Experimentation and Validation Questions

Deciding what to test and how to learn it cheaply before committing product investment: identifying the riskiest assumption, writing a falsifiable hypothesis, choosing between a prototype, fake door, concierge test, pilot, beta or live experiment, sequencing validation steps and budgeting effort across assumptions, setting go/no-go criteria and rollback triggers in advance, and combining qualitative and quantitative evidence, including when they disagree. Covers pilot design (participants, comparison group, guardrails, threats to validity), offline checks of a model idea before small online trials, limited trials of vendors or architectures, and validating demand under thin data or privacy limits. Assesses hypothesis-driven product development and evidence-based decisions, including validation of technical and operational bets. Excludes the statistical design of a single online test, interpreting finished experiment results, experimentation platform engineering, user research methods, ordering tests across a program, and non-randomized causal inference.