Looker Blog : Data Matters

You're Not Normal

Daniel Mintz, Chief Data Evangelist

May 11, 2016

One of the trickiest things about being human is that you only get to see the world from one perspective. This is relevant not just for the reasons that philosophers love to ponder, but also because it makes putting yourself in someone else’s shoes really hard.

And it’s not getting easier. As we’ve gained tools to reach larger and more diverse audiences, putting yourself in their shoes has simultaneously gotten much harder and much more critical.

After all, if you’re only fashioning tools for members of your village, you understand intuitively how they’ll be used. But when your potential audience is global—living in contexts and locations you can’t even dream of—you’re far from an average user.

And yet, while potential audiences are growing, the world each of us inhabits online has only shrunk, thanks to what my friend Eli Pariser calls the filter bubble.

When I was writing emails for MoveOn.org, it was easy to assume our 7 million members were following every legislative development as closely as I was. Except that was, of course, nuts, since following politics was my job, not theirs. They had their own lives to attend to.

I knew this intellectually, but even so, resisting the urge to think of myself as normal was really hard. Whenever I logged onto Facebook or the blogs I followed, I was surrounded by a (relatively tiny) group of people just like me. And even though I knew it was only a few hundred people, it didn’t feel tiny. It felt like my whole world.

So how can you counter this innate, very human belief in your own normality?

Empathy. And data.

First, always keep your audience in mind. At MoveOn, I’d think about writing to my mom’s friends. They weren’t representative of all MoveOn members, but they were a lot closer to average than I was. And when I recognized that my intended audience’s experiences were simply too far from my own for me to imagine, I’d ask for help from others who were more representative, either personally if I knew them, or by survey if I didn’t.

Then, and this is critical, don’t just assume that your guess was right. Even when we try to think about the world through others’ eyes, we’re generally not very good at it. Your guess is only a hypothesis. It’s data that proves your hypothesis right or wrong.

And as I learned, asking the people around you if your hypothesis is right is no substitute for real data. It’s no accident that those people surround you, and they’re probably no more representative of your intended audience than you are.

Because while the internet demands that we enlarge the scope of our empathy enormously, it’s also made data to aid us readily available and highly actionable. While you have to imagine yourself in an ever-wider range of shoes, you have better tools than ever to make sure they fit.

So, if you’re an engineer and you think users will suffer through a less-than-smooth onboarding process, I encourage you to check the data about your sign-up funnel. I think you’ll realize very quickly that your willingness to stick it out isn’t normal.

If you’re a writer and you’re sure that readers are loving your 3000-word essay because they clicked on its headline, see how many made it to the bottom of the page. You may love #longform, but, chances are, you’re not normal.

If you’re in marketing or sales and are sure it’s time to vary your message--that prospects must be as sick of your lines as you are--survey and see if it has even penetrated the consciousness of the average user. You may be sick of it, but you’re not normal.

Saying that you need to empathize with your audience doesn’t mean compromising your vision. Your vision is a big part of why you’re not normal, after all. But it does mean that your vision alone won’t suffice.

The goal, as MoveOn’s co-founders Wes Boyd and Joan Blades put it, should be "Strong Vision, Big Ears." The goal should be to embrace the fact that you’re not normal, while remembering that great software is an act of empathy. Empathy, that is, and data.

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