alirezarezvani/app-store-optimization

App Store Optimization (ASO)

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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 | |----------|---------------| | App Title | Highest | | Subtitle (iOS) | High | | Keyword Field (iOS) | High | | Short Description (Android) | High | | Full Description | Medium |

See: references/keyword-research-guide.md

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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

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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 |

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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

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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

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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 |

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Tools and References

Scripts

| Script | Purpose | Usage | |--------|---------|-------| | keyword_analyzer.py | Analyze keywords for volume and competition | python keyword_analyzer.py --keywords "todo,task,planner" | | metadata_optimizer.py | Validate metadata character limits and density | python metadata_optimizer.py --platform ios --title "App Title" | | competitor_analyzer.py | Extract and compare competitor keywords | python competitor_analyzer.py --competitors "App1,App2,App3" | | aso_scorer.py | Calculate overall ASO health score | python aso_scorer.py --app-id com.example.app | | ab_test_planner.py | Plan tests and calculate sample sizes | python ab_test_planner.py --cvr 0.05 --lift 0.10 | | review_analyzer.py | Analyze review sentiment and themes | python review_analyzer.py --app-id com.example.app | | launch_checklist.py | Generate platform-specific launch checklists | python launch_checklist.py --platform ios | | localization_helper.py | Manage multi-language metadata | python localization_helper.py --locales "en,es,de,ja" |

References

| Document | Content | |----------|---------| | platform-requirements.md | iOS and Android metadata specs, visual asset requirements | | aso-best-practices.md | Optimization strategies, rating management, launch tactics | | keyword-research-guide.md | Research methodology, evaluation framework, tracking |

Assets

| Template | Purpose | |----------|---------| | aso-audit-template.md | Structured audit checklist for app store listings |

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Platform Notes

| Platform / Constraint | Behavior / Impact | |-----------------------|-------------------| | iOS keyword changes | Require app submission | | iOS promotional text | Editable without an app update | | Android metadata changes | Index in 1-2 hours | | Android keyword field | None — use description instead | | Keyword volume data | Estimates only; no official source | | Competitor data | Public listings only |

When not to use this skill: web apps (use web SEO), enterprise/internal apps, TestFlight-only betas, or paid advertising strategy.

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Related Skills

| Skill | Integration Point | |-------|-------------------| | content-creator | App description copywriting | | marketing-demand-acquisition | Launch promotion campaigns | | marketing-strategy-pmm | Go-to-market planning |

Proactive Triggers

• No keyword optimization in title → App title is the #1 ranking factor. Include top keyword.
• Screenshots don't show value → Screenshots should tell a story, not show UI.
• No ratings strategy → Below 4.0 stars kills conversion. Implement in-app rating prompts.
• Description keyword-stuffed → Natural language with keywords beats keyword stuffing.

Output Artifacts

| When you ask for... | You get... | |---------------------|------------| | "ASO audit" | Full app store listing audit with prioritized fixes | | "Keyword research" | Keyword list with search volume and difficulty scores | | "Optimize my listing" | Rewritten title, subtitle, description, keyword field |

Communication

All output passes quality verification:

• Self-verify: source attribution, assumption audit, confidence scoring
• Output format: Bottom Line → What (with confidence) → Why → How to Act
• Results only. Every finding tagged: 🟢 verified, 🟡 medium, 🔴 assumed.