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There are 4 modules in this course
This course introduces students to marketing analytics as a data-driven approach to solving real-world marketing problems. It covers four key areas: causal analysis (identifying cause-and-effect in marketing interventions), predictive modeling and AI (forecasting customer behaviors using machine learning), social media analysis (extracting insights from online consumer interactions through text and network analysis), and consumer demand and preference analysis (estimating preferences, demand, and customer lifetime value). Students will gain hands-on experience using Python to analyze diverse data sources, apply advanced analytics techniques, and generate actionable insights to support strategic marketing decisions.
In the first module, we will discuss analytics in marketing and delve into causal analysis, a crucial tool for analytics. We will begin with a comprehensive overview of why analytics is crucial for marketers, including the various types of data, the process of applying analytics in marketing, and the different types of analytics. We will then delve deeper into causal analysis.
Online Education at Gies College of Business•10 minutes
Updating Your Profile•10 minutes
Module 1 Overview•10 minutes
Module 1 Readings and Demonstration Files•90 minutes
2 assignments•Total 60 minutes
Module 1 Graded Quiz•30 minutes
Orientation Quiz•30 minutes
1 discussion prompt•Total 10 minutes
Getting to Know Your Classmates•10 minutes
1 plugin•Total 15 minutes
Welcome! Please Tell Us About Yourself•15 minutes
Module 2: Artificial Intelligence, Prediction, and Machine Learning
2 hours to complete
Module details
In this module, we explore how Artificial Intelligence (AI) and Machine Learning (ML) are transforming marketing practices—from predicting customer behavior to enabling hyper-personalization at scale. We’ll examine the fundamentals of prediction, how to build machine learning models, and how advances in tools like Large Language Models (LLMs) are unlocking new capabilities in areas such as segmentation, market research, and customer retention. You’ll also learn about the tradeoffs and ethics of AI deployment, including bias, transparency, and privacy considerations.
What's included
8 videos2 readings1 assignment
Show info about module content
8 videos•Total 67 minutes
Intro to ML and AI•12 minutes
Foundational Principles of ML•10 minutes
Prediction Case - Geotracking•6 minutes
AI for Market Research•5 minutes
Prediction and Causality Combined•7 minutes
Ethics in AI Use•10 minutes
Application: Artificial Intelligence, Prediction, and Machine Learning•4 minutes
Python Demonstration: Artificial Intelligence, Prediction, and Machine Learning•13 minutes
2 readings•Total 27 minutes
Module 2 Overview•20 minutes
Module 2 Readings and Demonstration Files•7 minutes
1 assignment•Total 30 minutes
Module 2 Graded Quiz•30 minutes
Module 3: User, Firm, and AI-Generated Content Analysis
5 hours to complete
Module details
In this module, we explore how to make sense of the vast amounts of unstructured content that users and companies generate online—from product reviews and social media posts to Q&A threads and firm-generated promotions. You’ll learn how to pre-process text, extract insights using tools like sentiment analysis and topic modeling, and perform social network analysis to understand influence and engagement. We also examine how different types of content—user-generated, firm-generated, and AI-generated—shape brand perceptions and drive consumer behavior, while also discussing ethical challenges such as misinformation, bias, and fake reviews.
What's included
11 videos2 readings1 assignment1 peer review
Show info about module content
11 videos•Total 119 minutes
Intro to Online Content in Marketing Analytics•8 minutes
Text Analysis - A Historical Perspective•10 minutes
Types of Content•7 minutes
UGC - Deep Dive into Concepts•10 minutes
FGC Deep Dive into Concepts•9 minutes
AGC Deep Dive Into Concepts•7 minutes
Online Content and Emerging Concerns•8 minutes
Influencer Marketing Introduction•8 minutes
Application: User, Firm, and AI-Generated Content Analysis•4 minutes
Python Demonstration: User, Firm, and AI-Generated Content Analysis•11 minutes
Interview with Kate Lyons•38 minutes
2 readings•Total 50 minutes
Module 3 Overview•20 minutes
Module 3 Readings and Demonstration Files•30 minutes
1 assignment•Total 30 minutes
Module 3 Quiz•30 minutes
1 peer review•Total 120 minutes
User, Firm, and AI-Generated Content Analysis: Peer Review Assignment•120 minutes
Module 4: Customer Preferences and Lifetime Value Analysis
3 hours to complete
Module details
This module introduces data-driven tools for understanding consumer preferences and forecasting demand. You'll learn how to segment customers, assess their long-term value, and apply choice modeling techniques like conjoint analysis to evaluate which product features matter most. We also cover customer lifetime value (CLV), how to calculate it, and how it guides investment in acquisition and retention. The module highlights the growing importance of incrementality in churn prediction and campaign evaluation.
What's included
8 videos4 readings1 assignment1 plugin
Show info about module content
8 videos•Total 53 minutes
Intro to CLV and Customer Demand•5 minutes
Segmentation, Targeting, and Positioning•8 minutes
Conjoint Analysis•7 minutes
Intro to CLV Analysis - 1•7 minutes
Intro to CLV Analysis Example - 2•7 minutes
Understanding Customer Churn and Incrementality•8 minutes
Python Demonstration: Customer Preferences and Lifetime Value Analysis•11 minutes
Learn on Your Terms•1 minute
4 readings•Total 70 minutes
Module 4 Overview•20 minutes
Module 4 Readings and Demonstration Files•30 minutes
Congratulations on Completing the Course!•10 minutes
Get Your Course Certificate•10 minutes
1 assignment•Total 30 minutes
Module 4 Graded Quiz•30 minutes
1 plugin•Total 15 minutes
End of Course survey•15 minutes
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Build toward a degree
This course is part of the following degree program(s) offered by University of Illinois Urbana-Champaign. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
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Build toward a degree
This course is part of the following degree program(s) offered by University of Illinois Urbana-Champaign. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
¹Successful application and enrollment are required. Eligibility requirements apply. Each institution determines the number of credits recognized by completing this content that may count towards degree requirements, considering any existing credits you may have. Click on a specific course for more information.
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Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What is the refund policy?
You will be eligible for a full refund until 2 weeks after your payment date. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the 2-week refund period. View our full refund policy.
Is financial aid available?
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What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.