app-store-optimization by alirezarezvani
App Store Optimization toolkit for researching keywords, optimizing metadata, and tracking mobile app performance on Apple App Store and Google Play Store.
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Updated Jan 8, 2026, 08:39 AM
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---
name: app-store-optimization
description: App Store Optimization toolkit for researching keywords, optimizing metadata, and tracking mobile app performance on Apple App Store and Google Play Store.
triggers:
- ASO
- app store optimization
- app store ranking
- app keywords
- app metadata
- play store optimization
- app store listing
- improve app rankings
- app visibility
- app store SEO
- mobile app marketing
- app conversion rate
---
# App Store Optimization (ASO)
ASO tools for researching keywords, optimizing metadata, analyzing competitors, and improving app store visibility on Apple App Store and Google Play Store.
---
## Table of Contents
- [Keyword Research Workflow](#keyword-research-workflow)
- [Metadata Optimization Workflow](#metadata-optimization-workflow)
- [Competitor Analysis Workflow](#competitor-analysis-workflow)
- [App Launch Workflow](#app-launch-workflow)
- [A/B Testing Workflow](#ab-testing-workflow)
- [Before/After Examples](#beforeafter-examples)
- [Tools and References](#tools-and-references)
---
## Keyword Research Workflow
Discover and evaluate keywords that drive app store visibility.
### Workflow: Conduct Keyword Research
1. Define target audience and core app functions:
- Primary use case (what problem does the app solve)
- Target user demographics
- Competitive category
2. Generate seed keywords from:
- App features and benefits
- User language (not developer terminology)
- App store autocomplete suggestions
3. Expand keyword list using:
- Modifiers (free, best, simple)
- Actions (create, track, organize)
- Audiences (for students, for teams, for business)
4. Evaluate each keyword:
- Search volume (estimated monthly searches)
- Competition (number and quality of ranking apps)
- Relevance (alignment with app function)
5. Score and prioritize keywords:
- Primary: Title and keyword field (iOS)
- Secondary: Subtitle and short description
- Tertiary: Full description only
6. Map keywords to metadata locations
7. Document keyword strategy for tracking
8. **Validation:** Keywords scored; placement mapped; no competitor brand names included; no plurals in iOS keyword field
### Keyword Evaluation Criteria
| Factor | Weight | High Score Indicators |
|--------|--------|----------------------|
| Relevance | 35% | Describes core app function |
| Volume | 25% | 10,000+ monthly searches |
| Competition | 25% | Top 10 apps have <4.5 avg rating |
| Conversion | 15% | Transactional intent ("best X app") |
### Keyword Placement Priority
| Location | Search Weight | Character Limit |
|----------|---------------|-----------------|
| App Title | Highest | 30 (iOS) / 50 (Android) |
| Subtitle (iOS) | High | 30 |
| Keyword Field (iOS) | High | 100 |
| Short Description (Android) | High | 80 |
| Full Description | Medium | 4,000 |
See: [references/keyword-research-guide.md](references/keyword-research-guide.md)
---
## Metadata Optimization Workflow
Optimize app store listing elements for search ranking and conversion.
