# Creative Testing Framework > A complete framework for designing, running, and interpreting paid social creative tests — from hypothesis formation through statistical significance. ## Why You Need a Framework Creative testing without a framework produces false winners. Teams change multiple variables, read results after 48 hours, and declare victory on noise. A rigorous framework isolates variables and builds repeatable knowledge. ## Step 1: Form a Testable Hypothesis Template: **"If we change [single variable] from [A] to [B], then [metric] will improve by [expected magnitude] because [rationale]."** Write the hypothesis before opening Ads Manager. ## Step 2: Design a Controlled Test - Only one variable differs between variants - Equal budget allocation per variant (ABO, not CBO during tests) - Same audience, landing page, and conversion event - Pre-defined end date and sample size ## Step 3: Calculate Sample Size Plan for at least 50–100 conversions per variant for conversion-optimized tests, or 5,000–10,000 impressions per variant for upper-funnel metrics. ## Step 4: Interpret Results 1. Check statistical significance (95% confidence standard) 2. Assess practical significance — is the lift large enough to change workflow? 3. Segment by placement and device before concluding 4. Document learnings in your test tracker **Warning:** Checking results daily and stopping early inflates false-positive rates. Pre-commit to sample size or end date. ## Related Tools - [Creative Testing Calculator](/resources/tools/calculators/creative-testing-calculator) - [A/B Test Significance Calculator](/resources/tools/calculators/ab-test-statistical-significance-calculator) - [A/B Test Tracker Template](/resources/templates/ab-test-tracker-template)