/ads apple — Apple Search Ads Analysis

> Deep analysis of Apple Search Ads campaigns for iOS app advertisers.

Usage

bash
/ads apple

Process

1. Collect ASA account data (exports from Apple Search Ads dashboard or pasted metrics)
2. Identify active placement types (Search Results, Search Tab, Today Tab, Product Pages)
3. Evaluate all applicable checks as PASS, WARNING, or FAIL
4. Calculate ASA Health Score (0-100)
5. Generate findings report with action plan

What to Analyze

Campaign Structure (25% weight)

BOFU — Bottom of Funnel (Search Results, Exact Match brand)

• Brand keyword campaign present (own app name + misspellings)
• Competitor campaign present (competitor app names as keywords)
• Category campaigns targeting high-intent generic terms (e.g. "workout app", "budget tracker")

MOFU — Middle of Funnel (Search Match / broad discovery)

• Search Match campaigns active in at least one ad group for discovery
• Search Match ad groups isolated from Exact Match (separate ad groups — never mix)
• Search Terms Report reviewed to mine converting queries for Exact Match promotion

Campaign Architecture Rules:

• Brand / Category / Competitor should be separate campaigns (different CPT bids, budgets)
• Search Match ad groups isolated from manual keyword ad groups — NEVER mix in same ad group
• Goal: let Search Match discover, then promote winners to Exact Match campaigns

Bid Health (20% weight)

CPT (Cost Per Tap) vs Install Rate by Match Type:

• CPT vs category benchmarks (see Benchmarks section below)
• TTR (Tap-Through Rate): benchmark >2.5% for Search Results, >1.5% for Search Tab
• Conversion Rate (tap to install): benchmark 50-65% for brand terms, 20-40% for category
• CPT/CPG (Cost Per Goal): compare against target CPI/CPA from MMP

Bid Strategy:

• Manual CPT bidding appropriate? (Or use Apple's CPA Goals auto-bidding for scaled accounts)
• CPA Goals available at campaign level — evaluate if conversion volume supports it (>100 installs/month per campaign)
• Are bids differentiated by match type? (Brand Exact > Category Exact > Search Match)
• Keyword-level CPT bids set, not just ad group default?

Keyword Health:

• Irrelevant Search Terms (from Search Match) identified and excluded via negative keywords
• Low-performing keywords paused or bid reduced (TTR <1% + high CPT)
• High-volume generic terms checked for intent quality (avoid "free apps" type queries)

Creative Sets (15% weight)

Custom Product Pages (CPP):

• Custom Product Pages created in App Store Connect? (ASA Creative Sets pull from CPPs)
• At least 3 CPP variants tested per campaign type (different value props per audience)
• Creative Sets assigned to high-spend ad groups
• Screenshot/preview variations aligned with keyword intent (e.g. fitness keywords = fitness screenshots)

Default (Store Listing) Creative:

• App icon, subtitle, and first 3 screenshots optimized — these show in ads by default
• Short description (170 chars) compelling and keyword-rich
• Preview video present (strongly recommended for TTR improvement)

Creative Testing:

• Are different Creative Sets being A/B tested within ad groups?
• CPP performance compared: which Creative Set has highest TTR and lowest CPI?

Attribution & MMP Health (15% weight)

MMP Integration (Critical):

• MMP (AppsFlyer / Adjust / Branch / Singular) integrated with ASA via SKAdNetwork + ATT
• ASA is properly connected as a partner in MMP dashboard
• In-app events being sent back to ASA (enables CPA Goals and ROAS optimization)
• Post-install event quality: are purchase, subscription_start, or other revenue events tracked?

SKAdNetwork & ATT:

• SKAdNetwork conversion values configured in MMP (maps user actions to conversion windows)
• ATT opt-in rate monitored (low ATT rate = less MMP data, more reliance on SKAN)
• Privacy threshold considerations: are campaigns getting SKAN postbacks or null reports?

