User Analytics
What it is
User analytics is the collection and analysis of how real users interact with an application — page views, sessions, funnels, retention, clicks, geography, device, and journey paths — to understand behavior and satisfaction. In an Azure context it is typically instrumented through Application Insights and powered by its telemetry + KQL queries.
Why it exists
Performance monitors tell you a server is healthy, but user analytics tells you whether people actually use and value the product. It exists to answer “are users getting value?” — which is the insight that drives product decisions and ties back into continuous feedback.
Key ideas
- Signals tracked: page views, sessions, users, click/feature events, funnel steps (where users drop off), retention over time, geo/device breakdown.
- Where it lives: App Insights Browser/usage telemetry and custom events, queried with KQL over the Log Analytics store.
- Workbooks/views: usage analytics render as funnels, cohorts, and date-range comparisons (not just raw KQL).
- User analytics answers behavioral questions (“what do users do?”) while feature usage answers product-adoption questions (“which features get used?”).
Exam notes
- Pair user analytics (behavior) with feature usage (adoption) — the exam treats both as the user side of continuous feedback.
- Know it’s instrumented via Application Insights and analyzed with KQL.
- The point of collecting it is to feed back into the backlog/planning (a feedback-loop), not just to display dashboards.
Related
application-insights · feature-usage · feedback-loop · continuous-feedback · telemetry
📘 Source: Microsoft Learn — User Analytics