Applied Marketing Analytics: Machine Learning and Predictive Models for Improved Marketing

Marketing practice has evolved from being a highly qualitative field that is largely led by gut feelings and assumptions to one that is driven by data and models. In order for your marketing budget to be realized as an investment and not as an expense, you need to improve your data intelligence.

The Applied Marketing Analytics program is designed to be a career-defining next step for marketers and related roles who already work with analytics and strive to understand customers better, ask better questions, and ultimately make better marketing decisions.

This program will help you learn to measure what matters, sharpen your predictions, and drive marketing return on investment (ROI). You will be at the forefront of marketing practice by leveraging machine learning techniques to make better marketing investment decisions that will make an impact on your business - and your career.

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

Online Programs
High-Performance Marketing Communications

Create a successful advertising campaign based on a solid, effective strategy

Who Should Attend

  • Marketers drive business results through smarter targeting and conduct more meaningful, strategic discussions with analyst teams who want to
  • Business leads and consultants looking to implement machine learning predictions of customers and marketing to drive incremental business results and profits

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

Key Benefits

You will walk away with:
  • Hands-on experience with real-world data sets and advanced analytics tools for making more strategic, profitable decisions at your organization
  • An understanding of how predictive models work and which variables matter most for addressing the problems you are trying to solve and achieving your business goals
  • The confidence to engage in more productive conversations with data analysts and ask the right questions to drive enterprise-wide impact
  • Knowledge of the most common machine learning methods and how they are used to improve marketing models
  • The ability to leverage historical data to train and retrain models so that they are highly functional to grow your marketing effectiveness and your business

Faculty

Eric T Anderson - Polk Bros. Chair in Retailing; Professor of Marketing; Director Kellogg-McCormick MBAi

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

Program Content

Module 1: Understanding Your Data and Basic Predictions

To be an effective marketer today, you need to be able to extract value from the reams of data you have.
Build an understanding of the types of data the simulation organization has collected and how it can use this data to increase paying customers. Learn about variations in data, correlations between features, and how to predict how many users will convert in a campaign by using historical data.
- Segment customers through the lens of data
- Evaluate historical data for correlations between product features and conversions
- Make a basic prediction about customer behavior based on historical data

Module 2: Predictive Models and Desired Outcomes

Going beyond the historical data to grow your business, gain an introduction to how predictive models work. Learn different basic predictive models, when to use them, and how to interpret results. Experience the power of predictive models at finding customers who will buy.
- Identify users who are most likely to convert using a logistic regression model
- Determine which features are important for desired outcomes
- Use plots to visualize how each variable affects the predictions
- Learn a method to train, test, and evaluate model performance
 

Module 3: Machine Learning Tools for Segmenting and Targeting

Dive into more sophisticated models that will maximize the value of your data. Learn about several popular machine learning methods that are most relevant for marketing applications and how to assess which model is right for your business challenge.
- Understand the differences involved in supervised learning, unsupervised learning, and reinforcement learning
- Explore the benefits of using sophisticated machine learning models such as decision tree-based methods, bagging, boosting, random forests, and XGBoost
- Use the data dashboard and other tools to explore and interpret how different techniques can improve your ROI
 

Module 4: Machine Learning Models To Sharpen Your Strategy

Delve deeper into an advanced machine learning method: neural networks. Understanding multiple ways of predicting consumer outcomes will equip you to test models on your data and find the best fit for your business goals.
- Deepen your data IQ to evolve your conversations with data analysts
- Use a classic gameboard to experiment with the workings of neural networks
- Explore the data dashboard to compare models, make better predictions, and identify qualified leads
 

Module 5: Testing Models in the Real World: Link Analytics to Business Outcomes

Activate an advertising pilot and use the data dashboard to compare the results of the ad campaign with predictions made in earlier modules. After discovering how well your models and predictions performed, you will aim to improve them further by retraining the model through the pilot.
- Execute an advertising pilot and use the data dashboard to compare results with earlier module outcomes
- Understand the design of a data-driven advertising pilot and what capabilities are needed
 

Module 6: Incrementality: Identify Your Highest-Value Customers

By identifying your highest-value customers, you can optimize your ROI. 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 simulation: comparing the profitability derived from each model and exploring opportunities to improve marketing ROI.
- Gain exposure to sophisticated, marketing-applicable techniques: propensity modeling and uplift modeling
- Compare models to determine which one delivers the highest profitability and other key metrics
- Reflect on new opportunities to drive brand equity and improve marketing ROI at your organization

FAQ

What is the program about?

