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Design: Data-Informed Design

UXmatters has published 11 articles on the topic Data-Informed Design.

Top 3 Trending Articles on Data-Informed Design

  1. Designing with Analytics

    Data-Informed Design

    Understanding data to achieve great user experiences

    A column by Pamela Pavliscak
    June 22, 2015

    When we think of analytics, we think of marketing campaigns and funnel optimization. Analytics can seem a little overwhelming, with so many charts and lots of new features. How can we use analytics for design insights?

    The best thing about analytics is that they can show us what people do on their own. The worst thing is that analytics don’t tell us much about context, motivations, and intent. Like any kind of data, there are limitations. But that doesn’t mean analytics aren’t useful. Working with analytics is about knowing where to look and learning which questions you can reasonably ask. Read More

  2. Predictive User Experience

    June 19, 2017

    Envision coffee machines that start brewing just when you think it’s a good time for an espresso, office lights that dim when it’s sunny and workers don’t need them, your favorite music app playing a magical tune depending on your mood, or your car suggesting an alternative route when you hit a traffic jam.

    Predictability is the essence of a sustainable business model. In a digital world, with millions of users across the globe, prediction definitely has the power to drive the future of interaction. Feeding a historical dataset into a system that uses machine-learning algorithms to predict outcomes makes prediction possible. Read More

  3. Data-Driven Design: An Integral Part of UX Design

    October 5, 2020

    “What’s measured gets managed. Numbers have an important story to tell.”—Peter Drucker.

    What is data-driven design (DDD) and why should we care about it? UX design uses research data of various kinds to determine how to provide an optimal user experience. Forbes has described some key customer analytics, including customer satisfaction, lifetime-value, segmentation, sales-channels, Web, social-media, engagement, churn, and acquisition analytics. This data helps product teams understand their target users, reveals information about users’ painpoints, unearths new trends, supports data-driven design, and assures teams that their work is on track. User data can lead directly to improved business outcomes. UX methods incorporate data-driven design, which has proven, tangible results. Read More

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