Present Piracy Trends to a PM

You have already run the analyses described above and have two preliminary findings:

• the monthly pirated-theme usage rate appears to climb from 0% to 100% over the observed period
• cumulative estimated revenue loss from pirated themes keeps growing over time A product manager asks: Is this actually a red flag, how should we interpret it, and what should we do next? Explain how you would walk the PM through these results. Your response should address:

1. Which piracy metric or metrics you would lead with, and why: new pirated installs, active pirated shops, revenue loss, or a different metric.
2. Why a move from 0% to 100% may or may not be meaningful, covering small denominators, shifts in the merchant mix, detection bias, and seasonality.
3. Whether you would show monthly loss, cumulative loss, or both — and what each one does or does not communicate to the PM.
4. Which caveats you would flag around valid_to being null, right-censoring, false positives in the piracy classifier, and segment-level effects that could create Simpson's paradox.
5. What further analyses, slices, or follow-up actions you would suggest before the PM commits engineering or policy resources. Overview: This question tests a candidate's ability to interpret time-series analytics and revenue-impact estimates, reason through measurement biases and censoring, and communicate ambiguous statistical findings to product stakeholders. This question comes from a Shopify Data Scientist interview experience.