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Главная » 2012 » Май » 27 » May 8, 2012 Time Is On Your Side
00:24
May 8, 2012 Time Is On Your Side

Did you see those silly cats on Tumblr, that breaking news on Twitter, and those photos of your friend’s kids on Facebook? Different social networks have their own distinct personalities. Bitly links are shared across all social networking services, giving us a unique viewpoint on how these networks differ.

We track metrics like the main type of content being shared on a network, the geographic locations of the people sharing and viewing the content, and how the popularity of the network has risen and fallen compared to other networks. Studying the differences between these networks leads us to interesting insights, for example, did you know that the half-life of a link on Twitter is 2.8 hours?

Recently weʼve been exploring how content propagates (or "goes viral”) through social networks, particularly how the day and time something is posted affects the eventual amount of attention it will receive.

Note: All the plots are based on EST. You will see day of the week, starting with Monday, on the Y axis, and hour of the day, starting with midnight, along the X axis. For the first plot in each section, the darker the blue block, the more traffic on average links posted during that hour received in the following 24 hour period of time. White blocks, show when links got less traffic. For the second plot, the darker blue represents when the site is most active, which we calculate based on number of clicks on Bitly links coming from these social platforms.

Twitter

For Twitter, posting in the afternoon earlier in the week is your best chance at achieving a high click count (1-3pm Monday through Thursday). Posting after 8pm should be avoided. Specifically, don’t bother posting after 3pm on a Friday since, as far as being a gateway to drive traffic to your content, it appears that Twitter doesn’t work on weekends.
The peaks of Twitter activity fall before the optimal time to post. The peak traffic times for Twitter are 9am through 3pm, Monday through Thursday. Posting on Twitter when there are many people clicking does help raise the average number of clicks, but it in no way guarantees an optimal amount of attention, since there is more competition for any individual’s attention. An optimal strategy must weigh the number of people paying attention against the number of other posts vying for that attention.

Facebook

Links posted from 1pm to 4pm result in the highest average click throughs. The peak time of the week was on Wednesday at 3pm. Links posted after 8pm and before 8am will have more difficulty achieving high amounts of attention. As with Twitter, avoid posting on the weekends.

Facebook traffic peeks mid-week, 1 to 3pm. While traffic starts to increase around 9am, one would be wise to wait to post until 11am. Traffic from Facebook fades after 4pm. Despite similar traffic counts at 8pm and 7pm, posting at 7pm will result in more clicks on average than posting at 8pm.

Tumblr


Tumblr likes to party! This network shows a drastically different pattern of usage from Facebook and Twitter. One should wait until at least 4pm to post. Also postings after 7pm on average receive more clicks over 24 hours than content posted mid-day during the week. Friday evening, a no-man’s land on other platforms, is an optimal time to post on Tumblr.

Bitly traffic from Tumblr peaks between 7pm and 10pm on Monday and Tuesday, with similar traffic on Sunday.

Conclusion

It’s easy to see that just like your neighborhood restaurants, each social network has its own culture and behavior patterns. By understanding the simple characteristics of each social network, you can publish your content at exactly the right time for it to reach the maximum number of people.
 32 comments

  • Russ Hughes, Founder of Pro Tools Expert blog

    Next time I get a hot story I'll wait several hours before I post it.



  • The catch is that fine line between over posting and irritating your local audience vs. catering for your audience overseas who are on different time zones. Balance is key



  • Jeremy Roberts, Talent Acquisition and Sourcing Professional based in Dallas, TX; GuideHop Co-Founder; Social Marketer

    Great post.  Tumblr is a party site. I wonder if the porn has anything to do with the late night clicks :)



  • The best time is ... when the news occurs ...



  • Karin

    Great information, I had done some research into emailing and twitter, but its really interesting about tumblr. 



  • NY Creative Interns, NY Creative Interns is dedicated to enabling college students and recent grads to find internships, mentors, and inspiration through networking and meetups. In addition, we are a resource for companies and organizations, helping to alleviate the interview process by creating cool, unique atmospheres for creatives to interact and connect.

    Very helpful, thanks for sharing!



  • great info - Thanks. I will share this with everyone.



  • Is this study based in the US only?



  • Evans Thompson

    Good info.  Is there any data on posts on LinkedIn?



  • Does this take into account global traffic and their timezones?  Interested if Asia and Europe influence the times when retrofitted to EST



  • Clicks are good, but how are they connected to velocity and breadth of sharing? For instance, any particular times when links are more likely to go global than others? 



  • Rich Tucker , Cruise+

    A couple of questions on the calculations here.  Are you looking at total Bit.ly Link traffic during each hour?   If most marketers are posting status updates with links on Facebook M - F from 1 - 4 PM ET, then wouldn't the fact that there are more links being put on Facebook during those hours drive up the number? 

