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Product Management Trade-off Question: Airline app seat lock-in time optimization diagram

Asked at Amazon

15 mins

How will you decide lock-in time for a seat (before user makes the payment) on checkout page of an airline ticket app?

Product Trade-Off Medium Member-only
Data Analysis Experiment Design User-Centric Decision Making Travel E-commerce Airlines
User Experience Conversion Optimization A/B Testing Product Trade-Offs Travel Tech

Introduction

Determining the optimal lock-in time for a seat on an airline ticket app's checkout page is a critical product trade-off that directly impacts user experience, conversion rates, and revenue. This decision involves balancing user convenience with business needs and operational constraints. I'll analyze this trade-off by examining key stakeholders, metrics, and potential impacts, ultimately proposing an experiment to inform our decision-making process.

Analysis Approach

I'd like to outline my approach to this problem and ensure we're aligned on the key areas to explore.

Step 1

Clarifying Questions (3 minutes)

  • What's the current lock-in time, and why are we considering changing it?

  • Why it matters: Understanding the baseline and motivation helps frame the problem.
  • Hypothetical answer: Currently 10 minutes, considering change due to user complaints and cart abandonment.
  • Impact: Informs the range of options we'll consider and the primary pain points to address.
  • What's the average time users spend on the checkout page?

  • Why it matters: Helps determine a reasonable lock-in time that aligns with user behavior.
  • Hypothetical answer: Average time is 7 minutes, with 80% completing within 15 minutes.
  • Impact: Guides our decision on an appropriate lock-in time range to test.
  • What percentage of users abandon their carts during the checkout process?

  • Why it matters: Indicates the severity of the current problem and potential for improvement.
  • Hypothetical answer: 30% cart abandonment rate, higher than industry average.
  • Impact: Highlights the urgency of optimizing the lock-in time to improve conversion.
  • Are there any technical limitations affecting how quickly we can release and re-lock seats?

  • Why it matters: Technical constraints may limit our options or introduce additional considerations.
  • Hypothetical answer: System can handle seat status changes within 30 seconds.
  • Impact: Allows us to consider more dynamic lock-in time options if needed.
  • What's the competitive landscape like? How do our main competitors handle seat lock-in?

  • Why it matters: Provides context on industry standards and potential differentiation opportunities.
  • Hypothetical answer: Competitors range from 5 to 15 minutes, with some offering extensions.
  • Impact: Informs our strategy to balance user expectations with potential competitive advantages.

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