Applied Marketing Analytics: From Predictions to Profits

Achieving measurable impact for marketers and brand managers

Get Your Brochure

Course Dates

STARTS ON

March 9, 2022

Course Duration

DURATION

6 weeks, online
4–6 hours per week

Course Duration

PROGRAM FEE

US$2,600 US$2,210 or get US$260 off with a referral

Course Information Flexible payment available

Invest in Yourself in 2022

This new year, Kellogg Executive Education in partnership with Emeritus is offering 15% tuition assistance on this online program to set you up for professional success. Enroll before January 25, 2022, 04:00 PM PST to get this benefit.

Application Details

Round 1

US$2,210 / program fee

Application Deadline
1

Improve Your Data Intelligence and Boost Your Marketing ROI

Understanding your customers and key market dynamics is a given for marketing professionals. But could machine learning and analytics techniques lead to nonlinear gains in your marketing efforts? In order to find out, you need to improve your data intelligence.

You don't need to become a data scientist, but you do need to have more productive conversations with data specialists and understand the fundamental principles that allow you to convert data into insights. Even if you don't work with data specialists, advancing your data intelligence can add tremendous value to your organization.

26% Increase

The use of AI and machine learning methods in enterprises is predicted to grow from 12% in 2021 to 38% over the next three years.

(Source: THE CMO SURVEY, DUKE UNIVERSITY’S FUQUA SCHOOL OF BUSINESS & DELOITTE)

98.1% Gap

Businesses have reported a near-universal marketing analytics talent gap. Only 1.9% of marketing leaders reported that their companies have the right talent to leverage marketing analytics.

(Source: Gartner CMO Survey)

Who Is This Program For?

  • Marketing managers, both traditional and digital, who want to analyze the return on investment (ROI) on their marketing investments and increase their data intelligence to make more profitable decisions
  • Business and product managers working closely with marketing and analytic functions to advance business objectives
  • Analysts and data science specialists who want to better understand the techniques that can benefit marketing departments the most

While there are no specific prerequisites for this program, familiarity with basic statistics is important.

You Will Walk Away With:

  • A tangible experience of how to make more strategic, profitable decisions through data analysis
  • An understanding of how predictive models work and which variables matter most for reaching the desired outcomes
  • The confidence to engage in more productive conversations with data analysts and ask the right questions to drive enterprise-wide impact
  • Clear knowledge of machine learning methods and how they are used to improve models and make marketing decisions
  • The ability to leverage historical data to inform predictive models in marketing practice
  • Applications of the program’s principles to your own business challenge

Program Experience

Decorative image relating to live and recorded sessions with program faculty

Live and recorded sessions with program faculty

Decorative image relating to highly experiential approach using a data dashboard for accessing and analyzing proprietary datasets from Kellogg

Highly experiential approach using a data dashboard for accessing and analyzing proprietary datasets from Kellogg

Decorative image relating to personalized feedback on application exercises

Personalized feedback on application exercises

Decorative image relating to global peer network of collaborators

Global peer network of collaborators

Decorative image relating to live office hours with program leaders

Live office hours with program leaders 

Decorative image relating to Mobile learning app

Mobile learning app 

Program Modules

Program Simulation Case
A fictional company, Creative Gaming, wants to increase sales for its highly successful mobile game, Space Pirates. The case plays out much like a simulation in six chapters. The company’s data repository, which we call the CG dashboard, is introduced in Module 1 and is used as the linchpin for this experiential learning journey.  

Module 1:

Understanding Your Data

You will become familiar with the situational learning narrative and proprietary tools associated with the Creative Gaming case study, such as the CG dashboard. Engage in discussion about the case objective and identify a challenge you want to pursue with data analytics at your own organization.

Module 2:

Predictive Models

Test drive different models that help to predict paid customer conversions for the Creative Gaming case, then evaluate their relative performance.

Module 3:

Better Models, Better Predictions Part 1

Learn about several popular machine learning methods that are most relevant for marketing applications and the fundamentals of how to define and organize the data. This module is about developing an understanding of how these models work, not about building any particular model.

Module 4:

Better Models, Better Predictions Part 2

Delve deeper into a more advanced machine learning method: neural networks. Compare how well these more advanced models perform against the benchmark logistic regression model.

Module 5:

Testing Models in the Real World

Activate an advertising pilot and use the CG dashboard to compare the results of the ad campaign with predictions made in earlier modules.

Module 6:

Incrementality

Calculate both regular profits and incremental profits by employing two different (but equally cutting-edge) models: propensity modeling and uplift modeling. You will experience the final twist in the Creative Gaming narrative, compare the profitability derived from each model, and explore opportunities to improve marketing ROI.

Module 1:

Understanding Your Data

You will become familiar with the situational learning narrative and proprietary tools associated with the Creative Gaming case study, such as the CG dashboard. Engage in discussion about the case objective and identify a challenge you want to pursue with data analytics at your own organization.

Module 4:

Better Models, Better Predictions Part 2

Delve deeper into a more advanced machine learning method: neural networks. Compare how well these more advanced models perform against the benchmark logistic regression model.

Module 2:

Predictive Models

Test drive different models that help to predict paid customer conversions for the Creative Gaming case, then evaluate their relative performance.

Module 5:

Testing Models in the Real World

Activate an advertising pilot and use the CG dashboard to compare the results of the ad campaign with predictions made in earlier modules.

Module 3:

Better Models, Better Predictions Part 1

Learn about several popular machine learning methods that are most relevant for marketing applications and the fundamentals of how to define and organize the data. This module is about developing an understanding of how these models work, not about building any particular model.

Module 6:

Incrementality

Calculate both regular profits and incremental profits by employing two different (but equally cutting-edge) models: propensity modeling and uplift modeling. You will experience the final twist in the Creative Gaming narrative, compare the profitability derived from each model, and explore opportunities to improve marketing ROI.

Download Brochure

Program Faculty

Profile picture of programme faculty, ERIC T. ANDERSON

Eric T. Anderson

Polk Bros. Chair in Retailing; Professor of Marketing; Director, Kellogg-McCormick MBAi Program

Professor Anderson's research interests include analytics, retailing, pricing strategy, innovation, new products, and channel management. His recent research has been conducted with various companies around the world and has impacted both management practice and academic theory... More info

Profile picture of programme faculty, FLORIAN ZETTELMEYER

Florian Zettelmeyer

Nancy L. Ertle Professor of Marketing; Faculty Director, Program on Data Analytics at Kellogg

Professor Zettelmeyer specializes in evaluating the effects of information technology and big data on firms. More generally, his work addresses how the information consumers have about firms and the information firms have about consumers affect firm behavior.... More info

Certificate

Example image of certificate that will be awarded after successful completion of this program

Certificate

Upon successful completion of the program, Kellogg Executive Education grants a verified digital certificate of completion to participants. This program is graded as pass or fail; participants must receive 80 percent to pass and obtain the certificate of completion.

Download Brochure

After successful completion of the program, your verified digital certificate will be emailed to you in the name you used when registering for the program. All certificate images are for illustrative purposes only and may be subject to change at the discretion of Kellogg Executive Education.

Note: This online certificate program does not grant academic credit or a degree from Kellogg School of Management.

Apply Now

Early registrations are encouraged. Seats fill up quickly!

Flexible payment options available. Learn more.