### Workflow: Optimize App Metadata
1. Audit current metadata against platform limits:
- Title character count and keyword presence
- Subtitle/short description usage
- Keyword field efficiency (iOS)
- Description keyword density
2. Optimize title following formula:
```
[Brand Name] - [Primary Keyword] [Secondary Keyword]
```
3. Write subtitle (iOS) or short description (Android):
- Focus on primary benefit
- Include secondary keyword
- Use action verbs
4. Optimize keyword field (iOS only):
- Remove duplicates from title
- Remove plurals (Apple indexes both forms)
- No spaces after commas
- Prioritize by score
5. Rewrite full description:
- Hook paragraph with value proposition
- Feature bullets with keywords
- Social proof section
- Call to action
6. Validate character counts for each field
7. Calculate keyword density (target 2-3% primary)
8. **Validation:** All fields within character limits; primary keyword in title; no keyword stuffing (>5%); natural language preserved
### Platform Character Limits
| Field | Apple App Store | Google Play Store |
|-------|-----------------|-------------------|
| Title | 30 characters | 50 characters |
| Subtitle | 30 characters | N/A |
| Short Description | N/A | 80 characters |
| Keywords | 100 characters | N/A |
| Promotional Text | 170 characters | N/A |
| Full Description | 4,000 characters | 4,000 characters |
| What's New | 4,000 characters | 500 characters |
### Description Structure
```
PARAGRAPH 1: Hook (50-100 words)
├── Address user pain point
├── State main value proposition
└── Include primary keyword
PARAGRAPH 2-3: Features (100-150 words)
├── Top 5 features with benefits
├── Bullet points for scanability
└── Secondary keywords naturally integrated
PARAGRAPH 4: Social Proof (50-75 words)
├── Download count or rating
├── Press mentions or awards
└── Summary of user testimonials
PARAGRAPH 5: Call to Action (25-50 words)
├── Clear next step
└── Reassurance (free trial, no signup)
```
See: [references/platform-requirements.md](references/platform-requirements.md)
---
## Competitor Analysis Workflow
Analyze top competitors to identify keyword gaps and positioning opportunities.
### Workflow: Analyze Competitor ASO Strategy
1. Identify top 10 competitors:
- Direct competitors (same core function)
- Indirect competitors (overlapping audience)
- Category leaders (top downloads)
2. Extract competitor keywords from:
- App titles and subtitles
- First 100 words of descriptions
- Visible metadata patterns
3. Build competitor keyword matrix:
- Map which keywords each competitor targets
- Calculate coverage percentage per keyword
4. Identify keyword gaps:
- Keywords with <40% competitor coverage
- High volume terms competitors miss
- Long-tail opportunities
5. Analyze competitor visual assets:
- Icon design patterns
- Screenshot messaging and style
- Video presence and quality
6. Compare ratings and review patterns:
- Average rating by competitor
- Common praise themes
- Common complaint themes
7. Document positioning opportunities
8. **Validation:** 10+ competitors analyzed; keyword matrix complete; gaps identified with volume estimates; visual audit documented
### Competitor Analysis Matrix
| Analysis Area | Data Points |
|---------------|-------------|
| Keywords | Title keywords, description frequency |
| Metadata | Character utilization, keyword density |
| Visuals | Icon style, screenshot count/style |
| Ratings | Average rating, total count, velocity |
| Reviews | Top praise, top complaints |
### Gap Analysis Template
| Opportunity Type | Example | Action |
|------------------|---------|--------|
| Keyword gap | "habit tracker" (40% coverage) | Add to keyword field |
| Feature gap | Competitor lacks widget | Highlight in screenshots |
| Visual gap | No videos in top 5 | Create app preview |
| Messaging gap | None mention "free" | Test free positioning |
---
## App Launch Workflow
Execute a structured launch for maximum initial visibility.
### Workflow: Launch App to Stores
1. Complete pre-launch preparation (4 weeks before):
- Finalize keywords and metadata
- Prepare all visual assets
- Set up analytics (Firebase, Mixpanel)
- Build press kit and media list
2. Submit for review (2 weeks before):
- Complete all store requirements
- Verify compliance with guidelines
- Prepare launch communications
3. Configure post-launch systems:
- Set up review monitoring
- Prepare response templates
- Configure rating prompt timing
4. Execute launch day:
- Verify app is live in both stores
- Announce across all channels
- Begin review response cycle
5. Monitor initial performance (days 1-7):
- Track download velocity hourly
- Monitor reviews and respond within 24 hours
- Document any issues for quick fixes
6. Conduct 7-day retrospective:
- Compare performance to projections
- Identify quick optimization wins
- Plan first metadata update
7. Schedule first update (2 weeks post-launch)
8. **Validation:** App live in stores; analytics tracking; review responses within 24h; download velocity documented; first update scheduled
### Pre-Launch Checklist
| Category | Items |
|----------|-------|
| Metadata | Title, subtitle, description, keywords |
| Visual Assets | Icon, screenshots (all sizes), video |
| Compliance | Age rating, privacy policy, content rights |
| Technical | App binary, signing certificates |
| Analytics | SDK integration, event tracking |
| Marketing | Press kit, social content, email ready |
### Launch Timing Considerations
| Factor | Recommendation |
|--------|----------------|
| Day of week | Tuesday-Wednesday (avoid weekends) |
| Time of day | Morning in target market timezone |
| Seasonal | Align with relevant category seasons |
| Competition | Avoid major competitor launch dates |
See: [references/aso-best-practices.md](references/aso-best-practices.md)
---
## A/B Testing Workflow
Test metadata and visual elements to improve conversion rates.
