For Getaround's instant booking feature, should we focus on increasing availability or maintaining strict quality standards for listed vehicles?

Introduction

The trade-off between increasing availability and maintaining strict quality standards for Getaround's instant booking feature presents a critical decision point for the platform's growth and user satisfaction. This scenario touches on the core value proposition of Getaround: providing convenient, reliable access to shared vehicles. I'll analyze this trade-off by examining its impact on key stakeholders, metrics, and long-term business goals.

Step 1

Clarifying Questions (3 minutes)

• Based on recent market trends, I'm thinking user demand for instant bookings might be surging. Could you share any data on the growth of instant booking requests over the past quarter?

Why it matters: Helps gauge the urgency of increasing availability. Expected answer: 30% increase in instant booking requests. Impact on approach: High growth would prioritize availability over strict quality standards.

• Considering our revenue model, I assume we take a percentage of each booking. Is this correct, and are there any differences in our take rate for instant vs. regular bookings?

Why it matters: Clarifies the direct financial impact of instant bookings. Expected answer: Yes, with a slightly higher take rate for instant bookings. Impact on approach: Higher take rate for instant bookings would further justify focusing on availability.

• Looking at user segments, I'm curious about the profile of users who prefer instant bookings. Do we have data on whether they're primarily new or returning users?

Why it matters: Helps understand the impact on user acquisition and retention. Expected answer: Mix of both, with a slight skew towards new users. Impact on approach: If skewed towards new users, might prioritize availability to drive growth.

• Regarding our current quality standards, what's our threshold for vehicle acceptance, and how does it compare to industry benchmarks?

Why it matters: Establishes a baseline for quality and potential room for adjustment. Expected answer: Above industry average, with strict cleanliness and maintenance requirements. Impact on approach: If significantly above average, might consider slightly relaxing standards to increase availability.

• Considering our tech infrastructure, how quickly can we implement and test changes to our instant booking algorithm?

Why it matters: Determines the feasibility of rapid experimentation. Expected answer: Can implement A/B tests within 2-3 weeks. Impact on approach: Quick implementation would allow for more iterative testing of different quality thresholds.