Applied Marketing Analytics: From Predictions to Profits offers leading-edge marketing practices that leverage machine learning techniques to make better marketing investment decisions. Let's eliminate the data gap to achieve and accurately measure marketing ROI.

 

What is the learning experience?

Your learning experience will consist of frameworks delivered via video lectures, live webinars, real world examples and case studies, application of frameworks through weekly activities, customized assignments and quizzes, discussion boards, and faculty engagement.

 

What is the program format?

The program consists of 6 modules delivered over 7 weeks online. Learners can expect to dedicate 4-6 hours per week to watch videos, complete assignments and participate in discussions. Modules are opened at the beginning of each week and have quizzes/assessments at the module’s conclusion. Learners may choose to engage with the program module all in one sitting or in smaller segments of time throughout the week. While the modules do not close, access to assignments is closed each week.

 

Could a learner choose to opt out of some topics?

No. This is an online program in which a topic module is introduced each week and the learner is expected to watch the video lectures, participate in the live webinars, complete the exercises/activities and take the self-study quiz at the end of each week to progress to the subsequent week’s topic.

 

Are any of the sessions delivered in real time (live)?

There will be live webinars, led by faculty and/or subject matter experts, delivered during the course of the program via a video conferencing platform. These sessions provide learners an opportunity to listen and ask questions; while they are valuable in enhancing the overall experience, attendance is not mandatory. All live sessions are recorded for later viewing.

 

What methods will be used for grading and evaluations?

Kellogg program leaders will review and give feedback on assignments, discussions and exercises to determine participants’ understanding of the material.

 

How much time is allocated to complete assignments?

The due date for submitting assignments is typically within 7 days of the module opening, but can be as long as 14 days, depending on the scope of the assignment. However, learners may request deadline extensions to accommodate business and personal conflicts that may arise during the program timeframe. Reach out to the program leader to discuss any challenges you may have in completing assignments.

 

Can participation in this program be counted as credit toward a degree, either at Kellogg, Northwestern University or another academic institution?

No. Executive Education offers only non-degree programs and each participant receives a certificate of completion at the end of the program. This certificate does not count as credit toward a degree. In addition, at this time, our online programs do not count as credit toward a Kellogg Executive Scholar Certificate.

 

Does the program offer community engagement for learners?

Yes, participants can create a profile, connect and collaborate with peers, and interact with academic/industry experts such as program leaders and teaching assistants. Office hours will be held during the program and all participants are welcome to join in with questions or to discuss assignments.

 

What are the requirements for accessing the program?

Participants will need the following to access the Customer Loyalty program:

  • Valid email address
  • Computing device connected to the internet (Mac/PC/laptop, tablet or smartphone)
  • The latest version of your preferred browser to access our learning platform (Chrome and Firefox are preferred for accessing Canvas)
  • Microsoft Office and PDF viewer to access content such as documents, spreadsheets, presentations, PDF files, and transcripts
  • Additional software and resources may be required for certain programs – this will be communicated upon registration and/or at the beginning of the program

PLEASE NOTE: Google, Vimeo and YouTube may be utilized in the program delivery

 

Does the program offer a certificate?

Yes. Participants will receive a digital certificate of completion from Kellogg following a successful conclusion to the program. Since this program is graded as a pass or fail, participants must receive an 80% to pass and obtain the certificate. This digital certificate can be shared with colleagues and posted on LinkedIn. (PLEASE NOTE: We do not provide reports of assessments, or “transcripts,” since this is a non-degree program.)

Who is Emeritus and what is their relationship with Kellogg Executive Education?

Kellogg Executive Education is partnering with Emeritus Institute of Management, an online education provider, to develop and deliver this program. By working with Emeritus, we are able to provide broader access to Executive Education, beyond our on-campus offerings, in a collaborative and engaging format that is consistent with Kellogg’s standard of quality.


Additional questions?

Please contact us by calling 847-467-6018 or email us at execedonline@kellogg.northwestern.edu.


2022 Session

November 10, 2022 - January 5, 2023

Start: November 17 at 12:00 AM

End: January 5 at 12:00 AM


Accepting registrations through November 16

$2,600

Kellogg School of Management

James L. Allen Center
2169 Campus Drive, Evanston, IL 60208
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847.467.6018