Summary
As a product designer, do you trust data when it defies your intuition? What about those times when following data leads you astray? How can you balance the need for experimentation and iteration with the dangers of over-optimization? What are some of the ways that being "data driven" can go wrong? Follow along and learn about the Amplitude design team's journey blending qualitative and quantitative research to drive design strategy—while balancing quality and velocity.
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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