How to Build Data Experiences for End Users

How to Build Data Experiences for End Users

Organizational data literacy is regularly addressed, but it’s uncommon for product managers to consider users’ data literacy levels when building products. Product managers need to research and recognize their end users' data literacy when building an application with analytic features. Otherwise, it can lead to a low adoption rate and a poor product experience.

End users fall into 4 different categories along the data literacy continuum when it comes to their skill level with data:

  • Data challenged: Users have no-to-low levels of analytics skills or data access.
  • Data literate: Users have a comfort level of working with, manipulating, analyzing, and visualizing data.
  • Data aware: Users can combine past experiences, intuition, judgment, and qualitative inputs and data analysis to make decisions.
  • Data fluent: Users can go beyond insights and instinct to communicate, collaborate, tell stories, and drive ideas to make decisions based on data.

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