Communicate trade-offs and influence launch
Overview
This question evaluates product judgment, experimentation interpretation, and cross-functional leadership skills for a data scientist, focusing on communicating trade-offs between per-account metric lifts and cross-account cannibalization; Category: Behavioral & Leadership, Domain: data science and product experimentation.
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Oct 13, 2025, 9:49 PM
Data Scientist
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Behavioral & Leadership
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Product Experiment Trade‑off: Notifications for Multi‑Account Users
Context
You ran an experiment on notification delivery to users who often maintain multiple accounts ("multi‑account users"). The test shows:
- Significant lifts in notification success metrics on the notified accounts (views, CTR, notification‑driven actions).
- A meaningful decrease in usage of other accounts owned by the same person that did not receive notifications (suggesting cross‑account cannibalization).
Task
Address the following:
- How would you frame this trade‑off for a PM and cross‑functional partners?
- How would you estimate longer‑term user value and potential churn risk (e.g., CLV impact, account‑level activity diversity) to decide whether to launch?
- What mitigations would you propose (e.g., target only non‑preferred accounts, frequency capping, per‑person eligibility rules) and how would you design a phased rollout with guardrail thresholds?
- What monitoring plan would you outline post‑launch to catch regressions and unintended behaviors?
Solution
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