Attribution Windows:

• Default ASA attribution: 30-day click, 1-day view — appropriate for app install goals?
• For re-engagement or subscription goals: evaluate longer lookback windows

Budget Pacing (10% weight)

• Daily cap set at campaign level (budget pacing in ASA is daily, not monthly)
• Actual daily spend vs daily cap ratio: flag if consistently hitting cap (could be missing volume)
• Conversely: flag if spend is <50% of daily cap (creative or bid issue, not budget)
• Budget split across placement types aligned with performance (don't over-invest in underperforming placements)
• Lifetime budget campaigns (if used): check end dates and pacing curves

TAP Coverage — Placement Types (10% weight)

ASA offers 4 placement types — evaluate coverage and performance:

| Placement | Where | Best for | Benchmark CPT | |-----------|-------|----------|----------------| | Search Results | Below search results | High intent, bottom funnel | $0.50-$3.00 | | Search Tab | Top of Search tab | Discovery, mid funnel | $0.30-$1.50 | | Today Tab | App Store home | Brand awareness | $1.00-$5.00 | | Product Pages | Competitor/related app pages | Competitor conquesting | $0.50-$2.00 |

Evaluation:

• Search Results: must be active (highest intent placement)
• Search Tab: active for scale? Evaluate CPT and TTR vs Search Results
• Today Tab: only if budget >$3k/month and brand awareness is a goal (high CPT, low intent)
• Product Pages: competitive opportunity — are competitor CPPs being targeted?

Goal CPA / KPI Assessment (5% weight)

Benchmarks by Category (2025-2026 ASA averages):

| Category | Avg CPT | Avg TTR | Avg Install CVR | Target CPI | |----------|---------|---------|-----------------|------------| | Games | $0.50-$1.00 | 3-5% | 55-70% | $1.00-$3.00 | | Health & Fitness | $1.50-$3.00 | 2-4% | 45-60% | $3.00-$8.00 | | Productivity | $1.00-$2.50 | 2-3.5% | 50-65% | $2.00-$5.00 | | Finance | $2.00-$5.00 | 1.5-3% | 40-55% | $5.00-$15.00 | | Education | $1.00-$2.00 | 2-4% | 50-65% | $2.00-$6.00 | | Shopping | $0.80-$2.00 | 2.5-4% | 45-60% | $2.00-$5.00 | | Lifestyle | $0.80-$1.80 | 2-3.5% | 45-60% | $2.00-$5.00 |

Country-level benchmarks:

• Tier 1 (US, UK, AU, CA, JP): CPT 2-3x above global average; highest LTV
• Tier 2 (DE, FR, KR, SG, HK): CPT 1-1.5x above global average
• Tier 3 (BR, IN, MX): CPT 30-60% below Tier 1; high volume, lower LTV

Checks:

• Actual CPI vs target CPI (from MMP) — flag if >2x target
• CPI trend over 30 days (improving or worsening?)
• Revenue events: is ROAS positive within MMP attribution window?

Output

## Apple Search Ads Audit

**ASA Health Score: [X]/100**

### Critical Issues ([count])
- [Issue with specific impact and fix]

### High Priority ([count])
- [Issue]

### Campaign Structure
PASS/WARNING/FAIL for each check category

### Benchmark Comparison
[Metric] | Your Account | ASA Benchmark | Status

### Quick Wins (do this week)
1. [Most impactful fix with expected outcome]
2.
3.

### Recommended Next Steps
[Prioritized action plan]

Scoring Weights

| Category | Weight | |----------|--------| | Campaign Structure | 25% | | Bid Health | 20% | | Creative Sets | 15% | | Attribution & MMP | 15% | | Budget Pacing | 10% | | TAP Coverage | 10% | | Goal KPI Assessment | 5% |

Data to Request from User

If not provided, ask for:

• Campaign list with spend, installs, CPT, TTR, CVR (last 30 days)
• Active placement types
• MMP being used (AppsFlyer, Adjust, Branch, Singular, or none)
• Target CPI / CPA and app category
• Countries/regions active
• Whether Custom Product Pages are set up in App Store Connect