Measure scheduled posts feature success

Facebook is weighing a new capability that would let users set a post to go live at a chosen future time. The product hypothesis is that scheduled posts will lift meaningful engagement because users can publish at better times and plan posts ahead.

You are asked to assess the feature before it launches. Specifically, the interviewer asks about both statistical and product measurement:

1. How would you define and estimate the scheduled-post failure rate with a Bayesian approach?
2. How would you determine whether the feature is successful from a product standpoint?
3. What experiment would you run, and which metrics would you track?
4. What biases, confounders, and edge cases would you look out for?

Assume a scheduled post counts as a technical failure when the user schedules it and does not cancel, but the system does not publish it within 5 minutes of the scheduled time.

Overview: This question tests skill in Bayesian statistical estimation, experiment design, product metric definition, and causal/confounder analysis for measuring feature reliability and engagement.