• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Marketing Analytics

2020/2021
Academic Year
ENG
Instruction in English
3
ECTS credits
Course type:
Elective course
When:
1 year, 4 module

Instructor

Course Syllabus

Abstract

Organizations are in demand for information and data about consumer choices and need to translate these into decisions. Interpreting data is a challenge itself. Marketing analytics enables decision makers to measure, manage and analyze marketing performance to maximize its effectiveness and optimize return on investment (ROI). Marketing analytics can offer profound insights into customer preferences and trends, which can be further utilized for future marketing and business decisions. This course introduces tools to measure brand and customer assets, understand regression analysis, and design experiments as a way to evaluate and optimize marketing campaigns. The course is provied by Darden School of Business, University of Virginia. The full outline is here https://www.coursera.org/learn/uva-darden-market-analytics
Learning Objectives

Learning Objectives

  • Ability to understand econometric analysis
Expected Learning Outcomes

Expected Learning Outcomes

  • Skills for marketing experiments, customer lifetime analysis, marketing analytics, brand equity
  • Econometric skills, regression analysis
Course Contents

Course Contents

  • The Marketing Process
    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.
  • Metrics for Measuring Brand Assets
    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!
  • Customer Lifetime Value
    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.
  • Marketing Experiments
    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.
  • Regression Basics
    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.
Assessment Elements

Assessment Elements

  • non-blocking Essay
  • non-blocking Final oral group examination
    The Exam is planned as an ORAL GROUP EXAMINATION, online on ZOOM Platform. A Student should log in 20 minutes prior to Exam Session. Temporary internet breakdown is for up to 10 min. If longer - a written request to the course director, cc study office manager for further decision to reschedule the Exam for another date for examination: with different exam questions.
  • non-blocking Essay
  • non-blocking Final oral group examination
    The Exam is planned as an ORAL GROUP EXAMINATION, online on ZOOM Platform. A Student should log in 20 minutes prior to Exam Session. Temporary internet breakdown is for up to 10 min. If longer - a written request to the course director, cc study office manager for further decision to reschedule the Exam for another date for examination: with different exam questions.
Interim Assessment

Interim Assessment

  • Interim assessment (4 module)
    0.3 * Essay + 0.7 * Final oral group examination
Bibliography

Bibliography

Recommended Core Bibliography

  • Wedel, M., & Kannan, P. K. (2016). Marketing Analytics for Data-Rich Environments. Journal of Marketing, 80(6), 97–121. https://doi.org/10.1509/jm.15.0413

Recommended Additional Bibliography

  • Germann, F., Lilien, G. L., & Rangaswamy, A. (2013). Performance implications of deploying marketing analytics. International Journal of Research in Marketing, (2), 114. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.eee.ijrema.v30y2013i2p114.128