Marketing Analytics Foundation Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This beginner-friendly course introduces the core concepts of marketing analytics and equips learners with the skills to make data-driven marketing decisions. Over four weeks, you'll explore key metrics, customer behavior, and decision-making frameworks used in modern marketing. Each module combines foundational knowledge with hands-on exercises using real-world datasets and simple spreadsheet tools. With a total time commitment of approximately 16 hours, this course is ideal for anyone looking to start or transition into a marketing analytics role.
Module 1: Introduction to Marketing Analytics
Estimated time: 4 hours
- What is marketing analytics?
- Understanding data-driven marketing
- Business applications of marketing analytics
- Reviewing case studies on analytics-driven decisions
Module 2: KPIs and Metrics in Marketing
Estimated time: 4 hours
- Understanding conversion rates
- Measuring return on investment (ROI)
- Impressions, reach, and engagement metrics
- Calculating and interpreting marketing metrics using spreadsheets
Module 3: Understanding Customer Behavior
Estimated time: 4 hours
- Mapping the customer journey
- Customer acquisition strategies
- Retention and loyalty metrics
- Calculating customer lifetime value
Module 4: Data-Driven Decision Making
Estimated time: 4 hours
- Introduction to A/B testing
- Building and using analytics dashboards
- Basics of predictive modeling in marketing
Prerequisites
- Familiarity with basic marketing concepts
- Basic spreadsheet skills (e.g., Excel or Google Sheets)
- No prior analytics or programming experience required
What You'll Be Able to Do After
- Explain core marketing analytics concepts and their business impact
- Measure and optimize marketing campaign performance using data
- Interpret key metrics such as ROI, conversion rates, and customer lifetime value
- Analyze customer behavior to identify profitable segments
- Use dashboards and basic models to support data-driven marketing decisions