I made a tappable version of my DataGotham talk from Sept 9th, 2013. Hope you enjoy!
From the betaworks “Department of Insights That Make Sense, But Are Cool to See Play Out in the Real World” (better known as DITMSBACSPORW), we bring you a snippet of statistics about bit.ly clicks from mobile devices. Using two months of click history from one of SocialFlow’s customers, a user with a Twitter account with over 500,000 followers, we separated the clicks coming from mobile devices (such as iPhones and Android-powered phones) from all other clicks (such as from desktop computers). We could then see how mobile browsing varied over the course of each day as a percentage of total browsing.
➢ Mobile usage is really important – at the peak (at 8 PM on Saturdays), an average of 41% of all clicks came from mobile devices.
➢ Weekends generally have a higher percentage than weekdays. (It’s good to know you’re not just shifting from following Twitter on your office PC to following Twitter on your home PC. You’re using Twitter on your phone!)
➢ Friday night looks more like a weekend, and Sunday night looks more like a weeknight. (Your mother will be happy to know you’re staying home on Sunday nights.)
➢ People are less likely to click from their mobile devices in the middle of the day and wee hours of the morning than during morning rush hour or at night
While conventional wisdom might hold that the power of Twitter is based on the brevity of its 140-character messages and the convenience of receiving these messages on the go, it’s becoming clear that people on the move are also reading long-form content that appears (in link form) in their Twitter timelines.
SocialFlow’s algorithms help publishers select which of their potential Twitter and Facebook messages will be most interesting to their followers and fans, and it sends those selected messages at the best time. As web browsing on mobile devices increases, the right time to send a message will often be when people are on the go. That’s all the more reason to have a tool help you send messages – you’re too busy partying at night (and, um, compulsively checking your phone) to be at your desk sending tweets.
UPDATE: Editor’s note
We had a few questions regarding the timezone of the graph and whether we mapped clicks to the time in their respective zones.
1) All times are Eastern.
2) We did not normalize clicks to the times in their respective zones. Ultimately, when you send a tweet, it will go to all of your followers at the same time, regardless of what timezone they are in. We therefore felt it was appropriate to lump all the timezones into one.
3) As the client writes English-language articles, the vast majority of the client’s followers are clicking from US timezones.
4) The general trends, i.e. weekend higher than weekday, night higher than day, still hold even without accounting for different timezones.
We collected tweets from the twitter API (twitter also created their own visualization) that used worldcup hashtags (such as #worldcup and #copamundial), extracted the bit.ly URLs, and plotted the click traffic on a world map.
Each frame of the video is approximately one hour. The color ranges from white (low traffic) to dark blue (highest traffic), and is normalized by click count per country.
You can see the peaks in the US vs Ghana and Brazil vs Netherlands games and, most intriguingly, the immediate lack of traffic in the Netherlands after losing while the attention in Spain persisted through the next morning.
This effect is clearly visible if we zoom in on Europe:
If you want to relive the final, dramatic game, we loved this recreation of the final moments in LEGO:
Some of the data and arguments included in this post were first incorporated into Peter Kafka’s July 8, 2010 post entitled “LeBron James and the Giant Twitter Link” (http://bit.ly/9Hh2Mh).
As was widely reported, LeBron James made his initial foray into the world of Twitter last week and had quickly amassed a following of close to 300,000 followers. While many reports and posts had analyzed the diffusion of LeBron’s original tweet and the speed with which he has gained followers, the data we have here at betaworks provides us with unique insights into the awesome distribution surrounding LeBron’s first tweets and its lessons for the Twitter universe in general. LeBron’s tweet, despite a dearth of initial followers, serves as an extreme counterexample to the common misconception that “More followers equals more clicks.” As the LeBron example shows, and what we know from other betaworks data, relevance of message and follower engagement are for more important.
With the simplest of messages…
Check http://bit.ly/apxlxx (lebronjames.com) for updated info on my decision.
…LeBron’s bit.ly link had one of the most popular first days ever, both in terms of the volume and velocity of clicks by individual users.
The velocity profile (though not the absolute level) for the first hour of the shortened link is fairly typical of popular links – they peak soon after being published, drop sharply over the next ten minutes, and then decline slowly but steadily. LeBron’s shortened link is unique because of its sheer magnitude coupled with the fact that his number of Twitter followers is relatively low (more on this point later). Furthermore, people’s interest just doesn’t seem to die; 24 hours later, the link still gets about 50 clicks a minute. Below are some statistics on the massive click-storm unleashed by that single tweet.
|Total followers 24 hours after post||~300,000|
|Total bit.ly clicks 24 hours after post||~180,000|
|% of first day’s clicks within first hour||~25% (compared to ~50% for a typical popular tweet)|
|Peak velocity||~3,000 clicks per minute (reached almost immediately)|
|Time to 50% of peak velocity||~5 minutes|
|Time to 25% of peak velocity||~14 minutes|
|Time to 12.5% of peak velocity||~39 minutes|
LeBron’s post puts in clear focus the importance of tweet relevance to potential readers and the idea that it is better to have fewer dedicated followers than more disinterested followers.
With all the hoopla surrounding LeBron – Decision 2010, sports writers and fans had whipped themselves into a frenzy, jumping on any and every piece of LeBron-related news on which they can get their hands. LeBron’s post, table scraps in terms of its informational content, was consumed ravenously by a large swath of people precisely because they were starving for anything at that moment. At another time, as popular as LeBron may be, it is unlikely that the same type of tweet with so little actual news would have generated the same kind of response.
The other lesson we drew is that it is a far better strategy to ensure that your readers actually care about your posts than to amass an ever-growing legion of followers who couldn’t care less. LeBron started with almost no followers, yet the response was crazy.
These patterns and lessons bolster the thesis behind one of betaworks’ companies, SocialFlow. SocialFlow provides a tool for Twitter publishers to ensure that their posts go out when their followers actually care about the content with the proven ability to increase click-through rates and follower-retention. Examining the SocialFlow data, the cliche seen in the response to LeBron’s post, of quality (relevance) over quantity, plays out again and again; one of their clients that focuses on cycling and has about 17,500 followers generates a higher number of clicks, not just a higher click-through rate, than do some Twitter accounts that gained over a million followers because of their placement on suggested lists. In the world of micro-blogging, relevance and quality beat quantity any day.
Though he didn’t sign on with our hometown Knicks, we still appreciate LeBron for the important insights he has highlighted as a Twitter Phenomenon.
At betaworks, our focus and expertise lies in understanding and leveraging the real-time web to create superb products, great API’s and profitable businesses. With tens of millions of daily bit.ly decodes, Chartbeat pings and messages on Twitter, the amount of data that flows into betaworks-backed companies is staggering. We at betaworks understand the tremendous value embedded within this data and are consistently mining the data to create and improve new products, features and ultimately, entire business lines.
The data@beta blog will serve as our outlet to share interesting insights that we have gleaned from our data, as well as provide a small window into the way in which we use data to enhance our businesses. Topics and goals range from general market overviews to data-driven recommendations designed to enhance one’s business to posts devoted to fun, interesting, or simply wacky subjects. We’d love to hear your feedback as well as ideas for what you’d like to see on the blog. Feel free to email us at data at betaworks dot com.