Rideshare Subscription: Finding and Ranking the Experiences That Hurt Members Most

Quick Overview

Asks a product manager who owns a ride-hailing app's paid membership program how to find the experiences that hurt members most. It tests how the candidate defines a negative experience, combines behavioral data with customer feedback, and ranks problems by reach and impact on retention.

Rideshare Subscription: Finding and Ranking the Experiences That Hurt Members Most

Company: DoorDash

Role: Product Manager

Category: Analytics & Experimentation

Difficulty: medium

Interview Round: Other

You are the product manager for the paid membership program of a ride-hailing app. How would you find out which member experiences are the most negative? ```hint Define "worst" first Decide what makes one bad experience worse than another for someone who pays for the membership, and how you could measure that, before you list data sources. ``` ### Clarifying Questions - Which benefits does the membership include (for example ride discounts, priority matching, waived fees or partner perks), and does it renew automatically? - Should the analysis cover only failures of membership benefits, or any ride problem a member runs into? - Which outcome matters most: fewer membership cancellations, higher satisfaction, or more rides per member? - Which data can I use: trip logs, billing records, support tickets, ride ratings and surveys? ### What a Strong Answer Covers - A definition of a negative member experience that separates broken membership promises from ride problems every rider faces, and a way to measure how severe each one is - Behavioral and customer-feedback data sources, and the biases each one carries - A ranking method that combines how many members are affected with the measured effect on outcomes such as cancellation and ride frequency, without mistaking correlation for cause - Validation through qualitative research, and a path from the ranking to fixes and ongoing monitoring ### Follow-up Questions - Survey answers say price is the worst experience, but cancellation data points to slow pickups. How do you reconcile the two? - How would you tell whether a member cancelled because of a bad experience or simply because they stopped needing rides? - Once you have the top three experiences, how would you decide which to fix first?

Overview: Asks a product manager who owns a ride-hailing app's paid membership program how to find the experiences that hurt members most. It tests how the candidate defines a negative experience, combines behavioral data with customer feedback, and ranks problems by reach and impact on retention.

DoorDash logo
DoorDash
Feb 17, 2026
mediumProduct ManagerOtherAnalytics & Experimentation
0
0

You are the product manager for the paid membership program of a ride-hailing app. How would you find out which member experiences are the most negative?

Clarifying Questions Guidance

  • Which benefits does the membership include (for example ride discounts, priority matching, waived fees or partner perks), and does it renew automatically?
  • Should the analysis cover only failures of membership benefits, or any ride problem a member runs into?
  • Which outcome matters most: fewer membership cancellations, higher satisfaction, or more rides per member?
  • Which data can I use: trip logs, billing records, support tickets, ride ratings and surveys?

What a Strong Answer Covers Guidance

  • A definition of a negative member experience that separates broken membership promises from ride problems every rider faces, and a way to measure how severe each one is
  • Behavioral and customer-feedback data sources, and the biases each one carries
  • A ranking method that combines how many members are affected with the measured effect on outcomes such as cancellation and ride frequency, without mistaking correlation for cause
  • Validation through qualitative research, and a path from the ranking to fixes and ongoing monitoring

Follow-up Questions Guidance

  • Survey answers say price is the worst experience, but cancellation data points to slow pickups. How do you reconcile the two?
  • How would you tell whether a member cancelled because of a bad experience or simply because they stopped needing rides?
  • Once you have the top three experiences, how would you decide which to fix first?