ab-test-store-listing
When the user wants to A/B test App Store product page elements to improve conversion rate. Also use when the user mentions "A/B test", "product page optimization", "test my screenshots", "test my icon", "conversion rate optimization", "CPP", or "custom product pages". For screenshot design, see scr
By eronred · 2,776 installs
npx skills add eronred/aso-skills --skill ab-test-store-listing
Source repository · Upstream listing
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:
Examples:
"If we add social proof ('5M+ users') to the first screenshot, conversion rate will increase because it builds trust"
"If we change the icon from blue to orange, tap through rate will increase because it stands out more in search results"
"If we show the app's AI feature first instead of the basic editor, conversion will increase because AI is the key differentiator"
Step 2: Variants
Design 2 3 variants (including control):
Variant Description Hypothesis
Control (A) Current version Baseline
Variant B [specific change] [why it might win]
Variant C [different change] [why it might win]
Rules for good variants:
Change ONE thing per test (isolate the variable)
Make the change significant enough to detect (don't test subtle color shifts)
Each variant should have a clear hypothesis
Don't test more than 3 variants (dilutes traffic)
Step 3: Sample Size
Calculate required test duration:
Rules of thumb:
< 1000 daily impressions: Tests take 30 90 days (consider if worth it)
1000 5000 daily impressions: Tests take 14 30 days
5000+ daily impressions: Tests take 7 14 days
Need at least 1000 impressions per variant for meaningful results
Step 4: Run the Test
In App Store Connect:
1. Go to Product Page Optimization
2. Create a new test
3. Upload variant assets
4. Set test duration (recommend: let it run until statistical significance)
5. Monitor but don't stop early
Step 5: Interpret Results
Statistical significance:
Apple requires 90% confidence minimum
Aim for 95% confidence before making decisions
Look at the confidence interval, not just the point estimate
What to look for:
Conversion rate lift (primary metric)
Impression to tap rate (for icon tests)
Download rate (for screenshot/video tests)
Segment differences (new vs returning, country, source)
Common Test Ideas
Icon Tests
Test Control Variant Expected Impact
Color Current color Contrasting color 5 20% TTR change
Style Detailed Simplified 5 15% TTR change
Element Current symbol Different symbol 5 20% TTR change
Background Solid Gradient 3 10% TTR change
Screenshot Tests
Test Control Variant Expected Impact
First screenshot Feature focused Benefit focused 10 30% CVR change
Social proof No social proof "5M+ users" badge 5 15% CVR change
Text size Small text Large, bold text 5 10% CVR change
Style Light mode Dark mode 5 15% CVR change
Layout Device frame Full bleed 5 10% CVR change
Order Current order Reordered by benefit 5 15% CVR change
Video Tests
Test Control Variant Expected Impact
Has video No video 15s feature demo 5 15% CVR change
Hook Feature demo Problem/solution 5 10% CVR change
Length 30s 15s 3 8% CVR change
Output Format
Test Plan
Test Results Interpretation
When the user shares results:
1. Is it statistically significant? (confidence level)
2. What's the actual lift? (with confidence interval)
3. Are there segment differences?
4. What's the next test to run?
5. Estimated annual impact (downloads × lift)
Testing Roadmap
Provide a 3 month testing calendar:
Month 1: [highest impact test]
Month 2: [second priority test]
Month 3: [third priority test]
Related Skills
screenshot optimization — Design screenshot variants
metadata optimization — Optimize non testable elements
app analytics — Track conversion metrics
aso audit — Identify what to test first