Explain difference-in-differences with an example

Last updated: November 2, 2025

Quick Overview

Explain difference-in-differences in simple terms and provide a concrete example.

Square/Block
Analytics & Experimentation
Data Scientist
Square/Block
November 2, 2025
Data Scientist
Onsite
Analytics & Experimentation
Easy

12

5

365 solved


Explain difference-in-differences in simple terms and provide a concrete example.

Square/Block 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
  • 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
Sample size and power calculation
Network effects and interference
Simpson's paradox and ecological fallacy
Metric definition and success criteria
Funnel analysis and cohort analysis
Guardrail metrics
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 seasonality in your experiment?
  • 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?
  • How would you handle an experiment where the control and treatment groups are different sizes?
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