app-store-optimization

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. Use when this capability is needed.
metadata	{"author":"demerzels-lab"}

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.

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Table of Contents

• Keyword Research Workflow
• Metadata Optimization Workflow
• Competitor Analysis Workflow
• App Launch Workflow
• A/B Testing Workflow
• Before/After Examples
• Tools and References

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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	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

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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 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

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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

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