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Product Management Analytics Question: Measuring success of Mobike's bike-sharing system with key metrics

Asked at Mobike

12 mins

how would you measure the success of mobike's bike-sharing system?

Product Success Metrics Medium Member-only
Data Analysis Metric Definition Stakeholder Management Transportation Smart Cities Sharing Economy
Product Analytics Success Metrics Urban Mobility KPI Measurement Bike-Sharing

Introduction

Measuring the success of Mobike's bike-sharing system requires a comprehensive approach that considers multiple stakeholders and various aspects of the service. To effectively evaluate this product, I'll follow a structured framework covering core metrics, supporting indicators, and risk factors while considering all key stakeholders.

Framework Overview

I'll follow a simple success metrics framework covering product context, success metrics hierarchy.

Step 1

Product Context

Mobike's bike-sharing system is a dockless bicycle rental service that allows users to locate, rent, and return bicycles using a smartphone app. Key stakeholders include:

  1. Users: Seeking convenient, affordable short-distance transportation
  2. Mobike: Aiming for profitability and market expansion
  3. City governments: Interested in reducing traffic congestion and promoting sustainable transportation
  4. Investors: Looking for growth and return on investment

User flow:

  1. Locate a nearby bike using the app
  2. Scan QR code to unlock the bike
  3. Ride to destination
  4. Park the bike in a designated area
  5. End the trip via the app

Mobike fits into the broader strategy of smart city initiatives and last-mile transportation solutions. Competitors include Ofo and Lime, with Mobike differentiating through its robust bikes and data-driven operations.

Product Lifecycle Stage: Growth phase, with rapid expansion into new markets and continuous refinement of the service based on user feedback and operational data.

Hardware considerations:

  • Bike durability and maintenance
  • Lock mechanism reliability
  • GPS tracking accuracy

Software considerations:

  • App performance and user experience
  • Backend systems for bike tracking and payments
  • Data analytics for demand prediction and bike redistribution

Physical Product considerations:

  • Bike distribution strategy
  • Parking and storage solutions
  • Maintenance and repair logistics

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