.com/ Sarah Anne Hayes

    This is fascinating and is making me rethink the most common times I end up tweeting things! Since there seems to be more engagement overall (including clicks and replies), it seems that it’s almost better to post something like a blog post for Wednesday morning on Tuesday night so it gets a jump start on interaction and engagement. Thanks for putting this all together! It’s really neat to compare all the time zones and such.

    • http://blog.bufferapp.com Kevan

      Awesome strategy idea, Sarah! Yes, that makes a lot of sense to me. Publish things early on so they can gain early traction and get a head start before the day begins! We publish Buffer blog posts at 5am San Fran time, and now I’m thinking we could perhaps go even earlier!

  • Astrid Machado

    Thanks for considering South América in your report #NOT

    • http://blog.bufferapp.com Kevan

      So sorry for the exclusion there, Astrid! I definitely could have done a better job mentioning a broader list of places. We found that the data for South America time zones was not quite as full as other places, so we didn’t feel 100% confident in drawing conclusions there. My intuition is that any recommendations for South America would follow closely to the corresponding time zones in the US, probably Eastern Time mostly?

  • Lucie

    Great post Kevan. I will be sure to test it out.

    • http://blog.bufferapp.com Kevan

      Thanks so much, Lucie! Would love to hear how your tests go!

  • donnasvei

    Hi Kevan,

    I would love to see this fabulous analysis done month by month. I’m curious about the seasonality of social media usage.

    Donna

    • http://theiuvo.com/ Sandra Iuvo Omega Limited

      That would be very interesting to see. I assume summer period could be the best time to generally be active on social media (with all the vacation breaks and holidays).

  • hussainweb

    Thanks for the awesome article and stats. I’m wondering if you have plans to analyze data from India. I couldn’t really match the culture with any other regions listed and hence not sure of what would be the best equivalent. I would love to see you cover India as well.

    • Julian Winternheimer

      Thanks so much, I’m glad you found this information useful! We would love to have covered India in this analysis, but unfortunately the Tweet volume from India (sent with Buffer) was a bit small for us be very confident with the findings. I’m sorry I don’t have a better answer for you, but I really appreciate the suggestion! 🙂

  • http://www.LYFsolutions.com.au LYF Solutions

    This is really good data! One lesson I’d have to add would be that although the sample size is large, you might not find the times to post work for your account. Your audience may differ in the way it engages with you, based on demographic or other differences. That is not to say you should give it a go, social media is all about experimentation. Just don’t rely on the data for everything. Thanks for sharing Kevan. Look forward to seeing more data insights from you guys!

    • Julian Winternheimer

      This is a really great point! We took the aggregate of all of the Tweets sent out in the different time zones, which could include any number of industries, verticals, and personal preferences. Definitely still important to experiment and discover what your audience’s preferences are. 🙂

  • http://VAstaffer.com J Hunter

    Wow, what POWERFUL research. That is something that everyone in marketing needs to know. I am SHOCKED by the results, it is exactly opposite of what I thought. It’s time for a very large blog post to go out to our clients about this and how they can take advantage of it. Thanks! – J Hunter | Virtual Assistant Staffer

    • Julian Winternheimer

      Hi there J, I’m glad you found it helpful! It is interesting that the average amount of engagement is almost inverse-related to the most popular times to Tweet isn’t it? 🙂

  • cassie cruise

    this info is contradictory, it is not useful, nor is it notable,but mostly it sounds like blah,blah blah & you would spend an hour figuring time zones

    • Julian Winternheimer

      I’m so sorry for the lack of clarity in this post Cassie! Is there anything in particular I could perhaps try to explain in a better way to you?

  • E-MusicMaestro

    When you say 2 – 3am you do not make it clear which time zone your are referring to – please clarify. Reading further comments I see that you have omitted the UK – very disappointing to know that you have forgotten your UK (paying) subscribers.

    • Julian Winternheimer

      So sorry for all the confusion about the time zones! We reached the conclusion of 2 – 3am by combining the 10 separate time zones into a single dataset, and averaging the amount of clicks that tweets sent each hour received. We omitted the UK from this analysis because many Buffer users were defaulted to the GMT time zone, and many actually did not live in this time zone, so we did not feel confident enough with that particular dataset to include it in this study. I hope this helps a bit! So sorry for my lack of explanation in the blog post!

