An Infographic Tells You How To Make Your Tweets More Clickable

An intriguing infographic by Dan Zarrella shows that links inserted near the front of tweets may get more clicks.

How tiny can a data visualization be and still be meaningful? Edward Tufte pushed the limit of infographic density with his "sparklines," and now Dan Zarrella of Hubspot does something similar—with a micro-sized heatmap of a similarly micro-sized form of communication: the 140-character tweet. According to his visual analysis, links inserted into tweets are more likely to be clicked if they appear somewhere between the start and the middle of the tweet, not the end (as most of us would assume and do in practice).

That data-driven insight is intriguing enough, but so is the way Zarrella visualized it. If you’re like me, when you hear "heat map" you think of a two-dimensional map of a website color-coded in something like Predator-vision, which visualizes where users focus their attention onscreen. Zarrella’s one-dimensional heat map (it only maps points on a line) elegantly matches the parsimoniousness of Twitter itself—in fact, it could probably be squashed into the physical space that a tweet takes up on a smartphone screen and lose none of its informative power.

Heck, if a sparkline is designed to be meaningful at the size of a pencil eraser, Zarrella’s micro-heatmap could probably fit into the size of a favicon and still get its point across: Human beings are pretty excellent at distinguishing edges and color-contrasts in fine detail, and the areas in Zarrella’s graph corresponding to "high clickthrough rate"—ie, the parts of his graph that actually carry the useful meaning in contrast the rest, which essentially functions as "background"—would jump right out even if it were shrink-rayed. It would be neat to see Zarrella’s graph translated into ASCII, as well—a tiny string that could be tweeted along with some interesting commentary and still fit into 140 characters.

Okay, maybe that’s pushing it. But experimenting with the perceptual limits of information density in our displays isn’t just idle fiddling. Twitter itself is a (very successful) experiment in this regard: Five years ago, would anyone have believed that a network of SMS-length mind-burps would be capable of transmitting world-changing information? What if Twitter (or some enterprising startup) could offer a suite of visual analytics whose gestalt state could be grokked by flicking your eyes at a square of screen-space no bigger than a few dozen pixels? Alone, such a nano-visualization might be more cute than useful—but what if such visually dense graphics were aggregated, so that en masse they harnessed the formidable power of the human visual system to reveal useful patterns across many different channels, states, or media? Sounds like a job for the next Edward Tufte.

[Read more about Zarella’s micro-graph | via Mediabistro]

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  • Shelly Birger Phillips

    Thanks for sharing this! Great info that could make a huge difference for me. 

  • John Rennie

    Fascinating, but I wonder whether some of the pattern here is an artifact of how long (or short) tweets are on average rather than sweet spots for clickability. For example, most people start tweets with some comment, no matter how short, before a link. If those comments are often very short, and total tweet length is around 75 characters or less, that would account for the first half of the heatmap. But people who write longer tweets may routinely use almost the full 140 characters, again with a link at the end. That would account for the second half.

    So maybe it has less to do with most-clicked positions for links and more to do with where links are, period?

  • John Pavlus

    You mean, does the graph reflect relative position (where in the tweet, regardless of how long or short it is in toto) or absolute position (where on the 140-character space the link occurs)? Very interesting... I'm not sure.