For Musinsa's mobile app, should we emphasize personalized product recommendations to increase engagement or simplify the interface for easier navigation and faster purchases?

Introduction

For Musinsa's mobile app, we're facing a critical trade-off between emphasizing personalized product recommendations to increase engagement and simplifying the interface for easier navigation and faster purchases. This decision will significantly impact user experience, engagement metrics, and ultimately, our bottom line. I'll analyze this trade-off by examining our product context, key metrics, and potential experiments to inform our decision.

Step 1

Clarifying Questions (3 minutes)

• Based on our current market position, I'm thinking this decision could significantly impact our competitive edge. Could you share how our app's performance compares to our main competitors in terms of user engagement and conversion rates?

Why it matters: Helps contextualize the urgency and potential impact of this decision. Expected answer: We're slightly behind in engagement but ahead in conversions. Impact on approach: Would focus on balancing engagement improvement with maintaining our conversion advantage.

• Considering our revenue model, I assume we operate on a commission-based structure. Is this correct, and if so, what's our current average order value (AOV) trend?

Why it matters: Informs whether we should prioritize increasing purchase frequency or AOV. Expected answer: Commission-based model with stable AOV. Impact on approach: Might lean towards simplifying interface if it could increase purchase frequency.

• Looking at our user segments, I'm curious about the split between power users and occasional shoppers. Do we have data on this distribution and their respective behaviors?

Why it matters: Different user segments may benefit more from personalization or simplification. Expected answer: 20% power users generating 80% of revenue. Impact on approach: Could suggest a hybrid solution catering to both segments.

• Regarding our tech stack, I'm wondering about our current personalization capabilities. How sophisticated is our recommendation engine, and what data points does it use?

Why it matters: Determines the potential impact and feasibility of enhancing personalization. Expected answer: Basic collaborative filtering with room for improvement. Impact on approach: Might identify quick wins in personalization before deciding on interface changes.

• Considering our product roadmap, are there any major features or integrations planned that could affect this decision?

Why it matters: Ensures our decision aligns with long-term product strategy. Expected answer: Planned integration with a new payment system in Q4. Impact on approach: Could influence timing and scope of interface simplification efforts.