Interview
Questions
Data Science: Marketing Measurement Decisions
Practice evaluating marketing evidence, checking data quality, and explaining budget recommendations. Focus on attribution, marketing mix modeling, experimentation, and model reliability.
Practice these questions directly. An editable copy is yours to change; the original stays unchanged.
A retail client wants to move budget after one week of strong attributed sales from a channel. How would you compare that evidence with marketing mix modeling and an incrementality test before recommending a change?
Give me an example of how you have used A/B testing or experimentation to improve marketing performance. What was your hypothesis, methodology, and what did you learn?
Walk me through how you approach model selection for a new problem. What factors do you consider?
A marketing model reports a sharp improvement, but some channel spending data is missing. What would you investigate, and what would you tell the client about using the result for today's budget decision?
Tell me about a time when a model you deployed did not perform as expected in production. How did you diagnose and address the issue?
Tell me about a time when stakeholders disagreed with your analysis or recommendations. How did you handle it?