Prioritize six improvements for a favorite app
Overview
This question evaluates a data scientist's product-thinking, prioritization, impact-estimation, experimentation design, and risk-mitigation competencies, framed within the Behavioral & Leadership domain and focused on product management, modeling, and experimentation.
Capital One
Oct 13, 2025, 9:49 PM
Data Scientist
Onsite
Behavioral & Leadership
0
0
Case Prompt: Product Thinking, Modeling, and Experimentation
Choose one consumer mobile app you personally use weekly.
-
Propose exactly six concrete, shippable improvements. For each improvement, specify:
- Target user
- User behavior you aim to change
- Primary success metric
- 14-day leading indicator
- Largest execution risk
- Build a back-of-the-envelope model to estimate each idea’s 90-day impact on the app’s north-star metric. State all assumptions and provide low/base/high ranges.
- Prioritize the six ideas using a transparent framework (e.g., RICE or expected ROI) under the constraint of one squad for one quarter. Identify the top priority and justify the trade-offs you accept as the CEO (e.g., revenue vs. retention, complexity, brand risk).
- Define an experiment plan for the top idea: experiment design, go/no-go criteria, guardrail metrics, and explicit kill conditions if early signals underperform.
- List two non-obvious failure modes and how you would mitigate them pre- and post-launch.
Solution
Login required
Show