  • Scott

    He mentioned that 3AM is the best time for overall engagement but then went on to say that retweets & favorites are lowest at this time…..I recognize there is more to engagement than just retweets & favs but did anyone else find this contradictory?

    • Julian Winternheimer

      Hi Scott, thanks for pointing this unusual contradiction out! We also found some of the findings quite surprising, and are currently double and triple checking the datasets for outliers that may have caused these unusual results. Please bear with me for just a bit longer – keen to update you with more information and better explanations! 🙂

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  • John Chapman

    As an author, writing in English and based in the UK I find my market is global. When one English speaking area is going to sleep, another area is waking. Clicks on my tweets vary from day to day but most in the UK come between 5:00pm and 6:00pm (UTC 0) and between 1:00am and 2:00am. I’ve always presumed I’m picking up commuters on their way home after work and late night readers.
    It helps to know which are the English speaking countries and what theit time zones are:

    UTC -10
    Hawaii

    UTC -9
    Alaska

    UTC -8
    California (Amazon) Pacific time

    UTC -7
    Arizona, Mountain time

    UTC -6
    Central time

    UTC -5
    Eastern time

    UTC -4
    Atlantic time, Halifax

    UTC -3
    3:30 Newfoundland

    UTC -2

    UTC -1
    Azores

    UTC
    0
    UK, Ireland, Coordinated Universal Time

    UTC +1
    West Central Africa, Nigeria

    UTC +2
    South Africa, Germany, Sweden, Israel

    UTC +3
    Egypt

    UTC +4

    UTC +5
    Pakistan

    5:30 India

    UTC +6
    Bangladesh

    UTC +7

    UTC +8
    Phillipines, Australia, Perth,
    Western Standard time

    UTC +9
    9:30 Australia, Darwin, Central Standard Time

    UTC +10
    Australia, Sydney, Eastern Standard Time

    UTC +11

    UTC +12
    New Zealand

    • http://blog.bufferapp.com Kevan

      Great stuff here, John! Thanks so much for adding this information to the discussion!

  • Christine Leov-Lealand

    This is better info than I have seen recently bandied about regarding tweeting and time zones. As an author and publisher with a worldwide 24/7 audience the only way to tweet is 24/7. The MISSING INFO is that while there may be better engagement/faves/RTs from various time zones in the small hours, HOW MANY are there compared to busier times of day? Is someone buzzing on Methamphetamine at a rave RTing my tweet to their stoned friends as good an RT as someone on their phone at noon enjoying my tweet and sharing it with their friends? Will more people see it at 3am than at noon and what state of mind are they in?
    BTW what’s with the old passe desktop pc mindset guys? Who uses twitter from any kind of desktop application these days?
    If more developers used only mobile devices they would soon discover the glitches in their programming… just saying

    • http://blog.bufferapp.com Kevan

      Great point, Christine! Yes it’s a good distinction to make – I think there’s likely more total clicks/faves/RTs to go around during the day, and more tweets to divvy that engagement up! Understanding the quality of your audience at various hours is a great perspective to add also. Thanks!

  • http://www.savagegazelle.com/ Sirita Wright

    Thanks @kevanlee:disqus – I read through this and started implementing some of the findings into my scheduler. Thanks to you and your team for doing such extensive research. I actually can’t wait to share with my co-workers. This is useful for developing audiences, and getting the responses you’re really looking for.

    • http://blog.bufferapp.com Kevan

      Woohoo, thanks Sirita! Excited to hear what you find with your tests!

  • http://www.ElevatingYourBusiness.com/ Coach Maria Marsala

    To me, getting clicks is the most important — and when my audience is active.

  • Alexis D.M. Gourdol

    It would have been nice to include Latin America / Brazil in the data breakdown

    • Julian Winternheimer

      Hey Alexis, thanks for the great suggestion! I totally understand that a significant number of our awesome users are from Latin America and Brazil, and we will do our best to be much more inclusive in our next studies! 🙂

  • Liat Behr

    Wow, Kevan! Research based on 4.8 million tweets is pretty heavy duty. The importance of scheduling cannot be overstated. Thank you and thank you Buffer!!

    • http://blog.bufferapp.com Kevan

      Hi Liat! Yes indeed, I’m grateful for Julian and the data team for helping to make sense of it all!

