Data, Analytics and AI for Marketing Strategy

The course Data, Analytics and AI for Marketing Strategy introduces students to the principles and methods of data-driven marketing decision-making. The course emphasizes how data, analytics, and artificial intelligence can support strategic marketing decisions—from understanding customer behavior and optimizing marketing investments to developing effective pricing strategies and driving profitability.

Students will explore essential concepts such as customer segmentation, customer lifetime value, acquisition, retention, marketing effectiveness, and revenue optimization, while also examining how emerging technologies like machine learning, generative AI, and AI agents are transforming marketing strategy. Through real-world cases, practical exercises, and hands-on labs, students will learn to critically evaluate analytical insights, assess the impact of marketing activities, and translate data into actionable strategic recommendations.

The course is split into fourteen lecture units:

Part A – Foundations of Data-Driven Marketing Strategy

01 – Marketing Decision Architecture
02 – Data, Measurement & Causal Identification

Part B – Customer & Market Intelligence

03 – Segmentation for Strategic Targeting
04 – Customer Lifetime Value & Investment Decisions
05 – Customer Acquisition, Retention & Churn Analytics
06 – Cross-Selling & Recommendation Decisions

Part C – Marketing Effectiveness & Resource Allocation

07 – Marketing Mix Modeling & Budget Allocation
08 – Advertising Response & Media Effectiveness

Part D – Pricing, Demand & Revenue Optimization

09 – Demand & Price Elasticity Modeling
10 – Choice Models & Competitive Substitution
11 – Revenue & Profit Optimization

Part E – Autonomous & AI-Augmented Marketing Decisions

12 – Machine Learning for Marketing Decisions
13 – AI Agents & Reinforcement Learning in Marketing
14 – Generative AI & Marketing Intelligence