Interpret mixed results across segments from an experiment

Last updated: June 11, 2026

Quick Overview

An experiment shows conflicting results. What conclusions can you draw? What are the caveats?

Doordash
Analytics & Experimentation
Product Manager
Doordash
June 11, 2026
Product Manager
Onsite
Analytics & Experimentation
Medium

29

6

852 solved


An experiment shows conflicting results. What conclusions can you draw? What are the caveats?

Doordash asks this during the Onsite 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
Sample size and power calculation
Long-term vs short-term metrics
Segmentation and heterogeneous effects
Metric definition and success criteria
Network effects and interference
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 if the experiment shows a positive short-term effect but you suspect a negative long-term impact?
  • How would you handle seasonality in your experiment?
  • How would you handle an experiment where the control and treatment groups are different sizes?
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