Кто читает:: Кафедра инноваций и бизнеса в сфере информационных технологий

Статус:: Курс по выбору

Когда читается:: 3-й курс, 4 модуль

Преподаватель

Дмитриев Виктор Андреевич

Full Syllabus

Abstract

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.

Learning Objectives

Ability to build and define a brand architecture and how to measure the impact of marketing efforts on brand value over time
Ability to design basic experiments so that you can assess your marketing efforts and invest your marketing dollars most effectively
Ability to measure customer lifetime value and use that information to evaluate strategic marketing alternatives
Ability to set up regressions, interpret outputs, explore confounding effects and biases, and distinguish between economic and statistical significance

Expected Learning Outcomes

to define a brand architecture
to measure and track brand value
to measure customer lifetime value
to evaluate strategic marketing alternatives based on whether they improve customer retention and lifetime value
Skills for marketing experiments, customer lifetime analysis, marketing analytics, brand equity
Econometric skills, regression analysis
to set up regressions and interpret outputs

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

on-line tests
LMS-test exam
The duration of the exam is 90 minutes

Interim Assessment

Interim assessment (4 module)
0.4 * LMS-test exam + 0.6 * on-line tests

Bibliography

Recommended Core Bibliography

Venkatesan, R. (2014). Cutting Edge Marketing Analytics : Real World Cases and Data Sets for Hands On Learning. Upper Saddle River, N.J.: Pearson FT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1600652
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

Charan, A. (2015). Marketing Analytics : A Practitioner’s Guide to Marketing Analytics and Research Methods. Singapore: World Scientific Publishing Company. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1001262
Grigsby, M. (2015). Marketing Analytics : A Practical Guide to Real Marketing Science. London: Kogan Page. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1000089

Бакалаврская программа «Бизнес-информатика»

Контакты

Marketing Analytics