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Product Management Improvement Question: Uber PM tackling low ride ratings through data-driven solutions

You're the PM of Uber. The ride rating is 20% less than the industry standards. How do you solve this?

Product Improvement Medium Member-only
Problem-Solving Data Analysis User-Centric Design Transportation Technology Gig Economy
User Experience Product Improvement Data Analysis Ride-Sharing Customer Satisfaction

Introduction

As the PM of Uber, I'm faced with a critical challenge: our ride rating is 20% below industry standards. This issue directly impacts user trust, driver satisfaction, and our overall market position. To address this, we'll need to dive deep into our user experience, identify key pain points, and develop innovative solutions that align with Uber's broader strategic goals.

Step 1

Clarifying Questions

  • Looking at the product context, I'm thinking about the specific metrics that make up our ride rating. Could you clarify if this 20% gap is consistent across all rating components (e.g., driver professionalism, vehicle cleanliness, ride experience) or if it's concentrated in particular areas?

Why it matters: Helps focus our efforts on the most impactful areas for improvement. Expected answer: The gap is more pronounced in ride experience and driver professionalism. Impact on approach: Would prioritize solutions targeting these specific aspects.

  • Considering user behavior, I'm curious about the rating submission rate. Are we seeing a lower percentage of users leaving ratings compared to industry standards, or is it primarily the ratings themselves that are lower?

Why it matters: Determines if we need to focus on encouraging more ratings or improving the experience itself. Expected answer: Rating submission rate is on par with industry standards. Impact on approach: Would focus on improving the actual ride experience rather than just increasing rating volume.

  • Examining our product lifecycle, I'm wondering about recent feature changes or updates that might have coincided with this drop in ratings. Have there been any significant product changes in the past 6-12 months that could be contributing factors?

Why it matters: Helps identify if recent changes have unintended consequences we need to address. Expected answer: A new driver allocation algorithm was implemented 8 months ago. Impact on approach: Would investigate the impact of this algorithm on user satisfaction and potentially refine it.

  • Considering external factors, I'm interested in understanding if this rating gap is consistent across all markets or if it's more pronounced in specific regions or cities.

Why it matters: Allows us to determine if this is a global issue or if we need to tailor solutions to specific markets. Expected answer: The gap is more significant in larger urban areas. Impact on approach: Would prioritize solutions for high-density urban environments first.

Tip

Now that we've gathered this crucial information, let's take a brief moment to organize our thoughts before moving on to user segmentation.

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