Marketing Analytics: Data-Driven Decisions
Learn to measure marketing performance, analyze customer value, and design experiments. Master tools for data-driven marketing decisions.
Learn to measure marketing performance, analyze customer value, and design experiments. Master tools for data-driven marketing decisions.
This course, developed by the Darden School of Business at the University of Virginia, equips marketers with essential analytics tools to measure and optimize marketing performance. Participants learn to leverage data for informed decision-making across various marketing aspects. The curriculum covers key topics such as brand asset measurement, customer lifetime value calculation, marketing experiment design, and regression analysis. Through case studies, hands-on exercises, and real-world examples, learners gain practical skills in interpreting data, evaluating marketing strategies, and maximizing return on investment (ROI). The course also features insights from industry professionals, providing a bridge between academic concepts and real-world applications.
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What you'll learn
Understand the transformational role of analytics in marketing
Build and measure brand architecture and brand value
Calculate and utilize customer lifetime value for strategic decisions
Design and analyze marketing experiments to optimize campaigns
Use regression analysis to understand consumer behavior and marketing effectiveness
Interpret data to make informed marketing decisions
Skills you'll gain
This course includes:
4.5 Hours PreRecorded video
14 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This course provides a comprehensive introduction to marketing analytics, focusing on leveraging data for effective decision-making in marketing. Over five modules, learners explore various aspects of data-driven marketing strategies. The course begins with an overview of the marketing process and the role of analytics, using Airbnb as a case study. It then delves into metrics for measuring brand assets, teaching students how to build brand architecture and calculate brand value. The third module covers customer lifetime value (CLV), enabling learners to evaluate marketing strategies based on long-term customer relationships. The fourth module focuses on designing and analyzing marketing experiments to assess campaign effectiveness. The final module introduces regression analysis for understanding consumer behavior and marketing mix modeling. Throughout the course, real-world examples, case studies, and interviews with marketing professionals provide practical context for the analytical concepts covered.
Leveraging User Generated Content
Module 1 · 2 Hours to complete
Metrics for Measuring Brand Assets
Module 2 · 4 Hours to complete
Customer Lifetime Value
Module 3 · 2 Hours to complete
Marketing Experiments
Module 4 · 4 Hours to complete
Regression Basics
Module 5 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructor
Rajkumar Venkatesan, Ronald Trzcinski Professor of Business Administration at the University of Virginia
Rajkumar Venkatesan is a Professor of Business Administration at the Darden Business School, University of Virginia, specializing in the intersection of AI, digital strategy, marketing, and analytics. He has authored two influential books, Cutting Edge Marketing Analytics and AI Marketing Canvas, and has published numerous case studies and peer-reviewed articles. Venkatesan engages with MBA and corporate executive students globally through courses such as marketing analytics, digital marketing, and AI in marketing. He developed the innovative MBA/MSDS dual degree program and the popular tech immersion course in San Francisco. As the Academic Director for the AI Initiative and the Master of Science in Business Analytics degree at UVA, he consults with enterprises across various industries to address strategic challenges through analytics. His contributions include developing tools like the Marketing Analytics Canvas and the AI Marketing Canvas to enhance collaboration among marketers and analytics teams.
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4.7 course rating
6,372 ratings
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