← JP Morgan Chase Interview Insights
My first instinct was to just list UX problems but that felt too shallow.
Start by clarifying the funnel and metrics (e.g., time period, user segments, definition of drop-off) to ensure you understand the problem. Then, hypothesize potential causes across the user journey, prioritizing technical, UX, and external factors. Finally, propose a data-driven approach to validate each hypothesis and suggest actionable improvements.
Pro tip: Demonstrate a structured, hypothesis-driven mindset by mentioning that you would first check if the drop-off is uniform or concentrated at specific steps, and consider both qualitative (user feedback) and quantitative (analytics) data to pinpoint the root cause.
Ask questions to understand the funnel: What are the exact start and submission pages? What is the time frame? Are there specific user segments (e.g., new vs. returning, device type)? This ensures you're solving the right problem.
Break down the application process into discrete steps (e.g., form filling, document upload, verification). Identify where the 55% drop-off occurs—is it evenly distributed or concentrated at certain steps?
Brainstorm potential causes across categories: technical (bugs, slow load times), UX (confusing interface, too many fields), external (lack of trust, required documents not handy), and user intent (just browsing).
Prioritize hypotheses based on impact and ease of testing. Suggest using analytics (funnel analysis, session recordings), A/B tests, and user feedback to validate the most likely causes.
Propose actionable fixes for the validated causes, such as simplifying forms, improving error handling, adding progress indicators, or offering save-and-resume functionality.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.