In which other ways than respecting their TIME and their GOALS can we make sure that people will actually be interacting with our visualization pieces.

Again: be aware of your assumptions. Especially us datavis nerds often have the dangerous assumption that everyone is as crazy about datavis as we are. I mean, just think back to my grandiose introduction of visualization in the beginning here.

But, of course, that’s wrong. And that’s healthy! It’s a good thing not everyone is fighting about pie charts on Twitter!

So, given that most people aren’t that interested in visualization (let’s be honest here), we have to find a way to make them CARE about it. Because if they don’t care, they won’t look at it, let alone interact with it.

And even before they start caring about it, you want to make sure that you’re not closing the door right in their face. Don’t throw bar charts at them until they close that browser tab.

ONBOARDING

One aspect of that is the new fangled term “user onboarding” (how to get people on board). Basically, what happens in the first moments after a person opens your app or website or even newspaper page. This can shape the rest of people’s experience with your infographic. And of course also if they’re quickly frustrated and just close it and go do something else.

Onboarding is something that even happens in print. If we go back to Accurat’s La Lettura visualizations, each of them has a short introductory paragraph on the top left (where you would naturally start reading with a Western background) and then a section titled ‘How to read it?’. That gives you a clear idea of how to work with the graphic before diving into the details.

Other great examples for tutorials and guided exploration of visualizations are Nicky Case’s projects — if you haven’t played with ‘Parable of the polygons’, for example, you should definitely check it out. A clean text explanation of what this project is about plus interspersed interactive elements for exploration.

Super-thorough research

…. and those are basically all great examples for user onboarding in visualization that I’ve found despite my super-thorough research.

But seriously, it’s something that I and the visualization community really could become better at.

Good onboarding is the data expert giving a short introduction to the data and what they know about it, instead of just looking at you… blankly … staring into your soul…

But beyond simply teaching people how to read and understand your visualization, respecting their time and interests can go even further.

CARE

You want to make sure that they CARE about your visualization. Now, how to do that?

If we’re really _really_ honest about ourselves, what’s the one thing that’s endlessly fascinating to us and we could talk about forever?

Right. Ourselves.

So one simple trick to draw people into a visualization is by appealing to this inherent narcissism. Quickly answer the question ‘Why should I care. What is it to me? Why would I give any expletive about the situation in so-and-so?’

If you provide them with an answer right away, telling them what this dataset could mean to them, they might actually listen.

This is a pattern that you often see in visualizations:

In this piece by the BBC about humanity crossing the number of 7 billion people (those were the days), they ask you a few questions to arrive at your very unique and personal place in the world.

New York Times: The Secrets of Street Names and Home Values

Here’s another one by the New York Times, that shows you how much less your house is worth because it’s built on Main Street instead of Ocean Boulevard. Again, you can enter your own street name and explore how that changes things.

But instead of directly asking people you can also be more subtle about it. An easy way to get access to this type of contextual information is through the various sensors hidden in our smartphones and laptops. You could almost call that ‘passive interaction’.

Moritz Stefaner and I did a project for the OECD in 2014 called “Regional Well-Being”. The OECD is spending a lot of time capturing factors of well-being in their member countries and with this project, they decided to dive from a national to a regional level. So it was no longer about the quality of life in Germany, but in Bavaria versus Berlin and so on.

This of course also made the dataset much more complicated — while their Better Life Index contains 11 dimensions for 35 countries, the Regional Well-Being data contains 11 dimensions for 395 regions! Since this can make the data pretty overwhelming at first, Moritz and I decided to start with something that our audience could relate to — the quality of life in their own region.

So, when you open www.oecdregionalwellbeing.org your browser asks you to give them your current location (browsers can do that, and if you’re not comfortable with it you can also select it from a list). And the visualization then starts at this location, so you can look at how life is around you. From there as a starting point, you can branch out in your exploration — either looking at spatially close regions or regions that are similar to your own.

Or even go somewhere completely different. Starting in your own region lures you into the visualization and gives you a reason to actually care about it.