Present Piracy Trends to a PM

Q: Present Piracy Trends to a PM

This question evaluates a candidate's ability to interpret time-series analytics and revenue-impact estimates, reason about measurement biases and censoring, and communicate ambiguous statistical findings to product stakeholders.

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Question

You ran the analyses above and got two preliminary findings:

the monthly pirated-theme usage rate appears to rise from 0% to 100% over the observed period
cumulative estimated revenue loss from pirated themes keeps increasing 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 present these results to the PM. Your answer should cover:

Which piracy metric(s) you would show first and why: new pirated installs, active pirated shops, revenue loss, or another metric.
Why a change from 0% to 100% may or may not be meaningful, including the role of small denominators, changing merchant mix, detection bias, and seasonality.
Whether you would show monthly loss , cumulative loss , or both, and what each one does or does not tell the PM.
What caveats you would call out around valid_to being null, right-censoring, false positives in piracy detection, and segment-level effects that could create Simpson's paradox.
What additional analyses, slices, or follow-up actions you would recommend before the PM commits engineering or policy resources.

Present Piracy Trends to a PM

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