Overview:

Without customers, there is no business!

Managing Customers for Growth (MCG) focuses on how firms design and implement customer management activities to achieve sustainable customer growth. The course explores the fundamentals of customer value, including strategies for customer acquisition, retention, and development. By leveraging customer analytics tools and technologies, students will develop a data-driven approach to customer management. This course is relevant for students interested in marketing, growth strategy, customer experience, and data-driven decision-making.

(Syllabus from prior years: http://www.evaascarza.com/MCG_Syllabus_Fall2024.pdf)

Career Focus:

This course is particularly useful for students pursuing careers in roles where managing customer relationships and driving customer growth are central. This includes:

• Entrepreneurs and Business Leaders (e.g., CEOs, CMOs, Chief Growth Officers, Chief Customer Officers) seeking to build and scale customer-centric businesses.
• Consultants and Strategists advising companies on customer acquisition, retention, and monetization strategies.
• Investors and Analysts evaluating business growth trajectories and customer lifetime value.
• Product Managers and Marketing Professionals who need to understand customer segmentation, data-driven growth strategies, and personalized marketing interventions.

Educational Objectives:

This course provides students with frameworks, insights, and tools to successfully acquire, develop, and retain customers. Key learning objectives include:

1. Understanding and Measuring Customer Value: Students will learn foundational frameworks for assessing customer lifetime value (LTV), customer-base analysis, and cohort dynamics to inform strategic decision-making.
2. Leveraging Data for Customer Growth: The course explores how firms use data-driven insights for segmentation, personalization, and targeted interventions, as well as the ethical considerations of customer data use.
3. Executing Customer Management Strategies: Students will examine trade-offs in customer acquisition vs. retention, monetization strategies, and how to balance personalization with scale.
4. Developing Quantitative Intuition: Through hands-on exercises and workshops, students will strengthen their ability to translate customer data into strategic decisions and communicate effectively with data science teams.

Course Content and Organization:

The course is structured around three core modules, each addressing a key aspect of customer management:

Module 1: Measuring Customer-Driven Growth
Focuses on valuing customers, assessing customer-base dynamics, and measuring growth strategies. Students will analyze customer data and perform a Customer-Base Audit exercise to evaluate business health.
• Topics include: Customer lifetime value (LTV), customer valuation techniques, cohort analysis, and key metrics for growth measurement.

Module 2: Understanding Customers and Managing Growth
Explores customer segmentation, acquisition-retention trade-offs, and challenges in monetization. The module includes an exercise using clickstream data to create customer personas and growth strategies.
• Topics include: Acquisition vs. retention trade-offs, engagement-driven business models, customer segmentation, and monetization strategies.

Module 3: Managing Customers through Personalized Interventions
Covers personalization strategies, incrementality targeting, and ethical considerations in algorithmic decision-making. Students will explore real-world cases on AI-driven personalization and algorithmic bias.
• Topics include: Hyper-personalization, uplift modeling, fairness in AI-driven marketing, and customer data privacy.

The course concludes with a wrap-up session synthesizing key learnings.

Grading / Course Administration:

Student performance is assessed based on the following components:
• Class Participation (40%) – Engaged contribution to case discussions and in-class exercises.
• Three Short Quizzes (20%) – Assessing comprehension of key concepts throughout the course.
• Final Project (40%) – A customer management strategy project, completed individually or in pairs.

Technical skills are not required for this course. Workshops will include a data scientist to assist with technical aspects.

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