Design an A/B test for a new checkout flow

Last updated: August 16, 2025

Quick Overview

Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.

Robinhood
Analytics & Experimentation
Data Scientist
Robinhood
August 16, 2025
Data Scientist
Technical Screen
Analytics & Experimentation
Medium

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2,915 solved


Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.

Robinhood asks this during the Technical 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
  • Design a rigorous experiment with proper randomization and sample size calculation
  • Define primary and guardrail metrics with clear rationale
  • Address novelty effects, network effects, and interference
  • Segment results appropriately and identify heterogeneous treatment effects
  • Propose follow-up analyses when results are ambiguous
Key Topics to Cover
Funnel analysis and cohort analysis
Sample size and power calculation
A/B testing methodology
Segmentation and heterogeneous 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
  • What would you do if a stakeholder wants to end the experiment early because initial results look good?
  • How would you handle seasonality in your experiment?
  • How would you handle interference between treatment and control?
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