Marketing Analytics Course

Lesson 1 • What Marketing Analytics Means

Defines marketing analytics and distinguishes it from general business analytics. Establishes the scope and vocabulary used throughout the course.

Lesson 2 • Core Marketing Metrics and KPIs

Introduces the most critical marketing performance indicators and their formulas. Connects metric selection to specific business objectives.

Lesson 3 • The Analytics Workflow

Outlines the end-to-end process from business question to actionable insight. Provides a repeatable framework applied in every subsequent chapter.

Lesson 1 • Tracking and Tagging Fundamentals

Explains how digital tracking technologies capture user behavior across channels. Directly enables accurate data collection for all downstream analysis.

Lesson 2 • Data Integration Across Channels

Covers methods for combining data from multiple marketing platforms into a unified view. Resolves the fragmentation problem that distorts cross-channel analysis.

Lesson 3 • Privacy and Consent in Data Collection

Addresses consumer privacy principles and consent frameworks that govern marketing data use. Ensures analytical practices remain ethical and compliant.

Lesson 1 • Exploratory Data Analysis for Marketers

Applies statistical summaries and visualizations to uncover patterns in marketing datasets. Builds the habit of interrogating data before drawing conclusions.

Lesson 2 • Segmentation and Cohort Analysis

Groups customers by shared attributes or behavior to reveal differences in performance. Cohort analysis tracks how groups evolve over time.

Lesson 3 • Building Marketing Dashboards

Covers dashboard design principles and tool selection for ongoing performance monitoring. Connects visualization choices to the decisions dashboards must support.

Lesson 1 • Churn Prediction and Retention Analytics

Builds models that identify customers at risk of leaving before they disengage. Enables proactive retention campaigns grounded in data.

Lesson 2 • Behavioral Clustering Techniques

Uses unsupervised machine learning to group customers by behavioral similarity without predefined labels. Reveals natural audience segments for targeting.

Lesson 3 • Customer Journey Mapping with Data

Uses behavioral event data to reconstruct the paths customers take from awareness to purchase. Identifies friction points and optimization opportunities.

Lesson 1 • Multi-Touch Attribution in Practice

Applies attribution models to real campaign data and reconciles conflicting channel signals. Produces actionable budget reallocation recommendations.

Lesson 2 • Attribution Model Fundamentals

Compares rule-based attribution models and explains the assumptions behind each. Establishes why model choice materially changes budget decisions.

Lesson 3 • Incrementality and Lift Testing

Measures the true causal lift of a campaign by comparing exposed and unexposed groups. Distinguishes correlation from causation in campaign measurement.

Lesson 1 • Interpreting and Acting on Results

Translates statistical outputs into business decisions and documents learnings for future tests. Closes the loop between experimentation and strategy.

Lesson 2 • Running A/B and Multivariate Tests

Walks through the operational steps of launching and monitoring live experiments. Covers both simple A/B and more complex multivariate designs.

Lesson 3 • Statistical Foundations for Testing

Covers the statistical concepts required to interpret A/B test results correctly. Builds on descriptive analytics from Chapter 3 to add inferential reasoning.

Lesson 1 • Regression Models for Marketing Forecasting

Uses linear and logistic regression to predict continuous and binary marketing outcomes. Extends the statistical foundation built in the experimentation chapter.

Lesson 2 • Classification Models for Propensity Scoring

Builds models that score each customer's likelihood to convert, churn, or respond. Propensity scores directly feed targeting and personalization strategies.

Lesson 3 • Demand Forecasting and Budget Planning

Applies time-series and regression methods to forecast sales volume and marketing demand. Outputs feed directly into budget allocation decisions.

Lesson 1 • Budget Optimization Techniques

Uses MMM outputs to find the spend allocation that maximizes revenue within budget constraints. Directly answers the core marketing investment question.

Lesson 2 • Communicating MMM Insights to Leadership

Translates complex model outputs into executive-ready narratives and investment recommendations. Applies the storytelling skills from Chapter 3 at a strategic level.

Lesson 3 • Building and Calibrating an MMM

Walks through model specification, estimation, and calibration against known results. Produces a validated model ready for optimization.