Design an A/B test for a recommendation algorithm

Last updated: July 17, 2025

Quick Overview

Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.

Tesla
Analytics & Experimentation
Product Manager
Tesla
July 17, 2025
Product Manager
Phone Screen
Analytics & Experimentation
Easy

3

6

3,816 solved


Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.

Tesla asks this during the Phone Screen to assess your experimentation skills. They want to see how you define success metrics, design controlled experiments, and interpret results with appropriate statistical rigor.

What the Interviewer Expects
  • Define clear success metrics aligned with business goals
  • Propose a basic experimental design with control and treatment groups
  • Interpret results correctly and draw reasonable conclusions
  • Identify obvious confounding variables
Key Topics to Cover
Guardrail metrics
Long-term vs short-term metrics
Network effects and interference
Segmentation and heterogeneous effects
Simpson's paradox and ecological fallacy
Novelty and primacy effects
How to Approach This
  1. Define success metrics carefully. A good metric is measurable, actionable, and aligned with business goals.
  2. Run experiments long enough to account for novelty effects and weekly seasonality.
  3. Use funnel analysis to identify where users drop off for maximum optimization impact.
  4. Segment results by key dimensions (platform, country, user cohort) to catch hidden patterns.
  5. Consider network effects and interference between treatment and control groups.
Possible Follow-up Questions
  • How would you handle an experiment where the control and treatment groups are different sizes?
  • What would you do if a stakeholder wants to end the experiment early because initial results look good?
  • What if the experiment shows a positive short-term effect but you suspect a negative long-term impact?
  • What if you discover a bug in the logging during the experiment?
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