How to Lead With Data, and Without Data
Summary
Key Insights
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Designers are increasingly using data not only to improve UX but to influence product strategy at higher business levels.
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Too much focus on metrics can lead to over-optimization, harming user experience despite metric improvement.
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Amplitude developed a framework categorizing projects by ambiguity: blue sky, horizontal, vertical, and paper cuts, guiding the choice of metrics and evaluation.
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Blue sky projects require no gating short-term metrics because their impact unfolds over longer horizons.
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Executive buy-in for major initiatives improves when qualitative feedback is segmented and linked to long-term business goals alongside metrics.
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Redesigning Amplitude’s core chart controls increased user efficiency and conversion by 25%, demonstrating successful data-informed design.
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Data literacy involves learning the language of metrics relevant to your business and connecting UX improvements to measurable business outcomes.
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Data must be treated critically: the same data visualized differently can mislead if axes or contexts are adjusted to bias interpretation.
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Building personal relationships with data scientists and aligning cross-functional goals encourages collaboration and better data use.
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A continuous feedback loop combining qualitative research and quantitative data strengthens design hypotheses and strategic initiatives.
Notable Quotes
"It’s a great time to be a designer to make data-driven design decisions that impact beyond just pixels."
"We became addicted to our loop of over-optimization, driving traffic to certain features but frustrating users."
"Blue sky projects should have no gating metrics and no short-term metrics because their value is long-term."
"The chart controls were circular and confusing; users looked like deer in headlights not knowing where to start."
"Executives first want to know what metric you will impact next quarter before approving big initiatives."
"Data is a language you need to learn to speak and a mindset that must be continuously practiced."
"You can draw a convincing dotted line between a UX improvement and a hard business outcome if you practice."
"We improved the core chart experience performance by 25%, faster time to save and to first edit have major impact."
"Data is expressive, but just because it’s a chart doesn’t mean the data is true or fair."
"Building personal relationships with data scientists and aligning team goals melts away silos and incentives."
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