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ads-attribution

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Mis à jour17 mai 2026 à 01:10

Cross-platform attribution health audit covering AdAttributionKit (iOS view-through 24h post-impression, WWDC 2025 configurable windows), GA4 attribution models (data-driven vs last-click), Consent Mode V2 enforcement, server-side attribution stitching, MMP integration health, and cross-device / cross-platform attribution. Use when user says attribution audit, attribution model, AdAttributionKit, AAK, view-through attribution, GA4 attribution, Consent Mode V2, conversion window, attribution window, MMP audit, AppsFlyer audit, Adjust audit, Branch audit, Singular audit, cross-device attribution, or cross-platform attribution.

Installation

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Source

AgriciDaniel

AgriciDaniel/claude-ads

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Métiers associésSOC

Basé sur la classification professionnelle SOC

Analystes en études de marché et spécialistes en marketingProfessions des affaires et des opérations financières·SOC 13-1161

SKILL.md

readonly

name	ads-attribution
description	Cross-platform attribution health audit covering AdAttributionKit (iOS view-through 24h post-impression, WWDC 2025 configurable windows), GA4 attribution models (data-driven vs last-click), Consent Mode V2 enforcement, server-side attribution stitching, MMP integration health, and cross-device / cross-platform attribution. Use when user says attribution audit, attribution model, AdAttributionKit, AAK, view-through attribution, GA4 attribution, Consent Mode V2, conversion window, attribution window, MMP audit, AppsFlyer audit, Adjust audit, Branch audit, Singular audit, cross-device attribution, or cross-platform attribution.
user-invokable	false
tested_date	"2026-05-17T00:00:00.000Z"
tested_with	claude-code v2.x

Cross-Platform Attribution Health Audit

Attribution decay is the silent revenue killer of 2026 — Consent Mode V2 EEA enforcement (Jul 21, 2025), iOS ATT, SKAdNetwork → AdAttributionKit migration, and the death of third-party cookies have moved every advertiser's attribution signal toward modeled, server-side, first-party data. Misaligned attribution windows or unverified Consent Mode setups will mis-attribute 15-40% of conversions and silently waste budget.

Process

Collect current attribution stack: GA4 property ID, Google Ads conversion actions, Meta CAPI config, Apple Ads / AdAttributionKit registration, MMP dashboard (AppsFlyer / Adjust / Branch / Singular), any sGTM container
Read ads/references/conversion-tracking.md for the cross-platform tracking baseline
Evaluate attribution health per surface (web, iOS app, Android app, server-side)
Score each surface PASS / WARNING / FAIL
Generate findings report with cross-channel attribution map and remediation plan

What to Analyze

iOS Attribution (AdAttributionKit + ATT)

AdAttributionKit registered with Apple Ads (post-Apr 10, 2025 cutover); registration creates dual attribution with SKAdNetwork (SKAN v1-3)
View-through attribution active — 24h post-impression view window configured on Apple Ads campaigns where applicable
Configurable attribution windows (WWDC 2025): per-campaign window customization audited; overlapping re-engagement windows used for subscription / re-acquisition campaigns
Country code in postbacks (WWDC 2025): enabled if you need geo attribution detail
ATT (App Tracking Transparency) opt-in rate monitored; <30% opt-in means heavy reliance on SKAN/AAK + privacy threshold
Privacy threshold awareness — low-volume campaigns may receive null postbacks; campaign consolidation recommended below 1k installs/week

Web Attribution (GA4 + Google Ads + Meta CAPI)

GA4 attribution model: Data-Driven (default for properties with enough data) vs Last-Click — confirm setting is intentional, not residue from a pre-2026 migration
Google Ads attribution model: Data-Driven default; per-conversion override allowed but audit any Last-Click overrides for justification
Cross-channel attribution in GA4: confirm Google Ads, Meta, LinkedIn, TikTok, Microsoft are integrated as platforms with consent + auto-tagging
Conversion windows per channel appropriate to sales cycle:
- E-commerce: 7-day click, 1-day view
- B2B / lead gen: 30-90 day click, no view
- SaaS subscription: 30 day click, 1-day view, plus offline conversion import for the activation event
Conversion lag analysis run quarterly to validate window choice

