StackSight –
Product Analytics Platform
StackSight helps product teams understand how people use their application. It combines usage metrics, conversion funnels, retention cohorts and automatically generated insights in one simple dashboard.
Four useful analytics tools
Each feature answers a common product question using simple, understandable data.
Real-time analytics
Monitor active users, sessions and page views to understand current product activity.
Answers: “How is the product being used?”Conversion funnel
Follow users through Visitors → Sign-ups → Activated → Paid and identify drop-offs.
Answers: “Where are users leaving?”User cohorts
Group users by signup week and compare how many return over the following weeks.
Answers: “Are users staying active?”AI insights
Generate clear observations from changes and patterns found in the analytics data.
Answers: “What should the team notice?”Explore the StackSight dashboard
Use the menu to switch between analytics views. All values are realistic sample data prepared for this demonstration.
Analytics overview
A summary of product usage for the selected period.
How I approached this feature
This section provides a straightforward explanation that can be used during the college presentation.
Problem being solved
Product teams collect large amounts of usage data but often struggle to understand it quickly. StackSight organizes the most important information into understandable views.
How StackSight works
The application receives user events, calculates metrics such as conversion and retention, then displays the results using charts, funnels, tables and observations.
Features demonstrated
Dashboard navigation, state management, date filtering, reusable components, data visualization, responsive design and basic insight generation.
Simple tools for a clear result
- ReactInteractive interface
- TypeScriptStructured data
- CSSResponsive layout
- Sample eventsRealistic demonstration
Example insight“StackSight detected that users completing onboarding are 18% more likely to remain active after four weeks.”
This observation is generated by comparing the retention of users who completed onboarding against those who did not.