Interpret mixed results across segments from an experiment
Last updated: November 7, 2025
Quick Overview
An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
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An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
Analytics questions at Reddit evaluate your ability to define metrics, design experiments, and derive actionable insights from data. This Technical Screen question tests your end-to-end analytical thinking.
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 interference between treatment and control?
- How would you handle an experiment where the control and treatment groups are different sizes?
- 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?
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Browse Analytics QuestionsSample Answer
Problem Setup
In this experiment, we aim to analyze the impact of a new feature on user engagement across different segments of Reddit users (e.g., new users vs. returning users, users from different subreddits). T...
Methodology
Given the mixed results across segments, we will use a two-way ANOVA (Analysis of Variance) approach. This will allow us to assess the impact of the new feature not only overall but also across differ...
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