Should MFine prioritize expanding its AI-powered symptom checker or focus on enhancing its video consultation platform to improve user retention?

Introduction

The trade-off we're examining today is whether MFine should prioritize expanding its AI-powered symptom checker or focus on enhancing its video consultation platform to improve user retention. This decision is crucial for MFine's growth strategy and user experience. I'll analyze this trade-off by examining the product context, potential impacts, key metrics, and experimental approaches to inform a data-driven recommendation.

Step 1

Clarifying Questions (3 minutes)

• Based on MFine's current market position, I'm thinking user retention might be a critical challenge. Could you share some context on our current retention rates and how they compare to industry benchmarks?

Why it matters: Helps quantify the retention problem and its impact on the business. Expected answer: Below industry average, significant drop-off after first use. Impact on approach: Would emphasize immediate action on retention-focused features.

• Considering our revenue model, I'm assuming we have a mix of free and paid services. What's the current split between revenue from AI symptom checker vs. video consultations?

Why it matters: Identifies which product area is currently driving more revenue. Expected answer: Video consultations generate more revenue, but AI checker has higher engagement. Impact on approach: Would influence resource allocation based on revenue potential.

• Looking at user behavior, I'm curious about the typical user journey. Do users generally start with the AI symptom checker before moving to video consultations, or vice versa?

Why it matters: Helps understand the relationship between the two features and potential synergies. Expected answer: Most users start with AI checker, but conversion to video consultations is low. Impact on approach: Would focus on improving the transition between AI and human consultations.

• From a technical perspective, I'm wondering about the current state of our AI capabilities. How accurate is our symptom checker compared to human diagnoses?

Why it matters: Assesses the readiness of AI technology for expansion. Expected answer: Accuracy is good but not excellent, room for improvement. Impact on approach: Would influence decision on whether to invest more in AI development.

• Regarding our team structure, how are our engineering and product resources currently allocated between AI and video consultation features?

Why it matters: Helps understand the feasibility of shifting focus without major restructuring. Expected answer: More resources currently dedicated to video consultations. Impact on approach: Would inform how quickly we could pivot to AI expansion if chosen.