app-store-optimization

name

app-store-optimization

description

Complete App Store Optimization (ASO) toolkit for keyword research, metadata optimization, competitor analysis, A/B test planning, review sentiment analysis, ASO health scoring, and launch readiness for Apple App Store and Google Play Store. Load BEFORE the iOS or Android release workflow to optimize the store listing. Triggers: "ASO", "app store optimization", "keyword research", "app store listing", "metadata optimize", "competitor analysis", "app store keywords", "ASO score", "review sentiment", "localization strategy", "store listing", "A/B test icon", "launch checklist ASO".

App Store Optimization (ASO)

Iron Law

NO STORE SUBMISSION WITHOUT COMPLETING ASO HEALTH CHECK FIRST — TARGET SCORE ≥ 70/100

Run aso_scorer.py before any first App Store or Play Store submission. A low score wastes review queue time and launch momentum.

When to Use

• Before first App Store or Play Store submission
• Before each major update (new features, new screenshots, new markets)
• When ratings drop — use review_analyzer.py to find root causes
• When downloads plateau — keyword and competitor audit needed
• Before expanding to new markets — localization ROI assessment

Platform Character Limits (enforced by metadata_optimizer.py)

Field	Apple App Store	Google Play
Title	30 chars	50 chars
Subtitle / Short description	30 chars (subtitle)	80 chars
Promotional text	170 chars (editable without update)	—
Full description	4,000 chars	4,000 chars
Keyword field	100 chars (comma-separated, no spaces, no plurals, no duplicates)	— (extracted from title + description)
What's New	4,000 chars	—

Workflow

Step 1 — Keyword Research

Use keyword_analyzer.py to:
- Score candidate keywords by volume/competition/relevance
- Find long-tail opportunities (3–4 word phrases, lower competition)
- Identify which competitor keywords have gaps

Output: Ranked keyword list — primary (title/subtitle), secondary (keyword field), long-tail (description)

Step 2 — Metadata Optimization

Use metadata_optimizer.py to:
- Generate platform-specific title within character limit
- Write subtitle (Apple) / short description (Google)
- Craft conversion-focused full description
- Maximize Apple keyword field (100 chars, no wasted characters)
- Validate all character limits before writing

Apple keyword field rules: No spaces after commas, no plurals if singular exists, no words already in title, no competitor names.

Step 3 — Competitor Analysis

Use competitor_analyzer.py to:
- Extract top 10 competitor keyword strategies
- Identify visual asset approaches (icon style, screenshot structure)
- Find keyword gaps — terms they rank for that you don't target
- Spot positioning opportunities

Step 4 — ASO Health Score

Use aso_scorer.py to:
- Score 0–100 across 4 dimensions:
    Metadata Quality       (0–25): title, description, keyword density
    Ratings & Reviews      (0–25): average rating, volume
    Keyword Performance    (0–25): rankings in top 10/50/100
    Conversion Metrics     (0–25): impression-to-install rate
- Generate prioritized action list

Gate: Score ≥ 70 before proceeding to submission.

Step 5 — A/B Test Plan (icon + screenshots)

Use ab_test_planner.py to:
- Design test hypothesis and variants
- Calculate required impressions for statistical significance
- Define success metric (impression-to-install rate target)
- Recommend test duration

Step 6 — Review Sentiment Analysis (post-launch or before update)

Use review_analyzer.py to:
- Analyze sentiment distribution (positive/negative/neutral)
- Extract top complaint themes — rank by frequency
- Identify feature requests
- Generate response templates per complaint category
- Track sentiment trends across versions

Step 7 — Localization (international expansion)

Use localization_helper.py to:
- Identify high-ROI markets by tier:
    Tier 1: en-US, zh-CN, ja-JP, ko-KR, de-DE, fr-FR
    Tier 2: es-ES, pt-BR, ru-RU, it-IT
    Tier 3: nl-NL, pl-PL, tr-TR, sv-SE
- Adapt keywords per locale (not direct translation)
- Validate character limits per language (German ≈ 1.3× English length)
- Estimate localization ROI before investing

Step 8 — Launch Checklist

Use launch_checklist.py to:
- Generate platform-specific pre-launch checklist
- Validate Apple App Store compliance (metadata, screenshots, legal)
- Validate Google Play compliance (target API, content rating, privacy policy)
- Create update cadence plan
- Identify seasonal campaign opportunities

Scripts Reference

Script	Purpose	Key function
keyword_analyzer.py	Keyword scoring and research	analyze_keyword(), find_long_tail()
metadata_optimizer.py	Title/description/keyword field	optimize_title(), optimize_keyword_field()
competitor_analyzer.py	Competitor keyword + asset analysis	get_top_competitors(), identify_gaps()
aso_scorer.py	0–100 ASO health score	calculate_overall_score(), generate_recommendations()
ab_test_planner.py	A/B test design + significance	design_test(), calculate_sample_size()
localization_helper.py	Multi-market localization	identify_target_markets(), calculate_localization_roi()
review_analyzer.py	Sentiment + theme extraction	analyze_sentiment(), extract_common_themes()
launch_checklist.py	Pre-submission checklist	generate_prelaunch_checklist(), validate_app_store_compliance()

Integration with Release Workflows

This skill runs before the technical submission skills:

app-store-optimization (Phase 0)
        ↓
asc-* skills (iOS: signing → TestFlight → submission → monitoring)
gpd-* skills (Android: upload → beta → health check → staged rollout)

asc-submission-health checks technical compliance (build state, encryption, screenshots exist). This skill checks content quality (keyword strategy, conversion copy, ASO score). They are different layers — both are required before a production submission.

Anti-Patterns

• Don't skip the ASO health check before submission. Running aso_scorer.py after submission wastes review queue time — the gate is pre-submission.
• Don't use the same keywords in both the title and the Apple keyword field. Duplicate keywords waste the 100-character limit; keywords in the title already get indexed.
• Don't directly translate metadata between locales. Keyword intent differs by market — use localization_helper.py for locale-specific keyword research, not machine translation.
• Don't run A/B tests without confirming statistical significance first. Use ab_test_planner.py to calculate required impressions before declaring a winner.

Verify

After running aso_scorer.py, confirm:

• Score output shows ≥ 70/100 before proceeding to submission.
• All character limits validated: metadata_optimizer.py must exit without limit warnings.
• Apple keyword field: run grep "," <keyword_field> to confirm no spaces after commas and no duplicates with the title.

Limitations

• Keyword volume estimates are heuristic — no live Apple/Google API access
• Competitor data covers public store listings only
• A/B testing requires sufficient traffic for statistical significance (12,000+ impressions per variant)
• Store algorithms are proprietary and change without announcement

Documentation Sources

Source	How to Access	Purpose
Apple App Store guidelines	WebFetch apple.com/app-store/review/guidelines	Current metadata requirements
Google Play policy	WebFetch play.google.com/console/about/guides	Current Play Store requirements
ASO scripts	Read scripts in this skill directory	Run analysis functions