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. 1. Define target audience and core app functions:

- Primary use case (what problem does the app solve) - Target user demographics - Competitive category

1. 2. Generate seed keywords from:

- App features and benefits - User language (not developer terminology) - App store autocomplete suggestions

1. 3. Expand keyword list using:

- Modifiers (free, best, simple) - Actions (create, track, organize) - Audiences (for students, for teams, for business)

1. 4. Evaluate each keyword:

- Search volume (estimated monthly searches) - Competition (number and quality of ranking apps) - Relevance (alignment with app function)

1. 5. Score and prioritize keywords:

- Primary: Title and keyword field (iOS) - Secondary: Subtitle and short description - Tertiary: Full description only

1. 6. Map keywords to metadata locations
2. Document keyword strategy for tracking
3. 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. 1. Audit current metadata against platform limits:

- Title character count and keyword presence - Subtitle/short description usage - Keyword field efficiency (iOS) - Description keyword density

1. 2. Optimize title following formula:

   [Brand Name] - [Primary Keyword] [Secondary Keyword]
   

1. 3. Write subtitle (iOS) or short description (Android):

- Focus on primary benefit - Include secondary keyword - Use action verbs

1. 4. Optimize keyword field (iOS only):

- Remove duplicates from title - Remove plurals (Apple indexes both forms) - No spaces after commas - Prioritize by score

1. 5. Rewrite full description:

- Hook paragraph with value proposition - Feature bullets with keywords - Social proof section - Call to action

1. 6. Validate character counts for each field
2. Calculate keyword density (target 2-3% primary)
3. 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

CODEBLOCK1

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. 1. Identify top 10 competitors:

- Direct competitors (same core function) - Indirect competitors (overlapping audience) - Category leaders (top downloads)

1. 2. Extract competitor keywords from:

- App titles and subtitles - First 100 words of descriptions - Visible metadata patterns

1. 3. Build competitor keyword matrix:

- Map which keywords each competitor targets - Calculate coverage percentage per keyword

1. 4. Identify keyword gaps:

- Keywords with <40% competitor coverage - High volume terms competitors miss - Long-tail opportunities

1. 5. Analyze competitor visual assets:

- Icon design patterns - Screenshot messaging and style - Video presence and quality

1. 6. Compare ratings and review patterns:

- Average rating by competitor - Common praise themes - Common complaint themes

1. 7. Document positioning opportunities
2. 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. 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

1. 2. Submit for review (2 weeks before):

- Complete all store requirements - Verify compliance with guidelines - Prepare launch communications

1. 3. Configure post-launch systems:

- Set up review monitoring - Prepare response templates - Configure rating prompt timing

1. 4. Execute launch day:

- Verify app is live in both stores - Announce across all channels - Begin review response cycle

1. 5. Monitor initial performance (days 1-7):

- Track download velocity hourly - Monitor reviews and respond within 24 hours - Document any issues for quick fixes

1. 6. Conduct 7-day retrospective:

- Compare performance to projections - Identify quick optimization wins - Plan first metadata update

1. 7. Schedule first update (2 weeks post-launch)
2. 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. 1. Select test element (prioritize by impact):

- Icon (highest impact) - Screenshot 1 (high impact) - Title (high impact) - Short description (medium impact)

1. 2. Form hypothesis:

   If we [change], then [metric] will [improve/increase] by [amount]
   because [rationale].
   

1. 3. Create variants:

- Control: Current version - Treatment: Single variable change

1. 4. Calculate required sample size:

- Baseline conversion rate - Minimum detectable effect (usually 5%) - Statistical significance (95%)

1. 5. Launch test:

- Apple: Use Product Page Optimization - Android: Use Store Listing Experiments

1. 6. Run test for minimum duration:

- At least 7 days - Until statistical significance reached

1. 7. Analyze results:

- Compare conversion rates - Check statistical significance - Document learnings

1. 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

CODEBLOCK3

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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):
CODEBLOCK4

After (Optimized - 97 chars, 14 keywords):
CODEBLOCK5

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:
CODEBLOCK6

After:
CODEBLOCK7

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
keywordanalyzer.py	Analyze keywords for volume and competition	INLINECODE0
metadataoptimizer.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 | | abtest_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.