what metrics would you use to evaluate mobike's dynamic pricing system?

Introduction

Evaluating Mobike's dynamic pricing system requires a comprehensive approach to product success metrics. To address this challenge effectively, I'll follow a structured framework that covers core metrics, supporting indicators, and risk factors while considering all key stakeholders. This approach will help us assess the effectiveness of the pricing system and its impact on Mobike's overall business goals.

Step 1

Product Context

Mobike's dynamic pricing system is a crucial feature of their bike-sharing service, designed to optimize bike availability and revenue. The system adjusts prices in real-time based on factors such as demand, supply, time of day, and location.

Key stakeholders include:

1. Users: Seeking affordable, convenient transportation
2. Mobike: Aiming to maximize revenue and operational efficiency
3. City authorities: Interested in reducing traffic congestion and promoting sustainable transport
4. Investors: Looking for profitability and growth

User flow:

1. Open app and locate nearby bikes
2. View current price for the ride
3. Unlock bike and start ride
4. Complete ride and lock bike
5. Automatic payment based on ride duration and dynamic price

The dynamic pricing system fits into Mobike's broader strategy of optimizing resource allocation and maximizing revenue while maintaining user satisfaction. Compared to competitors like Ofo or Lime, Mobike's system aims to be more sophisticated in balancing supply and demand.

In terms of product lifecycle, the dynamic pricing system is in the growth stage, with ongoing refinements and optimizations based on data and user feedback.

Software considerations:

• Platform: Mobile app (iOS and Android)
• Integration points: Payment systems, GPS tracking, bike locks
• Deployment model: Cloud-based with real-time updates