  • Elisa Silverman

    Terrific information, but I’d be curious if you could segment the data by nature of the tweet (perhaps selecting some high volume hashtags and analysing that as a subset).

    Meaning, with clicks highest in the wee-hours, I wonder if that’s because this is a very social time for tweeting. If I’m tweeting primarily for business – are these the clicks that are happening at 3am? Maybe. Maybe 3am is just when people have time to actually read. But I don’t know.

    You mentioned that the high click rate in the early hours may be attributable to some outlier high-achieving post – what’s the topic of these outlier posts – news, social, business?

    • Julian Winternheimer

      Great questions Elisa! At the moment, we’re not segmenting the data by the nature of the tweet, only by timezone and hour of day.

      We also found the times quite surprising, and are currently double and triple checking the datasets for outliers that may have caused these unusual findings. So sorry I don’t have a better answer for you at the moment, but please stay tuned for a better explanation and possibly some new data! 🙂

  • http://customericare.com Aurelie Chazal

    I was so surprised by the times that get the most clicks. It makes sense when you think about it but it’s still something to see it confirmed by numbers.
    I changed the scheduling times on our account, I’m curious to see if it will improve engagement.

    I noticed before that we were getting a lot more clicks on the week end but never during the late evening or early morning. The week end stats are funny though. I have week ends with an average of 10 clicks per posts and others with 1-2 which is the average with get. Did you guys looked at days of the week also or just times?

    • Julian Winternheimer

      Thanks for the comment Aurelie, and great question! We chose to focus only on the hour of day in this analysis to try to keep it somewhat simple and interpretable. 🙂

      We also found the times quite surprising, and are currently double and triple checking the data for outliers that may have caused the data to give us these unusual results! Stay tuned for more information and explanation! 🙂

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  • Andreína Quijada

    Hi, You didn’t mention Latin America btw. In other case, I think the information is useful so I thank you dor this but I think it is still mising the information about where buffer user’s are coming from, because the data could be influenced by the country that have the biggest propotion using your service.

    • http://blog.bufferapp.com Kevan

      Makes complete sense, Andreina! Thanks for sharing this comment. Our data for some Latin American time zones wasn’t quite complete as we’d hoped in order to draw many conclusions; we’d love to explore the complete picture of best practices for all our Buffer users, and I really appreciate your great feedback here!

  • Natalie Narotzky

    Did you find any differences between different types of accounts that use buffer, like businesses, non-profits, or personal?

    • http://blog.bufferapp.com Kevan

      Great question, Natalie! We didn’t quite examine the data to that level of detail. Feels like a great one to push ahead with on further studies. Thanks for the nudge!

  • Soumitra Sengupta

    Great insight Kevan and thanks for sharing this with the world.
    Would have loved some insight on best posting time for audience in India as well.

    • Julian Winternheimer

      Thank you for the great suggestion Soumitra! We would love to include India in our future studies and are terribly sorry that we have excluded an amazing group of Buffer users from this study!

      The reason we chose not to focus on India is because there was a significantly lower volume of tweets coming from India, so we were less confident publishing findings from a relatively small sample of tweets. I hope that makes sense! 🙂

  • Geraldine

    Hi @kevanlee:disqus,

    I manage my company’s social media accounts and we post updates as a region (Asia Pacific). It’s interesting that the best times to tweet to get more clicks differs so greatly within the region:

    Hong Kong (Hong Kong Time): 5.00am
    Shanghai, Taipei, etc. (China Time): noon
    Sydney (Australian Eastern time): 2:00am

    Could you elaborate a bit more on how we can optimize getting clicks considering that even within the region, the timings differ so greatly. Thanks in advance!

