The following excerpt is from an article found on UX Magazine. It was written by Pamela Pavliscak.
There is a lot of buzz about data-driven design, but very little agreement about what data-driven design really means.
Even deciding how to define data is difficult for teams with spotty access to data within their organizations, uneven understanding, and little shared language. For any site or app, it’s standard practice to have analytics, A/B tests, surveys, intercepts, benchmarks, scores of usability tests, ethnographic studies, and interviews. So what counts as data? And more importantly, what will inform design in a meaningful way?
In trying to understand what data-driven design is, we can start with what data-driven design is not. Then maybe we can work toward how data might actually help make user experience better.
Myth 1: Data Means Numbers
A lot of the data about a site or app flows in from analytics, and analytics are basically tallies of who has come to your website, how they got there, how long they stayed, and what they clicked or tapped. Other data may come from how many clicked A and how many clicked B. More tallies. Then there are intercepts and surveys where scored responses are counted. Still more tallies.
Numbers represent the actions of real people with complicated lives. But rolling the behavior of millions of people into a single number is not always useful, or reliable. Even the most organized sets of numbers don’t answer a lot of the questions we still have about user experience, like why people take action or why they don’t, or how they felt about it, or what expectations they bring to the experience. Interviews, ethnographic studies, and usability tests fill in the gaps left by numeric data. But because qualitative insights are not numeric, they are often not considered data.
In other fields, like the social sciences and medicine, there is no question that qualitative is still data. Small numbers, or thick data, still count whether they remain as narrative or are quantified. This makes sense for data-informed design too.
The true defining characteristic of data that can be used to inform design, are the traces left behind by people, no matter the source.
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