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Use when designing copy experiments to optimize hooks, offers, and CTAs.
--- name: offer-testing description: Use when designing copy experiments to optimize hooks, offers, and CTAs. --- # Offer Testing Playbooks Skill ## When to Use - Planning subject line/CTA/offer tests across email, ads, or landing pages. - Validating new positioning or pricing language. - Running copy refresh cycles for campaigns. ## Framework 1. **Hypothesis** – statement of expected lift + rationale. 2. **Variable Selection** – hook, CTA, body copy, offer framing, proof element. 3. **Segmentation** – define audience splits and holdouts. 4. **Metrics** – primary KPI + guardrails (opens, CTR, CVR, CPL, unsub, spam). 5. **Analysis** – statistical significance (chi-square, z-test) or Bayesian approach. ## Templates - Experiment brief (variable, control, variant, KPI, sample size, duration). - Results report (metric table, significance, insight, next steps). - Prioritization matrix (ICE/RICE scoring). ## Tips - Limit to one variable per test to isolate learnings. - Ensure minimum sample sizes per channel before declaring winners. - Log tests and learnings in a shared repository. ------ name: offer-testing description: Use when designing copy experiments to optimize hooks, offers, and CTAs. --- # Offer Testing Playbooks Skill ## When to Use - Planning subject line/CTA/offer tests across email, ads, or landing pages. - Validating new positioning or pricing language. - Running copy refresh cycles for campaigns. ## Framework 1. **Hypothesis** – statement of expected lift + rationale. 2. **Variable Selection** – hook, CTA, body copy, offer framing, proof element. 3. **Segmentation** – define audience splits and holdouts. 4. **Metrics** – primary KPI + guardrails (opens, CTR, CVR, CPL, unsub, spam). 5. **Analysis** – statistical significance (chi-square, z-test) or Bayesian approach. ## Templates - Experiment brief (variable, control, variant, KPI, sample size, duration). - Results report (metric table, significance, insight, next steps). - Prioritization matrix (ICE/RICE scoring). ## Tips - Limit to one variable per test to isolate learnings. - Ensure minimum sample sizes per channel before declaring winners. - Log tests and learnings in a shared repository. ---
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