# A/B test store listing Human Guide

## What This Is For
When the user wants to A/B test App Store product page elements to improve conversion rate. It gives the agent a clearer input/output frame for A/B test store listing: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the A/B test store listing agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for A/B test store listing.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the A/B test store listing guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- Check for `app-marketing-context.md` — read it for context
- Ask for **current conversion rate** (if known from App Store Connect)
- Ask for **daily impressions** (determines test duration)
- Ask: **What do you want to test?** (icon, screenshots, description, etc.)
- Only tests against organic App Store traffic
- Minimum 90% confidence required to declare winner
- Can only run one test at a time
- Traffic split is automatic (not configurable)
- Different audiences (from different ad campaigns)
- Different value propositions
- Localized creative for specific markets
- It's the first thing users see in search results

## Decision Points And Nuance
The original skill emphasizes: Initial Assessment, What You Can Test, Apple Product Page Optimization (PPO), Custom Product Pages (CPP), Test Prioritization, Impact × Effort Matrix, What to Test First, Test Design Framework, Step 1: Hypothesis, Step 2: Variants.

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- Minimum 90% confidence required to declare winner
- 80% of users never scroll past the first 3 screenshots
- Make the change significant enough to detect (don't test subtle color shifts)
- Don't test more than 3 variants (dilutes traffic)
- Calculate required test duration:
- Required sample per variant: ~[N] impressions
- Monitor but don't stop early
- Required Impressions: [N] per variant

## Copy-And-Paste Prompt
```text
Use the A/B test store listing human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the eronred/aso-skills skill entry for `ab-test-store-listing`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# A/B Test Store Listing

You are an expert in App Store product page optimization and A/B testing. Your goal is to help the user design, run, and interpret tests that improve their App Store conversion rate.

## Initial Assessment

1. Check for `app-marketing-context.md` — read it for context
2. Ask for the **App ID**
3. Ask for **current conversion rate** (if known from App Store Connect)
4. Ask for **daily impressions** (determines test duration)
5. Ask: **What do you want to test?** (icon, screenshots, description, etc.)

## What You Can Test

### Apple Product Page Optimization (PPO)

Apple's native A/B testing tool in App Store Connect.

| Element | Testable? | Notes |
|---------|-----------|-------|
| App icon | Yes | Up to 3 variants |
| Screenshots | Yes | Up to 3 variants |
| App preview video | Yes | Up to 3 variants |
| Description | No | Not testable via PPO |
| Title | No | Not testable via PPO |
| Subtitle | No | Not testable via PPO |

**Limitations:**
- Only tests against organic App Store traffic
- Minimum 90% confidence required to declare winner
- Tests run for 7-90 days
- Can only run one test at a time
- Traffic split is automatic (not configurable)

### Custom Product Pages (CPP)

35 custom product pages per app, each with unique:
- Screenshots
- App preview videos
- Promotional text

**Use for:**
- Different audiences (from different ad campaigns)
- Different value propositions
- Seasonal messaging
- Localized creative for specific markets

**Not a true A/B test** — CPPs are targeted pages linked from specific URLs/campaigns, not random traffic splits.

## Test Prioritization

### Impact × Effort Matrix

| Element | Impact on CVR | Effort | Priority |
|---------|--------------|--------|----------|
| First screenshot | Very High (15-30% lift possible) | Medium | 1 |
| App icon | High (10-20% lift possible) | Medium | 2 |
| Screenshot order | Medium (5-15% lift possible) | Low | 3 |
| Screenshot style | Medium (5-15% lift possible) | High | 4 |
| Preview video | Medium (5-10% lift possible) | High | 5 |

### What to Test First

**Always start with the first screenshot.** It has the highest impact because:
- It's the first thing users see in search results
- 80% of users never scroll past the first 3 screenshots
- Small improvements here affect every visitor

## Test Design Framework

### Step 1: Hypothesis

Write a clear hypothesis before each test:

```
If we [change], then [metric] will [improve/increase] because [reason].
```

**Examples:**
- "If we add social proof ('5M+ users') to the first screenshot, conversion rate will increase because it builds trust"