    • Julian Winternheimer

      Hi there Geraldine, thank you for the great question! I’m really sorry about the confusion we’ve caused you here – keen to help you out! 🙂

      We’ve added a bit of extra information and explanation at the end of the blog post. After removing some of the large accounts that had a large effect on the averages, the times that received the most clicks, on average, shifted a bit:

      Hong Kong Time: 5:00 – 6:00am (9:00 – 10:00am was a close second)
      Shanghai, Taipei, etc: 7:00 – 8:00am
      Sydney: 1:00-2:00pm (11:00am – 12:00pm was a close second)

      These times seem to be a bit more consistent – perhaps now they could be a bit more helpful to you? Hope that helps Geraldine! 🙂

  • Aaron Dikel

    Fantastic post. Thanks a bunch.
    Now, not to be nit-picky about this, but it says above that in Japan the most tweets are sent out at 2 a.m. (Not that that is the best time, but that is the time most are sent) That doesn’t seem right.
    Everything else was a pleasure to read. The analysis is great, and filtering out the outliers was a great move.
    At this point, what most interests me, and probably should interest any social media marketer, is what the results would be according to twitter account theme. For instance, tweets about business probably act differently than tweets about entertainment or religion etc. It’s only logical that people relate to tweets of different subjects differently during different times of day. For instance, I doubt people are as interested in consuming business information at 2 in the morning, but that’s just an assumption.
    Is that possible to measure?

    • Julian Winternheimer

      Hi Aaron, thanks so much for the comment. And great intuition about the Japan time! That one was an error on my part – the most common time to tweet in Japan is actually 12-1pm. We’ll get that corrected in the post very shortly, thank you for pointing that out! 🙂

      I totally agree that the type of account is a very important factor, and we encourage experimenting to find the times that work best for your specific audience. At the moment, categorizing all of the Twitter accounts in our database might be a bit of a heavy task, but I can definitely see how it could make a great study by itself!

      Thanks again for the great suggestion and sorry for the confusion I’ve caused!

      • Aaron Dikel

        Hi Julian,
        Wow you all are on the ball with your response time.
        The mistake is minor and forgivable. Glad to know the intuition was right.
        What I most got out of this post is not to make assumptions about timing social media posts because I never thought to plan them for an hour that most people are sleeping.
        Keep on cranking out such fantastic content. Thanks a lot.

        • Julian Winternheimer

          Thanks so much for the kind words Aaron, I’m glad you found this information useful! 🙂

          It’s really interesting isn’t it, that high-volume tweet times and the times with the highest average engagement can often be quite different!

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  • Chris Briscoe

    But usually by default, because I am a new user I use what you list as GMT; but in your Blog, I notice you include many major Cities except London – please could you tell me why? And, sorry, but your blog is very confusing to me: you say that it’s best to post in the evenings or night-time when the traffic for clicks is highest, but between the hours of 1 a.m. and 4 a.m. is off-peak. But then you say, we can choose to post then because the traffic is not much; then you say, the best time to post is on average between 12.00 p.m. and 1.00 p.m.Can you help me cut through all this forest, please?

    • Julian Winternheimer

      Hey there Chris, so sorry that I’ve caused so much confusion with this information! Keen to help explain some of it better to you! 🙂

      We decided to exclude London and the GMT time zone from this study because many Buffer users’ schedules are set to the GMT time zone by default, even if they don’t actually live there. This means that there are many tweets sent at certain times that were quite different than the users’ time in their actual locations. We didn’t quite feel confident enough in the data from the GMT time zone for this reason. Does that perhaps make sense?

      Regarding the best times to post, would you mind letting me know which time zone you’re most interested in? If it helps at all, we found that tweets sent in the early morning hours received the most clicks, on average, and tweets sent in the evening and nighttime hours received more favorites and retweets, particularly in the United States. Thanks so much for bearing with me here – eager to help you out! 🙂

      • https://plus.google.com/u/0/108014476880311160592/posts/eg3aZN4Z2M9?pid=6163239964197478834&oid=108014476880311160592 Chris Briscoe

        Thank you Julian for your quick and kind help. It was helpful amd enlightening.

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  • http://www.songhong.info songhong

    Posts fairly specific analysis, hoping to learn a lot of things, thank you

  • Shanachie Carroll

    Have you considered making the data used in your study available to the buffer community? I’ve seen a lot of interesting questions asked and I have my own as well, and understandably you likely don’t have the resources to field all of the questions asked here. Crowdsourcing may be a viable means of helping to more rapidly and completely answering these burning questions. An anonymized data set would allow you to multiply the value of your data while still protecting the privacy of your userbase.

    • http://blog.bufferapp.com Kevan

      Hi there Shanachie! Great to hear from you, love the idea to make this data more accessible. We’ll see what we can do (I know it’s quite a large set of info!)

