The importance of dataviz in a fast-paced world

Some weeks ago I was asked to give a short lecture at the Data Stories 2018 exhibition organized by the Central European University. I decided to speak about the growing importance of data visualization in the 21st century, because it’s mind-blowing how fast the world has changed in the last decades. We face so many new information every day, that I feel satisfied keeping up with them even if I only manage to read the headlines.

In my favorite book (written by Attila Bartis) there’s a whole chapter about how people got together throwing parties to watch the moon landing together and everyone knew this was something BIG. Last week I went home and when I broke the news to my mom, that a Tesla has been launched into space, she was utterly shocked. She thought I was just joking around and refused to believe me until I showed her the photo of the floating car… In this fast-paced world we have become pickier in how we spend our time and consume news. Apparently, my mom doesn’t have the SpaceX missions in her spectrum of interest.

tesla-roadster-in-space-9

When I was preparing for this lecture – a topic that interests me – even I felt myself getting bored, while digging out the information I need from those massive articles. I was notoriously searching for the numbers I need in the word avalanche the writer hailed on me. As I tried to force myself reading it from top to bottom I got more and more impatient not getting to the gist of it.

But why is that so important anyway?

Let’s imagine, that 100 people land on your page to read an article… You lose almost 38 just after the load, because they either lose interest in the topic or would not sacrifice their time reading it. From the remaining 62, 3 will never scroll down. By the time your readers reach 60% of the article, you can only keep 30 out of 100.

However…

You can keep almost 100% of your readers by using visual content like photos, videos, interactive vizzes or infographics.

CEU 1

Coming from a social science background, I always have the twinge to validate my assumptions. To prove that it’s not just a myth, I brought both a quantitative and a qualitative approach to show this is really happening!


Proof 1: Buzzfeed statistics

I red some Buzzfeed statistics showing their evolving news structure in the past 5 years. In April 2012 they published almost 1000 articles and 10 videos. Comparing the same period 4 years later, the number of published articles was 5 times higher and they started to focus on visual content. It’s clearly showing, how this everyday news tornado has developed around us, as well as the growing importance on video posts. In 2017 the numbers increased further, in the past 5 years Buzzfeed written 6 times more articles comparing the same period of time, but the video figures are even more shocking. In 2012 they had posted 10 videos, that jumped over 300 by 2017.


Proof 2: The car sharing experience

Just to give you some background on my accidental participation observation experience, I’m a frequent user of the biggest Hungarian car sharing system. This means I get to spend 4 hours with strangers, in stranger’s cars almost every week where I need to engage in conversations with these strangers… and this is something I truly enjoy.

To share the story of one of my recent rides, have a look at the passenger profiles I put together to lay the foundations of my findings:

CEU 3

So, based on our conversation these four people only had two things in common:

  1. We were travelling from Kaposvár to Budapest at the same time in the same car
  2. …and we’re Index readers

By the time we reached lake Balaton it turned out that all of us had red an article on trending dog species and names some weeks ago. Don’t get me wrong, but a completely uninteresting and boring topic apart from one tiny thing. And that tiny thing was, that this is not like 99 out of 100 articles, but the 1 that used data visualization techniques to catch readers eyes.

If these examples don’t prove that data visualization works, I might have the wrong definition of proof. 🙂

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