Design metrics and experiment for donation feature

Q: Design metrics and experiment for donation feature

This question evaluates competencies in experimental design, metric specification and instrumentation, causal inference and statistical analysis, and product analytics for implementing an optional donation feature on a food-ordering platform.

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Question

Product/Experimentation Case

Uber Eats is considering a new feature: when a user places an order, they can optionally donate (tip-like or charitable donation) to the merchant.

You are asked to propose:

1) Goal and hypotheses

What is the main product goal of this feature?
State primary and secondary hypotheses you would test.

2) Metrics selection

Define:

Primary (success) metric(s)
Diagnostic metrics (to understand mechanisms)
Guardrail metrics (to ensure no harm)

Be explicit about metric definitions (unit of analysis, numerator/denominator, time window).

3) Experiment design

Describe an experiment plan, including:

Experiment unit (user/order/restaurant)
Treatment(s) and control
Eligibility/targeting
How you handle repeated orders, interference/spillover, and novelty effects
How you would evaluate heterogeneous effects (e.g., by restaurant type, user frequency)

4) Risks and confounders

List major risks/biases (e.g., selection, cannibalization) and how you would mitigate them.

Deliverable

Produce a concise plan that an analytics/DS team could execute.