• The great thing about data is that it can show us what people do. The not-so-great thing about data (both qualitative and quantitative ones) is that it can’t tell us accurately about context, motivations, and intent of users.

In data-driven design, data is at the center of the design decisions. It’s the primary (and sometimes, the only) input. Data-driven design looks to ship fast, optimize at every step and let the data drive many of the design decisions.

In data-informed design, data is a key input among many other variables. You use the data to build a deeper understanding of what value you are providing to the users. You combine data with qualitative feedback and your design intuition to produce iterations of successful products. Your expertise and understanding of information plays as great a role in your decisions as the information itself.


  • Designing with data has to go beyond algorithms, automation, A/B testing, and analytics. Rather, the goal is to use all the data to develop a better understanding of everyday experience.

Good product design comes from striking the right balance between data, empathy and intuition.

What you can do:

  • Understand what user behavior is driving the metric, don’t use the metric as is.
  • Ask if you are measuring the right things.
  • Think about the context of the data. What was the user experience for this experiment?
  • Force yourself to consider all the opinions of why the results of the analysis might be wrong. Play devil’s advocate.

“Data and A/B test are valuable allies, and they help us understand and grow and optimize, but they’re not a replacement for clear-headed, strong decision-making. Don’t become dependent on their allure. Sometimes, a little instinct goes a long way.” - Julie Zhuo, VP of Product Design at Facebook

Watch More

Adam Mosseri - Data-Informed, Not Data-Driven

Rochelle King - The complex relationship between data and design in UX

Jen Matson - Measuring the Wrong Thing: Data-Driven Design Pitfalls

Michael Anthony - Data-Informed Decision Making

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Why you should be data-informed and not data-driven

Data-driven vs. data-informed design in enterprise products

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