Define Churn and Design Onboarding Experiment

Imagine you are the product data scientist for a consumer application. Your team is currently evaluating a redesigned onboarding flow, and some experimental variants of this flow may incorporate an email outreach to encourage new users to complete their onboarding process.

You are required to address the following:

Part 1: Define Churn Rate

Define the churn rate specifically for this product. Your definition must include:

• The denominator (the user base being considered).
• The specific event that constitutes "churn".
• The time window over which churn is measured.
• The observation window for user activity.
• Considerations for timezone.
• How to handle user reactivation after a churn event.

Part 2: Historical Data for Churn Definition

Explain your methodology for using historical data to empirically determine the appropriate churn event and time window, rather than making arbitrary selections.

Part 3: A/B Test Design

Design an A/B test for the proposed onboarding flow changes. Your design should specify:

• The randomization unit.
• The setup for treatment and control groups, particularly addressing how an email component within a treatment variant would be handled.
• The primary success metric.
• Relevant secondary metrics.
• Critical guardrail metrics.
• How you would interpret and reconcile short-term versus long-term effects observed from the experiment.