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Level 8 / Project 14 - User Journey Tracer

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— This project — — Flashcards — —

Focus

  • Event stream processing and session reconstruction
  • Session splitting by inactivity timeout gaps
  • Funnel analysis with stage-to-stage conversion rates
  • Drop-off detection to identify UX bottlenecks
  • Group-by aggregation patterns for analytics

Why this project exists

Understanding how users flow through a system is essential for debugging, optimization, and product analytics. Why do 40% of users abandon checkout at the payment step? Where do new users get stuck during onboarding? This project builds a journey tracer that reconstructs user sessions from raw event streams, identifies drop-off points, and computes conversion funnels — the same pattern used by Amplitude, Mixpanel, and custom product analytics systems.

Run (copy/paste)

cd <repo-root>/projects/level-8/14-user-journey-tracer
python project.py --demo
pytest -q

Expected terminal output

{
  "journeys_count": 5,
  "funnel": {"stages": [...], "conversion_rates": [...]},
  "drop_off_points": [...]
}
7 passed

Expected artifacts

  • Console JSON output with journey analysis and funnel data
  • Passing tests
  • Updated notes.md

Alter it (required)

  1. Add a session_timeout_minutes parameter to reconstruct_journeys that splits sessions by inactivity.
  2. Add drop-off analysis: for each funnel stage, report what percentage of users left.
  3. Add a --user filter flag that traces only a specific user's journeys.

Break it (required)

  1. Pass events with unsorted timestamps — does reconstruct_journeys produce correct sessions?
  2. Create a funnel with stages not present in any events — what does analyze_funnel return?
  3. Pass an empty event list — does the journey reconstruction handle it gracefully?

Fix it (required)

  1. Sort events by timestamp inside reconstruct_journeys before grouping.
  2. Return 0% conversion for funnel stages with no matching events.
  3. Add a test for empty input and unsorted timestamps.

Explain it (teach-back)

  1. What is a user journey and how does event-based tracing reconstruct it?
  2. How does funnel analysis measure conversion between stages?
  3. Why does session splitting use a timeout gap between events?
  4. How do analytics platforms like Amplitude or Mixpanel implement similar journey tracing?

Mastery check

You can move on when you can: - explain user journeys, sessions, and funnel analysis with examples, - add a new funnel stage and trace it through real event data, - describe the difference between session-based and user-based analytics, - explain how drop-off rates help identify UX problems in a product.

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