Apple Search Ads

Apple 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 ( 5% strong; 50% good; 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  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 ASA
• screenshot-optimization — Build CPPs for keyword-specific creatives
• ab-test-store-listing — Test product page CVR before scaling spend

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Eronred
• Source: Eronred/aso-skills
• License: MIT
• Homepage: https://appeeky.com/

Install and usage instructions live in the source repository linked above.