Product instrumentation tells us when and how much people use different aspects of our product. This insight can inform feature prioritization, validate our assumptions, and identify potential user problems.
Research participants are more vulnerable than ever as researchers conduct remote usability tests, use third-party applications, and store data online. Protect participant privacy by adhering to best practices before, during, and after data collection.
Dashboards that monitor vast masses of data should guide users' attention to critical values but not by flashing endless alerts without prioritization.
Members of a design team will often argue for different solutions to a UI problem. That's when to say "show me the data" to resolve the debate by empirical insights, rather than who argues the best.
Spreadsheet defaults don't generate the most meaningful visualizations of UX data. Modify charts to enhance Context, Clutter (less of it than spreadsheet software likes!), and Contrast.
To gain a holistic picture of your users, exchange data with the non-UX teams in your company who are collecting other forms of customer data, besides the user research you do yourself. You gain; they gain.
To enable fast and reliable understanding of data shown on dashboard overviews, use visualization styles that work with human preattentive visual processing.
The most desired user actions (macroconversions) may be too rare to generate enough analytics data for fast design iteration, so we can also analyze smaller user actions (microconversions) that are more frequent and are connected to bigger goals.
