Marketing Analytics Mastery: From Strategy to Application Course Syllabus

Overview: This course is designed for marketers who want to master data-driven decision-making, from foundational metrics to advanced modeling. Over six modules, each requiring approximately 3-5 hours of work, you'll learn how to measure, analyze, and optimize marketing performance using real-world datasets. The course blends strategic frameworks with hands-on practice in Excel and basic statistical techniques, culminating in a final project that ties together analytics, visualization, and storytelling. Total time commitment: ~25-30 hours. Lifetime access allows for self-paced learning.

Module 1: Introduction to Marketing Analytics

Estimated time: 4 hours

• What is marketing analytics?
• Key terms and concepts
• Types of marketing data
• Setting up Excel for campaign tracking

Module 2: Descriptive Analytics & KPIs

Estimated time: 5 hours

• Understanding Customer Acquisition Cost (CAC)
• Calculating Customer Lifetime Value (LTV)
• Measuring ROI and conversion rates
• Working with real marketing datasets in Excel

Module 3: Predictive Analytics Techniques

Estimated time: 5 hours

• Introduction to regression analysis
• Forecasting campaign performance
• Churn modeling basics
• Running linear regression in Excel

Module 4: Customer Segmentation & Clustering

Estimated time: 5 hours

• RFM (Recency, Frequency, Monetary) analysis
• K-means clustering fundamentals
• Behavioral segmentation strategies
• Implementing clustering in Excel or Python

Module 5: Marketing Attribution & Mix Modeling

Estimated time: 5 hours

• First-touch vs. last-touch attribution
• Linear and time-decay attribution models
• Introduction to marketing mix modeling
• Evaluating multi-channel ROI

Module 6: Dashboarding & Data Storytelling

Estimated time: 6 hours

• Designing effective marketing dashboards
• Visualizing key metrics in Excel or Google Sheets
• Data storytelling techniques for stakeholders
• Final project: Build a comprehensive marketing performance dashboard

Prerequisites

• Familiarity with Microsoft Excel or Google Sheets
• Basic understanding of marketing concepts
• Some exposure to statistics is helpful but not required

What You'll Be Able to Do After

• Apply marketing measurement frameworks to real campaigns
• Analyze ROI and calculate key metrics like CAC and LTV
• Use regression and clustering techniques for predictive insights
• Build and present data-driven marketing dashboards
• Interpret attribution models to optimize channel spend