Apple search ads

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.
Paste-ready

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.

Terminal
$ npx skills add eronred/aso-skills --skill apple-search-ads

Use in Profound

Copy this file into a new Profound Skill. That's it, nothing else to install.

Copy and create in Profound
SKILL.md

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

PlacementWhere it appearsBest for
Search ResultsBelow the first organic result for a keywordKeyword-specific intent capture
Search TabTop of the Search tab before user typesBrand awareness, broad reach
Today TabApp Store home pageHigh-visibility brand moments
Product PagesCompetitor and related app pagesCompetitive 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 TypeHow it worksUse for
ExactOnly triggers on exact keywordHigh-value, proven terms
BroadTriggers on variations, related termsDiscovery
Search MatchApple auto-matches your app to relevant searchesDiscovery 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

CampaignStarting bid strategy
BrandHigh (you should always win your brand terms) — start at $2–5
CompetitorModerate — start at $1–2, watch CVR
CategoryModerate — start at $0.80–1.50
DiscoveryLow — start at $0.50–0.80

Bid Optimization Signals

SignalAction
Low impression share (<50%)Increase bid
High TTR but low conversionImprove product page or paywall
Low TTRCreative may not match keyword intent
High CVR but spend not scalingIncrease bid or budget cap
CPT rising with no CVR improvementReduce 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

MetricFormulaBenchmark
TTRTaps / Impressions> 5% strong; < 3% investigate creative
CVRInstalls / Taps> 50% good; < 30% review product page
CPTSpend / TapsVaries by category
CPISpend / InstallsVaries; compare to LTV
ROASRevenue / 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 ASA
  • screenshot-optimization — Build CPPs for keyword-specific creatives
  • ab-test-store-listing — Test product page CVR before scaling spend

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.