How can Getaround improve its car search filters to help renters find the perfect vehicle more quickly?

Introduction

To improve Getaround's car search filters and help renters find the perfect vehicle more quickly, we need to analyze user behavior, identify pain points, and develop targeted solutions. I'll approach this by examining user segments, analyzing their journey, and proposing data-driven improvements to the search experience.

Step 1

Clarifying Questions

• Looking at Getaround's position in the car-sharing market, I'm curious about the primary use cases driving our current user base. Could you share insights on whether most rentals are for short-term, local use, or if we're seeing a significant portion of longer-term or travel-related rentals?

Why it matters: This will help us tailor our search filters to match the most common rental scenarios. Expected answer: A mix, with a slight majority towards short-term, local rentals. Impact on approach: We'd prioritize filters relevant to quick, local trips while still accommodating longer-term needs.

• Considering the evolving landscape of transportation, I'm wondering about our user demographics and their environmental consciousness. Are we seeing a trend towards users specifically seeking out electric or hybrid vehicles?

Why it matters: This could influence how we prioritize and display eco-friendly options in our search filters. Expected answer: Yes, there's a growing interest, especially among younger urban users. Impact on approach: We might consider prominently featuring an "eco-friendly" filter or badge system.

• Given the competitive nature of the car-sharing market, I'm interested in understanding our current user retention rates. Can you share any data on how frequently users return to Getaround for subsequent rentals?

Why it matters: This helps us determine if we should focus more on improving the experience for new users or on features that cater to repeat customers. Expected answer: Moderate retention, with room for improvement. Impact on approach: We might consider personalized filters based on past rental history for returning users.

• Thinking about the technical aspects of our platform, I'm curious about the current architecture of our search functionality. Are we using a modern, scalable search engine that can handle complex filtering and sorting?

Why it matters: This impacts the complexity and feasibility of potential improvements we can implement. Expected answer: Using a relatively modern system, but with some limitations. Impact on approach: We might need to balance ambitious filter improvements with technical constraints.