    Or if you are looking at the average click-thrus on each individual Bit.ly Link, then the fact that the big marketers with Millions of Fans typically update 9 - 5 ET M - F skew the results?  A bit.ly Link shared by Nike is completely different than an individual person.  If all the big brands were posting at midnight, regardless of how many people were actually on Facebook at the time it would look like Midnight was the best time to post status updates. 



  • This is very interesting data, especially the extent of the drop in traffic on Fridays and Tumblr variance.  Thanks for sharing this!  (ps - day 0 is Monday, yes?)



  • You should also check out Dan Zarrella's Hierarchy of Contagiousness (http://danzarrella.com): he aggregated millions of bits of data to produce some interesting insights, but advocates you use YOUR data to make judgement calls.



  • You mention that you are basing the timelines on EST. Did you filter out posts from non US locations in the analysis or is this an overall picture ? I would be curious to see if a similar pattern exists in other regions of the world - like India (where I stay) or if there are other "cultures" so to speak.



  • jjduncan

    would love to see similar methodology applied to aggregator sites like reddit



  • Wow this is great info!  Thanks for sharing, it's probably too late to comment now though huh?  ; )

    - http://www.facebook.com/sfstat...



  • Thanks for sharing these insights, but allow me to point out one thing, hoping this will trigger some discussion: These findings demonstrate a clear non-trivial dependence between the time you share a link and how many clicks they get. But this doesn't mean there's a direct causal effect between the two things. Are these results actionable? Is the suggestion "Posting after 8pm should be avoided" a valid one?

    Assume for example that there are two kinds of people, BLUE and RED.
    BLUE people only share links between 1pm and 3pm Mon-Thur (peak period), and people like clicking on links shared by blue people.
    RED people tend to share stuff outside the peak period, and people don't care at all about what RED people share and never click on their stuff. If this would be the case, you would still see the general patterns you plotted in the data, but your conclusions and suggestions like "Posting after 8pm should be avoided" would make no sense at all. Even if RED people started posting stuff in the peak period, people still wouldn't click.

    And there are so many more possible confounding factors that are not controlled for: you can tell the same story with BLUE and RED content :)

    To get a real insight into causal effects, you'd have to dig deeper than correlation, or perhaps it would be easier do a randomised experiment, when sharing of bit.ly links is always delayed by a random time. Bufferapp seems to be the obvious source where one would go for such interventional data, and they already use bit.ly shortening.Ferenc http://bit.ly/K36jaK



  • Karim

    I did the same research last year on Egyptian users and reached almost the same conclusion

    http://karim-ouda.blogspot.com...
    http://karim-ouda.blogspot.com...



  • It's interesting the usage is based on US EST vs the rest of the world. You'd think non US traffic might even things out... or in Tumblrs case maybe non US time zones are what's making it popular in the evenings.



  • Adam Robinson, MBA, I am the owner of Strategexe Consulting Group, LLC in Louisville, KY. I am passionate about helping small business owners be more successful through strategic planning and effective marketing management.

    Thank you for providing this research to us.  As a social media marketing company we go to great lengths to schedule posts at times with the highest probability of engagement. This will vary greatly between target audiences; however, the insights provided in the blog are outstanding.



  • Thatguylam

    I liked your post on when to Pin on Pinterest, too! 
    http://mashable.com/2012/05/05...



  • Misslecommander

    Someone could make some money by creating an app that schedules one's postings based on real-time traffic data like this.



  • Thomas Baekdal, Author, Writer, Magazine Publisher, and Social Media Advocate.

    Interesting, but could you provide a more detailed explanation of how this was calculated. 



  • Terrific information. 

    I've linked to this from my new blog post, Data You Need to Make Content Go Viral:  http://mrkieran.com/make-conte...

    Michael Kieran



  • Bas

    Nice post. You used EST as standard, but did you also only measured traffic from the US and Canada? Or is this traffic worldwide? I live in the Netherlands, but I don't think I should ad 6 hours to all the outcomes?



  • Interesting data. Awesome charts! Nice work. 



  • laurenwick

    Thanks for sharing all this! I was particularly interested in the Tumblr data. 



  • Bill Freedman, Enterprise software and marketing start-up exec with a passion for creating content and automating marketing ops. Turning innovation into revenue since 1988.

    Fascinating visual and interesting to demonstrate the nature of each network's unique vibe.  I'm trying to figure out how to use this information to make decisions about posting to my network of 25-45 year old men in North America who use twitter to keep up with their key enterprise software suppliers. I'm using Twitter and to a lesser degree Facebook. Should I time for averages? Should I add other networks? Any thoughts based on the available data?



  • ty_frank

    and what about pinterest?



  • It would help some people a bit if you said the days of the week go from top to bottom on the Y axis.



  • I assume these patterns correlate with the time of posting?  ie. There's no ramp-up pattern where the link gets "seeded" among a group of people that's particular to each network?

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