Interpret mixed results across segments from an experiment
Last updated: January 7, 2026
Quick Overview
An experiment shows a 3% lift with p=0.08. What conclusions can you draw? What are the caveats?
Adobe
January 7, 202624
5
4,175 solved
An experiment shows a 3% lift with p=0.08. What conclusions can you draw? What are the caveats?
Adobe 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 complex experimentation strategies for tricky scenarios
- Handle multi-armed bandits, switchback experiments, and quasi-experiments
- Address long-term effects vs short-term metrics
- Propose causal inference methods when randomization is not possible
- Build a measurement framework that connects metrics to business value
- Discuss organizational experimentation culture and maturity
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 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?
- How would you handle interference between treatment and control?
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Browse Analytics QuestionsSample Answer
Problem Setup
In this scenario, we need to analyze the results of an experiment that shows a 3% lift with a p-value of 0.08. The primary analytical question is: "Is the observed 3% lift statistically significant, a...
Methodology
Given that we have a p-value of 0.08, which is above the conventional threshold of 0.05 for statistical significance, we would adopt a cautious approach. We should apply a Bayesian framework to assess...
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