How Usage Analytics Can Improve End User Experience?
summary
Defines five measurable usage signals—features/pages used, task completion and drop-off points, browsers/devices/resolutions, and stability/performance—and shows how to extract them from production logs and tools. Gives concrete splits (example: 84% Android traffic, iOS ~11%, web ~3–4%) and recommends prioritizing testing on top devices and workflows. Demonstrates using a customer-journey tool—Azure Application Insights user flow engine—to pick the top 10–15 regression flows, run real‑time or offline analysis, and catch pain points early to cut rework and testing cost.
AI-written summary · about
chapters (8)
- 0:00Introduction to usage analytics
- 0:21Why analyze usage behavior
- 1:03Top five areas for usage analysis
- 3:29How customers access the app
- 4:13What customers do in the app
- 8:04Aligning testing with real usage
- 10:52Benefits of real-time analysis
- 11:55Summary and Q&A
related talks
18mProduct Usage Metrics - Practical Lessons from the Trenches
41mThe What, Why and How of Web Analytics Testing
06mMeasurement is Not Enough: Rise of Performance Analytics
11mAre They Really Using It? Monitoring Digital Experience To Determine Feature Effect
46mUsing Analytics to Improve Quality
45mDon't trust the numbers!
30mHow to collect application metrics if it needs to be done yesterday
21mData Analytics for Better Product Decision Making