Data-Informed Product Design

Chapter 2. Designing with All of the Data

To clarify, add data.

Edward R. Tufte

There is a lot of hype about data-driven or data-informed design, but there is very little agreement about what it really means. Even deciding how to define data is difficult for teams with spotty access to data in the organization, uneven understanding, and little shared language. For some interactive products, it’s possible to have analytics, A/B tests, surveys, intercepts, benchmarks, and scores of usability tests, ethnographic studies, and interviews. But what counts as data? And more important, what will inform design in a meaningful way?

When it comes to 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. Thinking about the key differences can help us to sort out how it fits together, but it can also set up unproductive oppositions. Using data for design does not have to be an either/or; instead, it should be yes, and...

Big Data and the User Experience

At its simplest, Big Data is data generated by machines recording what people do and say. Some of this data is simply counts—counts of who has come to your website, how they got there, how long they stayed, and what they clicked or tapped. They also could be counts of how many clicked A and how many clicked B, or perhaps counts of purchases or transactions.

For a site such as Amazon, there are a million different ...