aso-playbook Β· diff

git:20260706.f77d636 to git:20260814.43c6232

23 added, 3 removed. Audit A to A.

---
name: aso-playbook
description: |
Beginner-friendly App Store Optimization guide covering keyword research, screenshot design, rating management, and A/B testing for iOS and Android. By @WeiYipei β€” practical ASO for indie developers and small teams.
source: https://github.com/Gingiris-1031/gingiris-skills/tree/main/skills/aso-playbook
tags:
- aso
- app-store-optimization
- mobile-growth
- keyword-research
- app-marketing
- app-store
- ios
- android
- app-ranking
- organic-growth
- claude-code
- ai-agent-skill
- indie-developer
- conversion-optimization
- latest
---
## πŸ“¦ Install
```bash
clawhub install aso-playbook
```
**What you get after installing:**
- Keyword research methodology for finding low-competition, high-intent terms
- - Screenshot design principles proven to increase conversion 2-3x
- - A/B testing framework with localization priorities for iOS and Android
+ - Screenshot hypothesis and message-hierarchy framework
+ - A/B testing and evidence-capture framework for iOS and Android
---
# App Store Optimization Basics β€” Keywords, Screenshots & Ratings
> 🌍 **Language / 语言**: [δΈ­ζ–‡](#δΈ­ζ–‡η‰ˆ) | [English](references/en/README.md) | [ζ—₯本θͺž](references/ja/README.md) | [ν•œκ΅­μ–΄](references/ko/README.md)
The fundamentals of ASO for developers who'd rather build than market β€” but need downloads.
- **Keyword research**: Finding low-competition, high-intent keywords for your category
- - **Screenshot optimization**: Design principles that increase conversion rate 2-3x
+ - **Screenshot optimization**: Turn user intent into testable screenshot hypotheses
- **Rating strategy**: How to ask for reviews without annoying users
- **Localization basics**: Which markets to target first and how to test
- **A/B testing**: What to test, how long to run, and interpreting results
+
+ ## Minimum viable ASO workflow
+
+ 1. Export the last 28 days by country and traffic source: impressions, product-page views, first-time downloads, conversion rate, proceeds, D1/D7/D30 retention.
+ 2. Build a keyword sheet with relevance, current rank, search popularity, competition, destination locale and target page.
+ 3. Change one variable family at a time: metadata, icon, first three screenshots, preview video, rating prompt or localization.
+ 4. Record the exact before/after version, release date, storefront and external UA activity.
+ 5. Keep a test only when conversion improves without a material decline in retained users, rating quality or revenue.
+
+ ### Evidence gate
+
+ Do not claim an ASO win from downloads alone. A valid case needs, at minimum:
+
+ - keyword rank or search-impression change;
+ - impression β†’ product-page-view rate;
+ - product-page-view β†’ first-time-download rate;
+ - D7 or D30 retained-user outcome;
+ - dates, storefronts, app version and paid-campaign overlap.
+
+ No controlled Gingiris App Store before/after dataset is bundled with this skill yet. The workflow is executable; any uplift claim must come from the user's own App Store Connect or Play Console export.
## Related Gingiris Skills
- Full version: https://clawhub.ai/gingiris-1031/skills/gingiris-aso-growth
- All skills: https://clawhub.ai/gingiris-1031
- Follow: [@WeiYipei on X](https://x.com/WeiYipei)