ORIGINAL COMPANY-CONTEXT PRACTICE
Separate promotion uplift from seasonal demand
Original practice scenario: A hypothetical food retailer promotes products during holidays. How would you estimate whether a promotion increased demand rather than merely coinciding with it?
Written for independent practice using company context; this is not a verified question from a company interview.
A REASONED APPROACH
Model answer.
Holiday timing, placement and availability can confound apparent uplift. Define the decision and comparison population before estimating an effect, and distinguish causal claims from predictive usefulness.
Work through it
- Prefer randomized store or customer assignment where feasible, choosing units that limit spillover and recording assignment before outcomes.
- Track baseline demand, stockouts, prices and concurrent promotions; analyze intention-to-treat effects with uncertainty at the assignment-unit level.
- If only observational data exist, state assumptions, assess comparable controls and pre-trends, and test sensitivity to unmeasured confounding.
Tradeoffs to discuss
- Cluster randomization reduces spillover but needs enough independent clusters; observational estimates cover more history with weaker identification.
Common pitfalls
- Do not compare holiday promotion weeks only with ordinary weeks.
- Check substitution across products rather than declaring gross item growth to be total incremental demand.