### Workflow: Run A/B Test
1. Select test element (prioritize by impact):
- Icon (highest impact)
- Screenshot 1 (high impact)
- Title (high impact)
- Short description (medium impact)
2. Form hypothesis:
```
If we [change], then [metric] will [improve/increase] by [amount]
because [rationale].
```
3. Create variants:
- Control: Current version
- Treatment: Single variable change
4. Calculate required sample size:
- Baseline conversion rate
- Minimum detectable effect (usually 5%)
- Statistical significance (95%)
5. Launch test:
- Apple: Use Product Page Optimization
- Android: Use Store Listing Experiments
6. Run test for minimum duration:
- At least 7 days
- Until statistical significance reached
7. Analyze results:
- Compare conversion rates
- Check statistical significance
- Document learnings
8. **Validation:** Single variable tested; sample size sufficient; significance reached (95%); results documented; winner implemented
### A/B Test Prioritization
| Element | Conversion Impact | Test Complexity |
|---------|-------------------|-----------------|
| App Icon | 10-25% lift possible | Medium (design needed) |
| Screenshot 1 | 15-35% lift possible | Medium |
| Title | 5-15% lift possible | Low |
| Short Description | 5-10% lift possible | Low |
| Video | 10-20% lift possible | High |
### Sample Size Quick Reference
| Baseline CVR | Impressions Needed (per variant) |
|--------------|----------------------------------|
| 1% | 31,000 |
| 2% | 15,500 |
| 5% | 6,200 |
| 10% | 3,100 |
### Test Documentation Template
```
TEST ID: ASO-2025-001
ELEMENT: App Icon
HYPOTHESIS: A bolder color icon will increase conversion by 10%
START DATE: [Date]
END DATE: [Date]
RESULTS:
├── Control CVR: 4.2%
├── Treatment CVR: 4.8%
├── Lift: +14.3%
├── Significance: 97%
└── Decision: Implement treatment
LEARNINGS:
- Bold colors outperform muted tones in this category
- Apply to screenshot backgrounds for next test
```
---
## Before/After Examples
### Title Optimization
**Productivity App:**
| Version | Title | Analysis |
|---------|-------|----------|
| Before | "MyTasks" | No keywords, brand only (8 chars) |
| After | "MyTasks - Todo List & Planner" | Primary + secondary keywords (29 chars) |
**Fitness App:**
| Version | Title | Analysis |
|---------|-------|----------|
| Before | "FitTrack Pro" | Generic modifier (12 chars) |
| After | "FitTrack: Workout Log & Gym" | Category keywords (27 chars) |
### Subtitle Optimization (iOS)
| Version | Subtitle | Analysis |
|---------|----------|----------|
| Before | "Get Things Done" | Vague, no keywords |
| After | "Daily Task Manager & Planner" | Two keywords, benefit clear |
### Keyword Field Optimization (iOS)
**Before (Inefficient - 89 chars, 8 keywords):**
```
task manager, todo list, productivity app, daily planner, reminder app
```
**After (Optimized - 97 chars, 14 keywords):**
```
task,todo,checklist,reminder,organize,daily,planner,schedule,deadline,goals,habit,widget,sync,team
```
**Improvements:**
- Removed spaces after commas (+8 chars)
- Removed duplicates (task manager → task)
- Removed plurals (reminders → reminder)
- Removed words in title
- Added more relevant keywords
### Description Opening
**Before:**
```
MyTasks is a comprehensive task management solution designed
to help busy professionals organize their daily activities
and boost productivity.
