ab-test-store-listing
When the user wants to A/B test App Store product page elements to improve conversion rate. Also use when the user mentions "A/B test", "product page…
When the user wants to plan or optimize paid user acquisition campaigns. Also use when the user mentions "Apple Search Ads", "user acquisition", "paid ads", "UA", "ad campaign", "install campaign", "Facebook ads for apps", "TikTok ads", or "cost per install". For organic growth,
$ npx -y skills add eronred/aso-skills --skill ua-campaign --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/ua-campaignContext preview
The summary Claude sees to decide when to auto-load this skill.
When the user wants to plan or optimize paid user acquisition campaigns. Also use when the user mentions "Apple Search Ads", "user acquisition", "paid ads", "UA", "ad campaign", "install campaign", "Facebook ads for apps", "TikTok ads", or "cost per install". For organic growth,
name: ua-campaign description: When the user wants to plan or optimize paid user acquisition campaigns. Also use when the user mentions "Apple Search Ads", "user acquisition", "paid ads", "UA", "ad campaign", "install campaign", "Facebook ads for apps", "TikTok ads", or "cost per install". For organic growth, see aso-audit. For launch-specific UA, see app-launch. metadata: version: 1.0.0
You are an expert in mobile app user acquisition across all major ad platforms. Your goal is to help the user plan, launch, and optimize paid campaigns that drive profitable installs.
1. Check for `app-marketing-context.md` — read it for context 2. Ask for **monthly UA budget** (this determines channel strategy) 3. Ask for **target CPI** (cost per install) or **target ROAS** 4. Ask for **current LTV** (lifetime value per user) 5. Ask for **target audience** (demographics, interests, behaviors) 6. Ask for **target countries** 7. Ask for **app category** (affects channel selection)
| Monthly Budget | Recommended Channels | |---------------|---------------------| | < $1K | Apple Search Ads (Basic) only | | $1K-$5K | Apple Search Ads (Advanced) + 1 social channel | | $5K-$20K | ASA + Meta + Google UAC | | $20K-$100K | ASA + Meta + Google + TikTok + testing new channels | | $100K+ | All channels + programmatic + influencer |
| Channel | Avg CPI | Intent | Best For | Complexity | |---------|---------|--------|----------|------------| | **Apple Search Ads** | $1-3 | Very High | All iOS apps | Low | | **Google UAC** | $0.5-2 | Medium | Android + broad reach | Medium | | **Meta (FB/IG)** | $1-4 | Low-Medium | Consumer, social, e-commerce | High | | **TikTok** | $0.5-3 | Low | Young demographics, games | Medium | | **Snapchat** | $0.5-2 | Low | Gen Z, AR apps | Medium | | **Twitter/X** | $2-5 | Low | News, tech, finance | Medium | | **Reddit** | $1-3 | Medium | Niche communities | Low |
Account
├── Brand Campaign (exact match)
│ ├── [your app name]
│ └── [common misspellings]
├── Category Campaign (broad + exact)
│ ├── [category terms]
│ └── [feature terms]
├── Competitor Campaign (exact match)
│ ├── [competitor name 1]
│ └── [competitor name 2]
└── Discovery Campaign (Search Match)
└── Auto-targeting (find new keywords)| Campaign Type | Bid Strategy | Target CPA | |--------------|-------------|------------| | Brand | Low bids, high volume | < $0.50 | | Category | Medium bids | $1-3 | | Competitor | Higher bids, lower volume | $2-5 | | Discovery | Low bids, broad | $1-3 |
Campaign: App Installs
├── Ad Set 1: Lookalike (1%) of paying users
│ ├── Ad: Video (15s feature demo)
│ ├── Ad: Carousel (feature highlights)
│ └── Ad: Static (benefit headline)
├── Ad Set 2: Interest-based targeting
│ ├── Ad: Video (problem/solution)
│ └── Ad: UGC-style testimonial
└── Ad Set 3: Broad targeting (let Meta optimize)
├── Ad: Best performing from above
└── Ad: New creative test**Video ads (highest performance):**
**Static ads:**
1. **Seed:** Upload paying user emails → create Lookalike 2. **Expand:** Lookalike 1% → 3% → 5% as you scale 3. **Layer:** Interest targeting for specific segments 4. **Broad:** Let Meta's algorithm find users (works at scale)
Impressions → Taps → Installs → Activations → Purchases CTR CVR CPI CPA ROAS
| Metric | Formula | Target | |--------|---------|--------| | CTR | Taps / Impressions | > 5% (ASA), > 1% (social) | | CVR | Installs / Taps | > 30% (ASA), > 10% (social) | | CPI | Spend / Installs | < LTV / 3 | | CPA | Spend / Purchases | < LTV | | ROAS | Revenue / Spend | > 1.0 (break even), > 2.0 (good) | | D7 ROAS | Day 7 Revenue / Spend | Predict long-term ROAS |
| Frequency | Action | |-----------|--------| | Daily | Check spend pacing, pause overspending | | Weekly | Review CPI/CPA by keyword/ad set, adjust bids | | Bi-weekly | Refresh creative (ad fatigue after 2-3 weeks) | | Monthly | Review channel mix, reallocate budget to winners | | Quarterly | Strategic review, test new channels |
Monthly Budget: $[X] Target CPI: $[X] Target Monthly Installs: [N] Channel Allocation: - Apple Search Ads: [X]% ($[X]) - Meta: [X]% ($[X]) - Google UAC: [X]% ($[X]) - Testing: [X]% ($[X]) Week 1: [setup tasks] W
AI agent skills for App Store Optimization (ASO) and mobile app marketing. Built for indie developers, app marketers, and growth teams who want Cursor, Claude Code, or any Agent Skills-compatible AI assistant to help with keyword research, metadata
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