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    Excellent, as always, guys! I’m going to promote some of your numbers in a future social media roundup. I host one every quarter on my blog.

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  • Jenny Gentry

    Not that i do not appreciate this information. BUT You guys spent almost FIVE Million dollars to get this info. REALLY ARE YOU KIDDING ME. People everywhere are going homeless and do not have enough to eat. But they can rest easy in the knowledge that if they tweet between noon and one their tweets will reach more people. I do not like to be sarcastic but surely you could have gotten this info out much cheaper than that.

    • http://courtneyseiter.com/ Courtney Seiter

      Hey Jenny, thanks for sharing this! I agree, 5 million dollars would be a very big price tag for this information! We did this study in-house and spent lots of time on it but no money, other than staff salary time, as far as I know. 🙂 Would you happen to remember where you came across that figure? I’d love to make sure no one else gets this idea, I can certainly see how it would make you question our priorities!

    • http://tatumweb.com/blog/ Rich Tatum

      They analyzed 5 million tweets. They didn’t spend a dollar per tweet—this was data Buffer already owned. They spent staff time. You wouldn’t begrudge Buffer having employees work on corporate objectives would you?

      Rich

  • Jeanne Burke

    Hi Kevan, Thank you for the information. I am new to Twitter and admit that I am still trying to figure it out all out. Your study was interesting and I appreciate the info. Because I tend to have less time in the day to devote to Twitter, having the timing provided will prove helpful. Thanks again!

  • http://www.tapanalytics.com/ Tap Analytic

    An early Morning social Post is very effective as it stays on top of new for a longer time due to inactivity and Less posts being posted.

  • Becky

    Hi Kevan- Thanks for this awesome data analysis!
    Like many of the other comments regarding 3am timing for top engagement twitter posts, It would be great to see this data set segmented further. The social/business breakdown could be telling as well.
    I also wondered if the click time was at the 3am post time or if the posts which were done at 3am were clicked upon at a later time than the 3am time frame. At times, I favorite a tweet and go back at a later time to click on it so as not to lose sight of something which peaks my curiosity. Just wondering if this might be a factor as well.
    Thanks again for sharing your amazing study insights!

    Becky

  • http://lazarenko.eu Max Lazarenko

    in Image Sources, Blurground link is wrong.
    Thanks for report. Not a fan of stats but going to study this. Cheers.

  • Moshood Raimi

    This is an interesting study. But one thing this study isolated is the audience in Africa. Your study only captured tweets from Asia, Europe and US. I think you should try and cover other parts of the world.

  • Dom Reidman

    the most important question is who is using buffer? Sure the data looks wonderful but if we don’t know where the data is coming from then it might only have minimal value. For example we are B2C in health and wellness genre (a female target market). Buffer might be popular among males who don’t even sell physical products but more informational products. So I think there should be disclosure of who is is predominately generating the data.

    • http://blog.bufferapp.com Kevan

      Hi Dom! Thanks so much for the comment. This is such a great point. We’d love to dig into the specific demographics here in future studies. Really helpful to hear your thoughts on this and help us improve this research moving forward!

  • http://www.mungleville.wordpress.com/ Mungle Ville

    I’m so confused! When you say 2am, do you mean EST? So as I’m based in the Uk this would be 8am?

    • http://blog.bufferapp.com Kevan

      Hi Mungle! Thanks for the comment. 🙂 Yeah the findings here were a bit counterintuitive for us also! The 2am time is for your local time zone, so it’d be 2am UK time. This is based on the highest average engagements, so it’s possible that some outliers skew things slightly though I think the takeaway for me is that it’s possible sharing at a time when few others are sharing could help a tweet stand out more so than during a busy time! 🙂 I’d love to answer any further questions here! Sorry if I muddied the results a bit!

  • Âäkásh Mäjūmdår

    Hi, I am from India, especially from Mumbai. What’s the best time to be engage and have many followers too.

  • Eve Cook

    We can get “the highest number of retweets and favorites… between 9:00 and 10:00 p.m.”, but… 9pm and 10pm where? What time zone? 9pm Central? 9pm London time? 9pm EST?

