Evaluate New Model's Impact on Rider and Driver Experience

Q: Evaluate New Model's Impact on Rider and Driver Experience

This question evaluates experimental design, metric selection, behavioral analytics, and causal inference skills for measuring a new ETA model’s impact on rider and driver experience within the Analytics & Experimentation domain.

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Question

Airport Pickups ETA Model: Evaluation and Experiment Design

Context

A new model predicts rider walk-time from the order location (e.g., terminal/door) to the pickup zone. The current baseline ETA shown to riders reflects only the driver’s arrival. The product will display a combined pickup ETA (driver ETA ± walk time), which can change rider behavior: riders may speed up or slow down based on the displayed time.

Assumptions added for clarity:

You can log rider device location pings to infer arrival at pickup zones and approximate walking start/arrival times.
You can log driver arrival/departure times at pickup zones.
Both baseline and new model predictions can be logged, regardless of which is shown to the rider.

Tasks

Metrics: What would you use to evaluate the new airport ETA model’s impact on rider and driver experience?
Experiment: Design an experiment to test the new model against the baseline.
Feedback loop: Riders may adjust their pace based on displayed ETA. How would you quantify this behavioral response and separate it from pure model accuracy?

Evaluate New Model's Impact on Rider and Driver Experience

Airport Pickups ETA Model: Evaluation and Experiment Design

Context

Tasks

Solution

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