What you'll learn
The Marketing Process
Metrics for Measuring Brand Assets
Customer Lifetime Value
Marketing Experiments
Regression Basics
Description
Organizations large and small are inundated with data about consumer choices. But that wealth of information does not always translate into better decisions. Knowing how to interpret data is the challenge – and marketers in particular are increasingly expected to use analytics to inform and justify their decisions. Marketing analytics enables marketers to measure, manage and analyze marketing performance to maximize its effectiveness and optimize return on investment (ROI).
Beyond the obvious sales and lead generation applications, marketing analytics can offer profound insights into customer preferences and trends, which can be further utilized for future marketing and business decisions. This course gives you the tools to measure brand and customer assets, understand regression analysis, and design experiments as a way to evaluate and optimize marketing campaigns. You’ll leave the course with a solid understanding of how to use marketing analytics to predict outcomes and systematically allocate resources. For more information on marketing analytics, you may visit; http://dmanalytics.org. You can also follow my posts in Twitter, @rajkumarvenk, and on linkedin; www. linkedin.com/in/rajkumar-venkatesan-14970a3.
Requirements
Access to a computer or mobile device with an internet connection.
Motivation to learn!
There are no special materials or prerequisite knowledge required for this course.
Who this course is for
Students who are new to this field
Students willing to put in a couple hours to learn about Marketing Analytics
Advanced students wanting to add another skill to their portfolio
Content Creator
Rajkumar Venkatesan – Ronald Trzcinski Professor of Business Administration – Darden School of Business
This course includes
Participation Confirmation/Certificate
Option for learning at your own pace
Videos and reading material about the course
Practice tests
Assessed tasks with feedback from other course participants
Evaluated tests with feedback
Evaluated programming tasks
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