website skill

---
name: pricing-tests
description: This skill should be used when the user asks to "test pricing", "A/B test pricing page", "pricing experiments", "optimize pricing", or mentions pricing psychology, price testing, or conversion optimization. Creates strategic pricing page experiments that maximize revenue through data-driven optimization.
---

# Pricing Page Experiments

Design and execute strategic A/B tests for pricing pages that optimize for maximum revenue through data-driven pricing psychology, presentation, and positioning experiments.

## Core Objectives

- Maximize revenue through optimal pricing presentation
- Test pricing psychology principles (anchoring, decoy effect, etc.)
- Optimize conversion rates at different price points
- Reduce price-related objections through positioning
- Drive data-informed pricing decisions

## Mandatory Elements

### 1. Test Hypothesis
- **Question:** What specific pricing element are we testing?
- **Hypothesis:** Expected outcome (e.g., "Showing annual savings increases conversions")
- **Success Metric:** Primary KPI (revenue per visitor, conversion rate, etc.)
- **Sample Size:** Minimum visitors needed for statistical significance

### 2. Variant Design
- **Control:** Current pricing page (baseline)
- **Variant(s):** Modified pricing presentation
- **Single Variable:** Only one element changes per test
- **Visual Consistency:** Maintain brand and design standards

### 3. Pricing Psychology Elements
- **Anchoring:** High-priced option to make others look reasonable
- **Decoy Effect:** Intentionally less attractive middle option
- **Value Stacking:** Show total value vs. price comparison
- **Scarcity:** Limited-time pricing or availability
- **Social Proof:** "Most Popular" or "Best Value" badges

## Structure & Frameworks

### The "Scientific Testing" Framework
1. **Hypothesis-Driven:** Start with a specific question
2. **Single Variable:** Test one element at a time
3. **Statistical Significance:** Wait for adequate sample size
4. **Revenue-Focused:** Optimize for total revenue, not just conversions

### Pricing Test Variants
- **Price Presentation:** $99 vs. $99/month vs. $1,188/year
- **Plan Ordering:** Low-to-high vs. high-to-low vs. "Most Popular" first
- **Value Communication:** Feature list vs. benefit-focused vs. ROI calculator
- **Anchoring:** 3 plans vs. 4 plans (with decoy) vs. 2 plans
- **Urgency:** No urgency vs. "Limited Time" vs. "Only X Spots Left"

## Voice & Tone Guidelines

- **Data-Driven:** Focus on metrics and outcomes
- **Clear & Transparent:** Make pricing easy to understand
- **Value-Focused:** Emphasize ROI and transformation over cost
- **Formatting:** Use comparison tables, value stacks, and clear CTAs

## Concrete Examples

### Pricing Anchoring Example
```text
"Plan Comparison:

• Starter: $49/month (Basic features)
• Professional: $99/month ⭐ Most Popular (Everything in Starter + Advanced)
• Enterprise: $299/month (Everything in Professional + Custom features)

*Most customers choose Professional for the best value*"
```

### Value Stack vs. Price
```text
"What You Get (Total Value: $2,497):

✓ Core Program ($997 value)
✓ Bonus Templates ($297 value)
✓ Community Access ($197 value)
✓ 1-on-1 Support ($497 value)
✓ Lifetime Updates ($509 value)

Your Investment Today: $497
(Save $2,000 - 80% off)"
```

## Quality Checklist

For every pricing test, ask:
- [ ] Is the test hypothesis clear and measurable?
- [ ] Is only one variable being tested at a time?
- [ ] Are success metrics defined (revenue, not just conversions)?
- [ ] Is the sample size adequate for statistical significance?
- [ ] Would this test provide actionable pricing insights?