ads-testing

An A/B testing plan for digital advertising is generated as a structured 90-day calendar, prioritizing tests by impact and effort while including durations, sample sizes, hypotheses, and winner criteria for Meta, Google, and LinkedIn campaigns.

A testing roadmap for ad campaign optimization should include a prioritized test matrix, week-by-week testing calendar, hypothesis templates, winner criteria, platform-specific setup instructions, and an iteration plan to guide ongoing optimization.

Sample size and duration for Meta and Google ad tests are calculated by enforcing test isolation and guardrails within the generated 90-day calendar, recommending specific test durations and milestones to ensure statistically sound campaign optimization.

Yes, this automated A/B testing roadmap supports LinkedIn campaigns by providing platform-aware guidance, specific setup instructions, and best practices tailored for testing advertising hypotheses across Meta, Google, and LinkedIn.

The best way to prioritize ad testing hypotheses for maximum ROI is using a ranked test matrix that evaluates each test by its expected impact and required effort, standardizing decision making with ready-to-use templates and winner criteria.

You need to specify a campaign context to generate the advertising testing plan, which outputs a complete ADS-TESTING-PLAN.md document and supporting trackers for logging results and guiding ongoing optimization iterations.