```
**After:**
```
Forget missed deadlines. MyTasks keeps every task, reminder,
and project in one place—so you focus on doing, not remembering.
Trusted by 500,000+ professionals.
```
**Improvements:**
- Leads with user pain point
- Specific benefit (not generic "boost productivity")
- Social proof included
- Keywords natural, not stuffed
### Screenshot Caption Evolution
| Version | Caption | Issue |
|---------|---------|-------|
| Before | "Task List Feature" | Feature-focused, passive |
| Better | "Create Task Lists" | Action verb, but still feature |
| Best | "Never Miss a Deadline" | Benefit-focused, emotional |
---
## Tools and References
### Scripts
| Script | Purpose | Usage |
|--------|---------|-------|
| [keyword_analyzer.py](scripts/keyword_analyzer.py) | Analyze keywords for volume and competition | `python keyword_analyzer.py --keywords "todo,task,planner"` |
| [metadata_optimizer.py](scripts/metadata_optimizer.py) | Validate metadata character limits and density | `python metadata_optimizer.py --platform ios --title "App Title"` |
| [competitor_analyzer.py](scripts/competitor_analyzer.py) | Extract and compare competitor keywords | `python competitor_analyzer.py --competitors "App1,App2,App3"` |
| [aso_scorer.py](scripts/aso_scorer.py) | Calculate overall ASO health score | `python aso_scorer.py --app-id com.example.app` |
| [ab_test_planner.py](scripts/ab_test_planner.py) | Plan tests and calculate sample sizes | `python ab_test_planner.py --cvr 0.05 --lift 0.10` |
| [review_analyzer.py](scripts/review_analyzer.py) | Analyze review sentiment and themes | `python review_analyzer.py --app-id com.example.app` |
| [launch_checklist.py](scripts/launch_checklist.py) | Generate platform-specific launch checklists | `python launch_checklist.py --platform ios` |
| [localization_helper.py](scripts/localization_helper.py) | Manage multi-language metadata | `python localization_helper.py --locales "en,es,de,ja"` |
### References
| Document | Content |
|----------|---------|
| [platform-requirements.md](references/platform-requirements.md) | iOS and Android metadata specs, visual asset requirements |
| [aso-best-practices.md](references/aso-best-practices.md) | Optimization strategies, rating management, launch tactics |
| [keyword-research-guide.md](references/keyword-research-guide.md) | Research methodology, evaluation framework, tracking |
### Assets
| Template | Purpose |
|----------|---------|
| [aso-audit-template.md](assets/aso-audit-template.md) | Structured audit checklist for app store listings |
---
## Platform Limitations
### Data Constraints
| Constraint | Impact |
|------------|--------|
| No official keyword volume data | Estimates based on third-party tools |
| Competitor data limited to public info | Cannot see internal metrics |
| Review access limited to public reviews | No access to private feedback |
| Historical data unavailable for new apps | Cannot compare to past performance |
### Platform Behavior
| Platform | Behavior |
|----------|----------|
| iOS | Keyword changes require app submission |
| iOS | Promotional text editable without update |
| Android | Metadata changes index in 1-2 hours |
| Android | No separate keyword field (use description) |
| Both | Algorithm changes without notice |
### When Not to Use This Skill
| Scenario | Alternative |
|----------|-------------|
| Web apps | Use web SEO skills |
| Enterprise apps (not public) | Internal distribution tools |
| Beta/TestFlight only | Focus on feedback, not ASO |
| Paid advertising strategy | Use paid acquisition skills |
---
## Related Skills
| Skill | Integration Point |
|-------|-------------------|
| [content-creator](../content-creator/) | App description copywriting |
| [marketing-demand-acquisition](../marketing-demand-acquisition/) | Launch promotion campaigns |
| [marketing-strategy-pmm](../marketing-strategy-pmm/) | Go-to-market planning |
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