Customer Analytics Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview (80-120 words) describing structure and time commitment.
Module 1: Introduction to Customer Analytics
Estimated time: 1 hour
- Overview of customer analytics and its significance in modern business
- Understanding the role of data in shaping marketing strategies
- Introduction to course structure and learning objectives
Module 2: Descriptive Analytics
Estimated time: 2.5 hours
- Methods for collecting and interpreting customer data
- Identifying patterns in customer behavior
- Differentiating between causal and correlative data
Module 3: Predictive Analytics
Estimated time: 3 hours
- Techniques for forecasting future customer actions
- Application of regression analysis and probability models
- Selecting appropriate predictive tools for business scenarios
Module 4: Prescriptive Analytics
Estimated time: 2.5 hours
- Transforming data insights into actionable strategies
- Optimization methods for revenue and profit maximization
- Using analytics in pricing and advertising decisions
Module 5: Application/Case Studies
Estimated time: 2 hours
- Real-world examples of customer analytics in action
- Case studies from Amazon, Google, and Starbucks
- Effective data-driven strategies in practice
Module 6: Final Project
Estimated time: 2 hours
- Deliverable 1: Analyze a customer dataset using descriptive techniques
- Deliverable 2: Apply predictive modeling to forecast customer behavior
- Deliverable 3: Recommend prescriptive actions based on insights
Prerequisites
- Familiarity with basic business concepts
- No technical or programming background required
- Access to a web browser and Coursera account
What You'll Be Able to Do After
- Understand major methods of customer data collection and their business impact
- Interpret customer behavior patterns using descriptive analytics
- Apply predictive tools to forecast customer actions
- Develop data-driven strategies using prescriptive analytics
- Communicate key insights from customer analytics to support business decisions