Track Metrics to Measure Push Notification Quality

Q: Track Metrics to Measure Push Notification Quality

This question evaluates a data scientist's competency in defining and measuring push-notification quality by selecting relevant engagement, retention, and opt-out/uninstall metrics, setting thresholds, and designing randomized experiments to validate a notification-selection algorithm.

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Question

Scenario

A consumer mobile app sends push notifications to drive user engagement. You need to evaluate the quality of these notifications, define what constitutes “high-quality,” and design a rigorous experiment to validate a new notification-selection algorithm at launch.

Assumptions (minimal):

You can randomize at the user level and collect event-level telemetry (send, delivered, opened/tapped, session starts, conversions, opt-outs, uninstalls).
Platforms include iOS and Android; weekly seasonality exists.

Questions

Metrics: Which metrics would you track to measure push-notification quality? Include engagement, retention, and opt-out signals.
Thresholds: How would you define and set thresholds for “high-quality” notifications?
Experiment: Design an experiment to evaluate a new push-notification algorithm at launch. Specify units of randomization, key metrics and guardrails, sample size/power, duration, and rollout safeguards.

Hints: Consider engagement, retention, opt-outs, control vs. treatment setup, and sample size.

Track Metrics to Measure Push Notification Quality

Scenario

Questions

Solution

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