Apple search ads
Quick answer
- 01What is it?
- Provides specialist in Apple Search Ads (ASA), the only ad platform that places ads natively within the App Store. It stands out by giving paid media a defined shape, so the agent asks for better context and returns a more usable result.
- 02Inputs
- Context for paid media: your goals, audience, constraints, and any source material the skill asks for.
- 03Output
- A ready-to-use result for paid media: the analysis, copy, or recommendations the agent produces.
Add this skill
Install as a package
Installs this one skill package for your coding agent, including any supporting files that skill ships with — not every skill in the repository. Read the tutorial.
$ npx skills add eronred/aso-skills --skill apple-search-adsUse in Profound
Copy this file into a new Profound Skill. That's it, nothing else to install.
Copy and create in ProfoundApple Search Ads
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.
Why ASA Is Different
- Users are actively searching the App Store — highest intent of any channel
- Ads appear exactly like organic results (only "Ad" badge distinguishes them)
- No audience targeting (demographics, interests) — only keyword-based
- Conversion data is reliable (no ATT/SKAdNetwork limitations)
- CPI is typically higher than other channels but LTV is proportionally higher
Campaign Types
| 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 Structure
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)
Why Separate Campaigns
- Separate budgets (protect brand spend from being eaten by generic)
- Separate bid strategies per intent type
- Clean performance data per keyword type
- Easier to pause/scale individual segments
Match Types
| 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.
Keyword Strategy
Seed List by Campaign
Brand campaign:
- Your app name (exact)
- Common misspellings
- Your developer name
Competitor campaign:
- Top 5–10 competitor app names (exact)
- Tip: bid lower, watch conversion — brand-searchers for competitors convert at lower rates
Category campaign:
- High-volume generic terms: "meditation app", "habit tracker", "budget planner"
- Long-tail terms: "meditation app for anxiety", "daily habit tracker free"
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
Negative Keywords
Essential to prevent waste. Add negatives at account level:
- Competitor names you're not targeting (avoid accidentally winning at bad CVR)
- Irrelevant terms from Search Match (review weekly)
- Terms with high impressions, zero taps
Bidding Strategy
Starting Bids
| 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 |
Bid Optimization Signals
| 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)
Automated Bidding
ASA offers automated bidding toward a target CPA or target ROAS. Use only after:
- Campaign has 50+ conversions per ad group per week (minimum data)
- Manual bidding has established a baseline CPT
Creative Product Sets (CPS) and CPP Routing
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.
Metrics and Benchmarks
| 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%+ |
Weekly Optimization Checklist
- [ ] 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
Scaling Checklist
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
Output Format
Campaign Audit
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]
Related Skills
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 spend
Common questions
How do I install Apple search ads in Cursor, Claude Code, or Codex?
Run npx skills add eronred/aso-skills --skill apple-search-ads in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only Apple search ads, not every skill in the repository.
Where does Apple search ads come from and what license is it under?
Apple search ads comes from the eronred/aso-skills repository on GitHub. That repository has 1.6K GitHub stars. The skill is published under the MIT license.
Prefer plain text? Read the Apple search ads guide as markdown.
Related skills
More from eronred
More Paid Ads skills