Lilly Tech Systems
AI Attribution Modeling
Understand which marketing touchpoints truly drive conversions. Master multi-touch attribution, data-driven models, incrementality testing, and marketing mix optimization powered by machine learning.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
Why attribution matters: the challenge of measuring marketing impact across channels and the evolution from simple to AI-driven models.
2. Multi-Touch Attribution
Rule-based multi-touch models: linear, time-decay, U-shaped, and W-shaped attribution across the customer journey.
3. Data-Driven Models
Markov chains, Shapley values, and algorithmic attribution that let the data determine touchpoint credit allocation.
4. Incrementality Testing
Causal inference, lift studies, geo experiments, and randomized controlled trials to measure true incremental marketing impact.
5. Marketing Mix Modeling
MMM with machine learning: budget optimization, channel synergy effects, and diminishing returns modeling.
6. Implementation
Building a unified measurement framework, privacy-safe attribution, and organizational adoption strategies.
What You'll Learn
By the end of this course, you'll be able to:
Measure Impact
Accurately attribute revenue to marketing touchpoints using data-driven models that go beyond last-click attribution.
Prove Incrementality
Design and run experiments that prove the true causal impact of your marketing spend on business outcomes.
Optimize Budgets
Allocate marketing budgets across channels based on predicted incremental returns and diminishing returns curves.
Build Frameworks
Implement a unified measurement approach that combines attribution, incrementality, and MMM for holistic marketing intelligence.