Interpret mixed results across segments from an experiment
Last updated: May 1, 2026
Quick Overview
An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
Salesforce
May 1, 202667
6
3,366 solved
An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
Salesforce asks this during the Phone 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
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
- How would you handle seasonality in your experiment?
- How would you handle interference between treatment and control?
- What if the experiment shows a positive short-term effect but you suspect a negative long-term impact?
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Browse Analytics QuestionsSample Answer
Problem Setup
The analytical question at hand is: "What can we conclude from the conflicting results observed across different segments in our recent experiment?" To address this, I would need detailed data on the ...
Methodology
For this analysis, I would employ a segmented analysis approach, using ANOVA (Analysis of Variance) to test for differences in outcomes across segments. This will allow us to determine whether the mix...
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