ads-test
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.
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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.
- Repository
- AgriciDaniel/claude-ads
- Commit
ac21644
- Last updated
- First committed
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