Splunk·Product Manager·Onsite - Product Sense / Strategy·Senior

Senior

Jul 2026

Summary

PM interview at Splunk with a product sense question that required picking a consumer app and designing two features end to end. Pretty demanding scope for a single question, covering personas, journeys, tech feasibility, and metrics all at once.

Questions Asked (1)

Pick a consumer app you admire. Propose two new features that improve it. For each, walk through the target persona, user journey, technical feasibility including backend services and data flows, and how you'd measure success.

Product Sense & IdeationSystem DesignProduct Analytics & Metrics

Author's notes

I went with a music streaming app and immediately regretted how crowded that space is for these questions.

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AI HintsAI Generated

Suggested Approach

Choose a widely-used consumer app you know deeply, then propose two features that address clear user pain points and align with the company's strategic goals. For each feature, structure your answer around persona, journey, technical feasibility, and metrics, ensuring you connect the dots between user value and business impact. Keep the technical explanation accessible but demonstrate understanding of backend services, data flows, and measurement frameworks.

Pro tip: Tie your success metrics to a north-star metric and show how you'd instrument the feature to measure both leading and lagging indicators, including guardrail metrics to catch unintended consequences.

1. Select the app and features

Pick a consumer app you genuinely admire and know well, then brainstorm two features that solve real user problems and fit the app's vision. Briefly justify why these features matter now.

2. Define target persona and user journey

For each feature, describe a specific persona (demographics, goals, pain points) and map their current journey vs. the improved journey with the feature. Highlight the friction points the feature removes.

3. Assess technical feasibility

Outline the backend services, data flows, and any third-party integrations required. Discuss potential technical challenges (e.g., scalability, latency, data privacy) and how you'd mitigate them.

4. Define success metrics

Propose a mix of metrics: adoption (e.g., % of users using feature), engagement (e.g., frequency), and business impact (e.g., retention, revenue). Include leading and lagging indicators, and guardrail metrics.

5. Summarize and prioritize

Conclude by comparing the two features in terms of impact, effort, and strategic alignment. Recommend which to build first and why, showing product prioritization skills.

Key Points to Mention

Clear problem statement and user pain point for each feature
Persona details that make the target user tangible (e.g., goals, behaviors)
End-to-end user journey mapping with before/after states
Backend architecture: APIs, databases, microservices, and data flow diagrams (verbal)
Metrics framework: north-star, leading/lagging, and guardrail metrics
Prioritization rationale (e.g., RICE, impact vs. effort) and trade-offs

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.