creative-testing-frameworklisted

# /dm:creative-testing-framework ## Purpose Design a systematic creative testing framework that maximizes learning velocity while maintaining statistical rigor across advertising platforms. Produces a complete testing playbook with variable prioritization, sample size requirements, iteration cadence, and documentation standards for continuous creative optimization. ## Input Required The user must provide (or will be prompted for): - **Ad platform(s)**: Where ads are running — Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, programmatic DSPs, Pinterest, X/Twitter, or multi-platform - **Creative types available**: What formats can be produced — static image, video (short-form/long-form), carousel, text-only, responsive display, HTML5, playable, or collection ads - **Monthly ad budget allocated to testing**: How much budget is available specifically for creative experimentation vs. proven performers - **Current top-performing creative**: Description or reference to the best-performing ads currently running, including their key metrics - **Learning goals**: Which creative elements need optimization — headlines, imagery, CTA copy, video hooks, color palette, offer framing, social proof, format type, or ad copy length - **Audience segments for testing**: The audience groups available for testing — prospecting, retargeting, lookalike, interest-based, demographic, or custom segments - **Campaign objectives**: What the ads are optimized for — awareness (impressions/reach), consid