Data analysis

Do you have all the useful data you need? Try to have a look at funnels, clicks, page views, performances.

In order to make the most of analytics data, UX professionals need to integrate this data where it can add value to qualitative processes instead of distract resources. The biggest issue with analytics is that it can very quickly become a distracting black hole of “interesting” data without any actionable insight. Many beginners get stumped over one of three hurdles:

  • Scope of metrics: So many things that can be measured, but which are meaningful?
  • Difference between metrics: Which metrics best answer specific questions?
  • Interface complexity: How do you get the analytics system to tell you what you want to find out?

Because of this last point, many people end up jumping in the deep end and focusing on the tool instead of the work that it is intended to support. With that in mind, we recommend that UX professionals back up a step and think about how analytics data can supplement current methods and processes.

We discovered some interesting high-value UX uses for analytics:

  1. Issue indication: Notifying the team of potential problems reaching goals
  2. Investigation: Identifying potential causes of issues
  3. Triangulation: Adding data to supplement qualitative research

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