Evaluate Impact of $1 Fee on Fast-Food Profitability
Overview
This question evaluates proficiency in experimental design and causal inference for marketplace pricing changes, covering competencies such as randomization and interference management, metric selection and guardrails, sample size and power calculations, and analysis frameworks like ITT/TOT and variance-reduction techniques.
DoorDash
Aug 4, 2025, 10:55 AM
Data Scientist
Onsite
Analytics & Experimentation
0
0
Experiment Design: $1 Delivery-Fee Surcharge on Unprofitable Restaurants
Scenario
About 10% of fast-food restaurants on the platform are unprofitable. Product wants to add a $1 delivery-fee surcharge to orders from those restaurants to cover the deficit.
Task
Design an experiment to evaluate the impact of the $1 fee on:
- Restaurant-level profitability
- Order volume (conversion and frequency)
- Customer satisfaction
Include:
- Experimental unit and randomization plan (address marketplace spillovers/interference).
- Primary/secondary metrics and guardrails, with clear hypotheses.
- Sample size and duration guidance (state assumptions if needed).
- Analysis plan (e.g., ITT vs. TOT, variance reduction, decomposition of effects).
- Concrete techniques to increase statistical power (e.g., stratified randomization, CUPED, covariate blocking, geo-testing, longer horizon), and when to use each.
Assume the $1 fee is only applied to currently unprofitable restaurants. If needed, make minimal additional assumptions explicit.
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