Consent Mode V2 (EU/EEA + recommended globally)

Consent Mode V2 active (enforcement began Jul 21, 2025 for EEA/UK)
Advanced Mode (not Basic) — Basic loses ~25% of EEA conversion signal
700+ ad clicks/day over 7 days per country/domain threshold met for Advanced Mode behavioral modeling to activate
Signal recovery measured: aim 15-25% conversion recovery vs pre-CMV2 baseline
Consent banner correctly reads CMV2 signals (not just GDPR boilerplate)

Server-Side Attribution Stitching

First-party server logs stored with user_id + event_id + timestamp
- platform tag for every conversion event
MMP + first-party stitching: MMP (AppsFlyer / Adjust / Branch / Singular) receives both client-side AND server-side events with shared event_id for deduplication
Server-side conversion import to Google Ads (offline conversion import) and Meta (CAPI) within 72h of the conversion event
Hash quality: email / phone fields SHA-256 hashed and lowercased before send; cross-platform hashing convention consistent
Deduplication rate ≥90% (matched event_id between client + server)

MMP Health (Mobile Apps)

MMP integrated — AppsFlyer / Adjust / Branch / Singular set up before any paid campaigns launched
Apple Ads connected as a partner in MMP dashboard
Post-install events sent back to Apple Ads, Google UAC, Meta App Campaigns, TikTok (enables Maximize Conversions and ROAS bidding)
Event quality: purchase, subscription_start, trial_start, or other revenue events tracked (not just install → registration)
Postback configuration: SKAN/AAK conversion values map to meaningful user actions

Cross-Device & Cross-Platform Attribution

Customer Match lists synced to Google Ads, Meta (Customer File CA), LinkedIn Matched Audiences, TikTok Customer File for cross-device stitching
Enhanced Conversions active for Google Ads (hashed first-party data, ~10% uplift on properly-implemented setups)
CAPI customer_information parameters (em, ph, fn, ln, ct, st, zp, external_id) sent server-side to Meta
Privacy-safe identifiers (Customer Match hashes, GAID/IDFA where permitted) included in conversion exports

Key Thresholds

Metric	Pass	Warning	Fail
GA4 attribution model	Data-Driven	Last-Click (intentional)	Last-Click (residual)
Consent Mode V2	Advanced + verified	Advanced (unverified)	Basic / Not implemented
EMQ (Meta Purchase)	≥8.0	6.0-7.9	<6.0
Event dedup rate	≥90%	70-89%	<70%
Server-side / client-side hit ratio	≥80%	50-79%	<50%
ATT opt-in (iOS)	≥30%	15-29%	<15% (heavy SKAN reliance)
Offline conversion import latency	<24h	24-72h	>72h
Customer Match list freshness	<7 days	7-30 days	>30 days

Output

Attribution Health Score

Attribution Health Score: XX/100 (Grade: X)

iOS (AdAttributionKit + ATT):    XX/100  ████████░░  (20%)
Web (GA4 + Ads + CAPI):           XX/100  ██████████  (30%)
Consent Mode V2:                  XX/100  █████████░  (15%)
Server-Side Stitching:            XX/100  ████████░░  (20%)
MMP Health (mobile):              XX/100  ███████░░░  (10%)
Cross-Device / Customer Match:    XX/100  ██████░░░░  (5%)

Deliverables

ATTRIBUTION-AUDIT.md: Full surface-by-surface findings
Cross-channel attribution map (which platform owns which conversion windows + which events)
Modeled vs reported conversion delta (estimated revenue under- or over-attribution)
Quick Wins sorted by signal-recovery $ impact
Pre-launch checklist for any new platform (Amazon, Apple Ads, TikTok) to ensure attribution is wired before spend begins

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