Boost Google Workspace Chat Usage with Strategic A/B Testing

Q: Boost Google Workspace Chat Usage with Strategic A/B Testing

This question evaluates a data scientist's competency in product analytics, growth measurement, hypothesis-driven experimentation, segmentation, and A/B testing for an enterprise messaging or collaboration product.

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Question

Scenario

Google Workspace Chat adoption is low, and leadership asks for a data-driven plan to grow monthly active users (MAU).

Task

Design a plan to drive user growth. Include:

North-star metric and supporting metrics to track.
Acquisition/activation funnel and key segmentation.
Hypotheses (with rationale) to increase growth.
An A/B-testing roadmap: design, cadence, powering, and guardrails.
Success criteria and how you will validate results.

Hints: North-star metric, acquisition funnel, segmentation, experiment cadence, guardrail metrics.

Boost Google Workspace Chat Usage with Strategic A/B Testing

Scenario

Task

Solution

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