Usage Analytics: Understanding User Behavior
Overview
Using application telemetry to understand how real users interact with your product — behavior, feature adoption, and satisfaction — and turning that understanding into product decisions. This is the user side of continuous feedback.
Units
- Collecting user/usage telemetry
- Analyzing page views, sessions, funnels, and engagement
- Measuring feature adoption and drop-off
- Feeding insights into the backlog
Concepts introduced
- user-analytics — behavioral insights (page views, sessions, funnels, retention).
- feature-usage — which features are adopted/used (product-adoption lens).
- Application Insights — the instrumentation source for user telemetry.
- feedback-loop — how usage insights become planned work.
Key terms & commands
- Track custom events (e.g. “feature used”) in App Insights for adoption measurement.
- Pair adoption telemetry with feature flags: ship to a subset, measure, then roll out or kill.
- Analyze usage via KQL over App Insights data.
Hands-on
- Instrument custom events and build a usage/funnel query.
- Use feature-usage data to make a “keep / expose / retire” decision.
Exam focus
- User analytics = how users behave; feature usage = which features get used.
- Usage telemetry is only valuable when it feeds planning (the feedback loop).
Related
user-analytics · feature-usage · application-insights · feedback-loop · Path MOC