The Amazon framing threw me a bit since I was interviewing at TikTok, so I spent a second wondering if there was a trick to it.
Start by clarifying the context and defining churn metrics, then segment customers to identify root causes through data analysis. Prioritize improvements based on impact and effort, and propose a test-and-learn plan to validate solutions and measure success.
Pro tip: Show that you balance qualitative insights (customer interviews) with quantitative data (funnel analysis) to avoid solving the wrong problem. Also, tie your recommendations to business impact, like LTV and retention rates.
Ask clarifying questions to understand the scope: what defines churn, which customer segments are affected, and what the business impact is. Define success metrics like churn rate reduction and improved NPS.
Analyze data to identify where in the customer journey churn occurs (e.g., onboarding, engagement, support). Use funnel analysis, cohort analysis, and customer feedback to pinpoint pain points.
Segment customers by behavior, demographics, or tenure to understand varying needs. Prioritize segments based on business value and ease of impact, focusing on high-value or at-risk groups.
Brainstorm improvements for each stage of the journey, such as personalized onboarding, proactive support, or feature enhancements. Validate with A/B tests or prototypes, measuring against defined metrics.
Roll out successful changes, monitor key metrics, and iterate based on feedback. Establish a continuous improvement loop to adapt to evolving customer needs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.