Provides A/B testing strategies for funnel pages: priorities (headlines, CTAs), rules, 95% significance thresholds, hypothesis templates, patterns for opt-in/sales/pricing pages.
npx claudepluginhub ominou5/funnel-architect-pluginThis skill uses the workspace's default tool permissions.
Test everything. Opinions are nice — data is better.
Guides planning, design, and implementation of A/B tests, split tests, and experiments using hypothesis frameworks, test types, and sample size calculations.
Guides A/B test setup for ads, landing pages, emails, products: selects variables, calculates sample sizes, sets up tracking, analyzes statistical significance. Triggers on 'A/B test', 'split test' keywords.
Guides A/B test planning and design with hypothesis frameworks, sample size calculations, test types, and statistical principles for valid, actionable results. Useful for experiments or split tests.
Share bugs, ideas, or general feedback.
Test everything. Opinions are nice — data is better.
| Priority | Element | Expected Impact |
|---|---|---|
| 🔴 P0 | Headline | 10–50% lift |
| 🔴 P0 | CTA text + color | 5–30% lift |
| 🟡 P1 | Hero image/video | 5–20% lift |
| 🟡 P1 | Form fields (fewer vs. more) | 10–40% lift |
| 🟡 P1 | Social proof placement | 5–15% lift |
| 🟢 P2 | Page layout (long vs. short) | 5–20% lift |
| 🟢 P2 | Pricing display | 5–25% lift |
| 🟢 P2 | Urgency messaging | 3–15% lift |
| 🔵 P3 | Color scheme | 2–10% lift |
| 🔵 P3 | Font choices | 1–5% lift |
HYPOTHESIS: If we change [element] from [current] to [proposed],
then [metric] will [increase/decrease] by [estimated %]
because [reasoning based on conversion principles].
TEST SETUP:
- Control (A): [Current version description]
- Variant (B): [New version description]
- Primary metric: [Conversion rate / Click rate / etc.]
- Secondary metric: [Revenue / Engagement / etc.]
- Required sample: [Number] visitors per variant
- Estimated duration: [X] days at [Y] daily visitors
After each test, log:
TEST: [Test Name]
DATE: [Start] → [End]
TRAFFIC: [Total visitors] ([Per variant])
RESULTS:
Control: [X]% conversion ([N] conversions)
Variant: [Y]% conversion ([N] conversions)
WINNER: [Control/Variant]
LIFT: [+/- X]%
CONFIDENCE: [X]%
NEXT: [What to test next based on learnings]