Calculate conditional probability for click-through rates
Last updated: October 15, 2025
Quick Overview
Given the following scenario about revenue per session, calculate the the p-value.
Salesforce
October 15, 202578
12
4,085 solved
Given the following scenario about revenue per session, calculate the the p-value.
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 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
- 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?
- How would you handle seasonality in your experiment?
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Browse Analytics QuestionsSample Answer
Problem Setup
The analytical question we need to answer is: What is the conditional probability of a user clicking through to the next page given their revenue per session? To tackle this, we need to gather data th...
Methodology
For this problem, we will use logistic regression to model the probability of a user clicking through based on their revenue per session. The logistic regression will help us estimate the log-odds of ...
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