ads-test
热门Design and evaluate paid-ad experiments with hypotheses, randomization units, sample-size and duration assumptions, guardrails, platform experiment tools, analysis, and decision rules. Use for A/B test, split test, experiment design, hypothesis, statistical significance, sample size, test duration, or experiment readout.
Design and evaluate paid-ad experiments with hypotheses, randomization units, sample-size and duration assumptions, guardrails, platform experiment tools, analysis, and decision rules. Use for A/B test, split test, experiment design, hypothesis, statistical significance, sample size, test duration, or experiment readout.
Paid Media Experiment
- State the decision, causal hypothesis, treatment, control, randomization unit,
population, primary metric, guardrails, minimum effect, and stopping rule. - Check platform constraints, overlapping experiments, conversion lag, seasonality,
interference, and measurement quality. - Calculate sample and duration from declared assumptions; disclose approximations.
- Change one decision surface unless the design explicitly estimates interactions.
- Pre-register exclusions, quality checks, analysis, and decision thresholds.
- For readout, verify assignment integrity and data completeness before estimating
effect and uncertainty. - Return setup or readout in versioned JSON with a plain-language decision.
Do not repeatedly peek and stop on a favorable result, call underpowered noise a
winner, or generalize beyond the tested population.
