In-Demand Supply Chain Management Skills to Boost Your Resume in 2025
January 6, 2025
Article
(6,403 reviews)
Recommended experience
Beginner level
No prior experience needed to participate in and benefit from this course.
(6,403 reviews)
Recommended experience
Beginner level
No prior experience needed to participate in and benefit from this course.
How to build and define a brand architecture and how to measure the impact of marketing efforts on brand value over time
How to measure customer lifetime value and use that information to evaluate strategic marketing alternatives
How to design basic experiments so that you can assess your marketing efforts and invest your marketing dollars most effectively
How to set up regressions, interpret outputs, explore confounding effects and biases, and distinguish between economic and statistical significance
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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, developed at the Darden School of Business at the University of Virginia, 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. You can follow my posts in Twitter, @rajkumarvenk, and on linkedin: https://www.linkedin.com/in/education-marketing. Thanks, Raj Professor of Business Administration at Darden
Welcome! We'll start with an overview of the marketing process and the transformational role of analytics. Then we'll walk through a case study. Ever heard of Airbnb? They're a powerhouse of the online community marketplace matching travelers to hosts. You'll see how they use analytics and the surprising results of their analyses.
10 videos2 readings3 assignments
Firms spend millions on branding for one reason: It allows them to charge more for their products and services. In this module, we'll explore this valuable, if intangible, asset. We'll discuss how to build and define a brand architecture and how to measure the impact of marketing efforts on brand value over time. By the end of this module, you'll be able to measure and track brand value. So let's get started!
12 videos3 assignments1 peer review2 discussion prompts
How valuable are your customers? That's a tough question that we'll show you how to answer in this module where we'll explore Customer Lifetime Value, or the future net value of a customer relationship. This forward-looking measure of the customer relationship helps you connect marketing strategies to future financial consequences and invest marketing dollars in the right place to maximize return over a customer's lifetime. By the end of this module, you will know how to measure customer lifetime value and evaluate strategic marketing alternatives based on whether they improve customer retention and lifetime value.
11 videos2 assignments2 discussion prompts
Ever wonder how much you have to cut prices to drive the most sales? Or which advertisement copy is more effective in customer conversion? Do an experiment! Experiments allow you to understand the effectiveness of different marketing strategies and forecast expected ROI. This week, we'll explore how to design basic experiments so that you can assess your marketing efforts and invest your marketing dollars most effectively. We'll help you avoid a gap between your test results and field implementation, and explore how web experiments can be implemented cheaply and quickly. By the end of this module, you'll be able to design and conduct effective experiments that test your marketing campaigns--and then use the results to make future marketing decisions.
13 videos3 readings4 assignments1 peer review
Ever wonder how variables influence consumer behavior in the real world--like how weather and a price promotion affect ice cream consumption? In this module, we will take a look at regression and how it's used to understand that relationship. We will discuss how to set up regressions and interpret outputs, explore confounding effects and biases, and distinguish between economic and statistical significance. We'll finish the week with a series of interviews with real marketing professionals who share their experiences and knowledge about how they use analytics on the job.
17 videos2 assignments1 discussion prompt
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
A premier institution of higher education, The University of Virginia offers outstanding academics, world-class faculty, and an inspiring, supportive environment. Founded by Thomas Jefferson in 1819, the University is guided by his vision of discovery, innovation, and development of the full potential of students from all walks of life. Through these courses, global learners have an opportunity to study with renowned scholars and thought leaders.
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Reviewed on May 21, 2020
This course was really very well designed and it will definitely help me to interpret the marketing data and analyse it in the right way.thanks to the instructor for making such a great course.
Reviewed on May 12, 2023
I enjoyed the lessons and they were challenging especially dealing with numbers and formulas, but that gave me assurance that Coursera offers reliable courses from recognized universities
Reviewed on Jul 12, 2022
It was comprehensive . but the explanaition for control group and test group as well as causality was very unclear to understand especially for me and u didnt explain some terms like these !thank you
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