    • http://blog.bufferapp.com Kevan

      Hi Eve! Thanks for the great question! The data for retweets and favorites was from US tweets, so my best suggestion there is that the 9pm and 10pm time tends to work well for each local time zone in the US and would be great to test if the same is true in the UK. My hunch is that 9-10 could do quite well. I’d love to hear what you find!

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    is there something for middle east ؟

  • Ruth K

    How fascinating. I feel that perhaps engagement is most significant when there are retweets and favorites rather than just clicks? Also was wondering how bots fit into the whole theory. Do they play a role in how many clicks I might get?

    P.S. I do want to take the ecourse but I’m getting an error message 🙁 Seems like a link is broken?

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    Very interesting… btw free course link is broken.

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  • Breeze Marturell

    Well I can say this: I am a seller in mercadolibre.com (it’s the Latino EBay) and can see the number of visits to my products. Once I tested the veracity of Twitter Stats, publishing an article without any type of highlight, the free publication option (almost zero visibility). After a day my article just had 2 visits (both mine) and then I started to tweet about it in some buyers circles, including the link to my article page. After half an hour and 17 tweets, Analytics gave me 77 impressions and a 0 engagement report, while I could see 17 new visits to my article. Can anybody explain why is that? Clearly, the tweets generated engagements (clicks to the link). I can generate +100 visits to any article, and I never had received a proper Analytics Report.

  • http://www.posterguy.in Akshay Chugh

    Posting at 3-4 am is actually working for me. I’am able to fetch more clicks. Thank you Buffer for making our lives easier (:

  • Taylor Walker

    Hey Kevan! I tried to sign up for your email course but it says “Something’s Wrong”. Any way I can get added? Thank you!

  • Kirk Weir

    Wouldn’t allow me to sign up… 🙁

  • http://technovariance.blogspot.com Meegan Naicker

    I recently decided to change my schedule and the engagement and impression rates fell drastically. I suggest you schedule your tweets according to your followers activities, this seems to work best.

  • Cameron

    Great article!

  • Nick Jackson

    Could this be because those wee hour clicks are from bots, who would click at a constant rate throughout the day?

  • Onaopemipo Monblaze Dara

    Hey, Jon! Great article. There’s not much mention of the data and findings in Africa (West Africa specifically).

    Also I worry that using all tweets published through Buffer since 2010 may not take into cognisance the role of time and trend. The may be different peak times for each year in the different regions. No?

  • http://www.totalashford.com/ Jonathan Goodwin

    I’m wondering if the middle of the night posts also get more clicks as they are top of people’s feeds when they get on their phones first thing in the morning? This would also correlate with the above update for 6-7am being an optimum post time. I take it you can’t tell the time of the clicks, only the timing of the posts that get the clicks?

  • http://www.stohnweb.com/ Jason Stanley

    Wow great research. Ironically I am tweeting this post at 10am est, one of the worst times to tweet for clicks. I will post it again at 11pm to see if I notice a difference.

  • Sushil Sharma

    Hi Kevan, Very nice insights and quite useful. I am going to use them to update my twitter strategies. Please follow us on twitter @realmonkey15

  • SicaBixby

    Since I have followers from all over the world, that made it to much work to figure it out. Those tools suck except Tweriod, but it broke last year and I couldn’t get any response on it.

    Did they finally fix it?

    • SicaBixby

      Tweriod still broken (Unexpected error 2) Not used their twitter account since 2014 and their Facebook page since 2013. So Buffer should just stop recommending the tool.

      It’s sad cause there is nothing else out there like it.

  • Stefan

    Loads of information, Wow Great blog post! We recently published a simplified version of our findings, compare the two and create your very own posting schedule based on your industry. Our blog is now up on http://sigma-events.com/2016/04/24/what-are-the-best-times-to-post-on-social-media/ Good luck all!

  • James Wrigley

    Very thorough research, it seems.

    Density of the populace in English speaking countries such as America might be best for me to tweet between 11am and 1pm EST.

    Bookmarked this so I can refer to it often.

    Thanks

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  • http://www.livingthewiselife.com/ Jared Chan

    Man so many different times… its overwhelming… makes me just want to pump a post out every hour… it’s not like everyone is going to see the posts from the other side of the day…

  • SDR Kings

    Upon reading this, I think I’ll be experimenting with the different times to tweet for better engagement. These practices seem to go against the convention but perhaps that’s what it takes!