Column: Data-Informed Design

This is the first edition of my new column, Data-Informed Design, which will explore the use of data to inform UX design. Data, in many different forms, is changing how we think about ourselves and the world. And, for better or worse, it is definitely changing our experience with technology—from great new mobile apps that we can use to monitor our health to incremental improvements on our favorite Web sites to those annoying ads that follow us everywhere.

In my column, I’ll describe how to use different types and sources of data to create better user experiences and how to achieve some balance—so data isn’t driving decisions. There are three key topics that I’ll cover:

• Starting at a high level, I’ll look at why you would want to use data, some misconceptions around data and UX design, and discuss a process for incorporating any kind of data into your decisions.
• Then, I’ll move on to considering various data sources such as analytics, A/B tests, social-media sentiment, and various types of quantified data from UX research.
• I’ll also describe how to use and analyze data, including metrics and measurement frameworks, as well as presentation tips and visualization tools.

Read More

Despite all the talk about data-informed design, there is not much agreement on what data really means for a product or service’s user experience. That might be because teams don’t yet have a shared language for talking about data, or because access to data is uneven or siloed, or perhaps because team members have different goals for the use of data.

At its core, data-informed design can be difficult to define, because there is not even agreement on what counts as data. We tend to think in dichotomies: quantitative and qualitative, objective and subjective, abstract and sensory, messy and curated, business and user experience, science and story. But the more I work with data and the more familiar I become with the data-science community, the more inclusive my definition of data becomes. Read More

As a researcher, I want to understand how technology changes people’s lives, not wade through a bunch of data. Like a lot of people, I think in stories rather than numbers; in the tangible rather than the abstract. So, when I made it a goal to understand all of the data about the experiences people have with technology—not just the kinds of data that I was comfortable with—there were some big gaps in my knowledge.

First Steps

First, I had to cross the threshold of my number aversion. This wasn’t too hard because, even though I love to dive into messy questions, I’m not thrilled with messy answers. I’m still relearning statistics—thanks to Khan Academy and The Cartoon Guide to Statistics—getting more confident with Excel, and gaining some basic skills in Tableau. Read More