Interpret a statistically significant lift of 2% from an experiment
Last updated: August 18, 2025
Quick Overview
An experiment shows a 3% lift with p=0.08. What conclusions can you draw? What are the caveats?
Spotify
August 18, 202530
6
2,844 solved
An experiment shows a 3% lift with p=0.08. What conclusions can you draw? What are the caveats?
Spotify asks this during the Take-home Project 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
How to Approach This
- Define success metrics carefully. A good metric is measurable, actionable, and aligned with business goals.
- Run experiments long enough to account for novelty effects and weekly seasonality.
- Use funnel analysis to identify where users drop off for maximum optimization impact.
- Segment results by key dimensions (platform, country, user cohort) to catch hidden patterns.
- 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 an experiment where the control and treatment groups are different sizes?
- What if you discover a bug in the logging during the experiment?
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Browse Analytics QuestionsSample Answer
Problem Setup
The primary analytical question revolves around interpreting a 3% lift in user engagement due to a specific feature change, with a p-value of 0.08. To analyze this, we would need data on user engageme...
Methodology
Given the p-value of 0.08, we are close to the conventional threshold of 0.05 for statistical significance. However, since it is above this threshold, we interpret the results with caution. We can app...
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