Marketing & GrowthBusinessPlatinum

Analyze marketing channel effectiveness across customer journeys.

Multi-Touch Attribution Analyst

Shapley, MMM, Privacy, Incrementality

expertv5.0

Best for

▸Designing Shapley value attribution models for multi-channel B2B campaigns with 6+ month sales cycles
▸Implementing Marketing Mix Modeling (MMM) to measure incrementality of brand awareness channels like podcasts and billboards
▸Building privacy-compliant attribution frameworks using server-side tracking and first-party data signals
▸Creating geo-experiment designs to validate incremental lift from paid social and search campaigns

What you'll get

▸Statistical framework comparison (Shapley vs Markov chain vs MMM) with data volume requirements and implementation complexity for specific business context
▸Technical architecture diagram showing data collection, identity resolution, model training, and incrementality validation components
▸Geo-experiment design with control/treatment allocation, sample size calculations, and statistical significance testing protocols

Expects

Marketing channel mix details, conversion goals, data infrastructure capabilities, privacy constraints, and typical customer journey patterns with conversion volumes.

Returns

Statistical attribution framework recommendations with implementation architecture, data requirements, model selection rationale, and incrementality testing protocols.

What's inside

“You are a Multi-Touch Attribution Analyst. You diagnose marketing measurement problems and design attribution frameworks that combine multiple approaches (tactical MTA, strategic MMM, and causal validation) to balance optimization with rigor. - **Reject single-model thinking.** You recognize that la...”

Covers

What You Do DifferentlyMethodologyWatch For

Not designed for ↓

×Basic last-click attribution setup in Google Analytics (use ga4-analytics-expert instead)
×Social media content creation or ad creative optimization
×Simple campaign performance reporting without statistical modeling
×Email marketing automation or lifecycle campaign design

SupaScore

89.08▼

Research Quality (15%)

9.1

Prompt Engineering (25%)

8.95

Practical Utility (15%)

8.55

Completeness (10%)

9.3

User Satisfaction (20%)

8.9

Decision Usefulness (15%)

8.75

Evidence Policy

Standard: no explicit evidence policy.

attributionmulti-touch-attributionmarketing-analyticsmarketing-mix-modelingincrementalityshapley-valuecross-channelroasbudget-allocationprivacy-measurementga4conversion-tracking

Research Foundation: 8 sources (4 official docs, 2 academic, 2 industry frameworks)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.