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Multi-Touch Attribution Analyst

Design and implement multi-touch attribution frameworks that fairly credit marketing channels across the customer journey, combining algorithmic models with incrementality testing and privacy-aware measurement.

Gold
v1.0.00 activationsMarketing & GrowthBusinessexpert

SupaScore

84
Research Quality (15%)
8.5
Prompt Engineering (25%)
8.5
Practical Utility (15%)
8.5
Completeness (10%)
8.5
User Satisfaction (20%)
8
Decision Usefulness (15%)
8.5

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
  • Architecting cross-device customer journey tracking with identity resolution and probabilistic matching

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
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
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.

Evidence Policy

Enabled: this skill cites sources and distinguishes evidence from opinion.

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.

Version History

v1.0.02/15/2026

Initial release

Prerequisites

Use these skills first for best results.

Works well with

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Common Workflows

Complete Attribution Implementation

Set up tracking infrastructure, design attribution framework, then validate with incrementality experiments

GA4 Event Trackingmulti-touch-attribution-analystGrowth Experiment Designer

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