SKILLS/apple-search-ads/SKILL.md
When the user wants to set up, optimize, or scale Apple Search Ads (ASA) campaigns — including keyword bidding, match types, campaign structure, Creative Product Sets, CPP routing, and ROAS optimization. Use when the user mentions "Apple Search Ads", "ASA", "Search Ads", "Search tab ads", "Today tab ads", "CPT", "TTR", "Search Match", "exact match", "broad match", "CPP in ads", "ASA bidding", or "Search Ads budget". For Meta/Google UAC/TikTok paid UA, see ua-campaign.
npx skillsauth add pinkpixel-dev/skills-collection-1 apple-search-adsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You are a specialist in Apple Search Ads (ASA) — the only ad platform that places ads natively within the App Store. ASA drives highly qualified installs because users are already in purchase intent.
| Placement | Where it appears | Best for | |-----------|-----------------|---------| | Search Results | Below the first organic result for a keyword | Keyword-specific intent capture | | Search Tab | Top of the Search tab before user types | Brand awareness, broad reach | | Today Tab | App Store home page | High-visibility brand moments | | Product Pages | Competitor and related app pages | Competitive conquesting |
Start with Search Results. It's the highest-intent, most measurable, most controllable placement.
Account
└── App (one per app)
├── Campaign: Brand
│ └── Ad Group: Brand keywords
├── Campaign: Competitor
│ └── Ad Group: Competitor app names
├── Campaign: Category
│ └── Ad Group: Generic category terms
├── Campaign: Discovery (Search Match)
│ └── Ad Group: Search Match on (no keywords)
└── Campaign: Search Tab (optional)
└── Ad Group: (no keywords needed)
| Match Type | How it works | Use for | |------------|-------------|---------| | Exact | Only triggers on exact keyword | High-value, proven terms | | Broad | Triggers on variations, related terms | Discovery | | Search Match | Apple auto-matches your app to relevant searches | Discovery campaign only |
Workflow: Use Search Match + broad in discovery. Mine the search terms report weekly. Move top performers to exact match in a separate campaign with higher bids.
Brand campaign:
Competitor campaign:
Category campaign:
Use Appeeky to validate volume and difficulty:
GET /v1/keywords/metrics?keywords=meditation+app,mindfulness,sleep+sounds&country=us
GET /v1/keywords/suggestions?term=meditation&country=us
Essential to prevent waste. Add negatives at account level:
| Campaign | Starting bid strategy | |---------|--------------------| | Brand | High (you should always win your brand terms) — start at $2–5 | | Competitor | Moderate — start at $1–2, watch CVR | | Category | Moderate — start at $0.80–1.50 | | Discovery | Low — start at $0.50–0.80 |
| Signal | Action | |--------|--------| | Low impression share (<50%) | Increase bid | | High TTR but low conversion | Improve product page or paywall | | Low TTR | Creative may not match keyword intent | | High CVR but spend not scaling | Increase bid or budget cap | | CPT rising with no CVR improvement | Reduce bid or pause keyword |
Target CPT = Target CPI × Historical CVR (installs/taps)
ASA offers automated bidding toward a target CPA or target ROAS. Use only after:
Link Custom Product Pages (CPPs) to specific ad groups to show tailored creatives:
Ad Group: "yoga app" keyword → CPP: Yoga-themed screenshots
Ad Group: "sleep sounds" keyword → CPP: Sleep-themed screenshots
Ad Group: Competitor keywords → CPP: Comparison-focused screenshots
Why this works: Users searching "yoga app" see yoga screenshots instead of generic app screenshots. TTR and CVR both improve (typically +15–30%).
Setup: App Store Connect → Custom Product Pages → create pages → ASA → Ad Group → select CPP.
| Metric | Formula | Benchmark | |--------|---------|-----------| | TTR | Taps / Impressions | > 5% strong; < 3% investigate creative | | CVR | Installs / Taps | > 50% good; < 30% review product page | | CPT | Spend / Taps | Varies by category | | CPI | Spend / Installs | Varies; compare to LTV | | ROAS | Revenue / Spend | > 100% = profitable; target 150%+ |
- [ ] Review Search Terms report → add top new terms to exact match campaigns
- [ ] Add new negatives from irrelevant search terms
- [ ] Check impression share per keyword → adjust bids where < 50%
- [ ] Pause keywords with 100+ taps and 0 installs
- [ ] Review TTR per ad group → test new CPS/CPP if TTR < 3%
- [ ] Check budget pacing — no campaigns hitting daily cap before noon
- [ ] Compare CVR across campaigns — Category vs Brand vs Competitor
Before increasing budget:
- [ ] CVR > 30% on main campaigns
- [ ] CPI < 3× your target
- [ ] Bid strategy is manual and stable
- [ ] Negative keyword list maintained
- [ ] At least 2 CPP variants tested
Account: [App Name]
Campaign Structure:
✓/✗ Brand campaign
✓/✗ Competitor campaign
✓/✗ Category campaign
✓/✗ Discovery campaign
Performance ([period]):
Impressions: [N]
Taps: [N] (TTR: [X]%)
Installs: [N] (CVR: [X]%)
CPI: $[N]
Spend: $[N]
Top issues:
1. [issue] — [recommended fix]
2. [issue] — [recommended fix]
Priority actions:
1. [specific change] — Expected impact: [rationale]
2. [specific change] — Expected impact: [rationale]
ua-campaign — Full paid UA across all channels (Meta, Google, TikTok)keyword-research — Identify keywords to target in ASAscreenshot-optimization — Build CPPs for keyword-specific creativesab-test-store-listing — Test product page CVR before scaling spendtesting
When the user wants a full ASO health audit, review their App Store listing quality, or diagnose why their app isn't ranking. Also use when the user mentions "ASO audit", "ASO score", "why am I not ranking", "listing review", or "optimize my app store page". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.
testing
Clarify requirements before implementing. Use when serious doubts arise.
tools
Complete reference and build guide for ASI:One (ASI1) — the AI platform by Fetch.ai built for agentic, Web3-native applications. Use this skill IMMEDIATELY and ALWAYS when the user mentions ASI1, ASI:One, Fetch.ai AI API, building with ASI1, integrating ASI:One, asking about ASI1 models, tool calling with ASI1, ASI1 image generation, ASI1 agentic LLM, Agentverse, uagents, Agent Chat Protocol, structured output with ASI1, or OpenAI-compatible wrappers for ASI1. Also trigger when the user says things like "use ASI1 instead of OpenAI", "build an app with ASI:One", "ASI1 API", or references docs.asi1.ai. This skill covers everything needed to build production apps - setup, all models, all API features, tool calling, image gen, agentic orchestration, structured data, session management, streaming, LangChain integration, uagents / Agent Chat Protocol, and TypeScript/Node.js patterns.
data-ai
When the user wants to analyze their own app's actual performance data from App Store Connect — real downloads, revenue, IAP, subscriptions, trials, or country breakdowns synced via Appeeky Connect. Use when the user asks about "my downloads", "my revenue", "how is my app performing", "ASC data", "sales and trends", "my subscription numbers", "App Store Connect metrics", or wants to compare periods or top markets. For third-party app estimates, see app-analytics. For subscription analytics depth, see monetization-strategy.