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Predictive Analytics for Marketing

Decipher patterns to unlock unparalleled marketing success.

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Predictive analytics

At a Glance

Enrollment:
Open Enrollment
Length:
8 weeks
Format:
Online
Total CEUs:
5.3 CEUs
Investment:
$2,800
Also offered in:

Learn and apply analytic techniques to measure and improve marketing performance.

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The University of Chicago’s online Predictive Analytics for Marketing course teaches you how to analyze data, gauge campaign effectiveness, segment and size markets, and use predictive modeling to forecast customer lifetime value. Additionally, its holistic approach will enable marketing and sales teams to create better and more effective marketing campaigns, execute cross-selling and upselling more efficiently, and provide improved customer relations.

Designed For

Designed for professionals interested in advancing their analytical acumen within the marketing discipline, this course will benefit practicing and prospective marketers, managers, and other leaders looking to leverage analytic techniques to measure and improve marketing performance.

Learning Objectives to Become an Expert in Marketing-Applied Predictive Analytics

This course focuses on optimal data analysis and predictive modeling. Over eight weeks, you will acquire the tools to extract insights to better understand customers’ behavior, spending habits, and desires.

After completing the course, you will be able to:

  • Effectively find and evaluate internal and external sources of data.
  • Determine whether to buy an off-the-shelf market segment analysis or build a customer segmentation in-house.
  • Construct predictive equations for setting appropriate campaign sizing to meet financial targets.
  • Recommend the product mix for marketing to each customer or prospect.
  • Measure individual campaigns in terms of long-term customer value.
  • Earn a credential certifying completion from the University of Chicago and become part of the UChicago network.
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Predictive Analytics for Marketing Curriculum

You will learn to:

  • Leverage data to target the right audience.
  • Segment audiences for optimal contact strategy.
  • Measure the impact of marketing campaigns.
  • Predict future customer purchases.
  • Forecast Customer Lifetime Value (CLV).

Online Format Features

  • Self-paced interactive learning modules with a variety of engaging learning activities, assignments, and resources.
  • Live sessions that bring you, your peers, and your instructor together to learn collaboratively about the current state of the field, engage with real-world problems, and explore authentic solutions.
  • Continuous support from your instructional assistant, who will accompany you on your journey through the content, answer your questions, and provide feedback on your work.

Weekly Course Schedule

Become familiar with the three case studies that will be used throughout the course: automotive (manufacturer), travel (cruise lines), and consumer packaged goods (retailer). Explore sample targeted marketing campaigns, incremental revenue goals relative to advertising costs, and approaches to finding the appropriate audience.

Explore potential data sources for three case studies. Determine how to define the marketing question for each using purchase frequency, data value relative to cost, and data specific to a use case versus across use cases.

Learn about off-the-shelf segmentation. Sketch out rule-based segmentation for each use case: product-based, location-based, and market basket-based. Determine how to apply different contact strategies for each use case: banner ads, email, direct mail, and apps.

Discover k-means segmentation. Demonstrate a sample segmentation using Excel. Translate from customer segmentation to activation in each use case: product-based, location-based, and market basket-based.

Learn about marginal return on investment. Explore techniques for appropriate audience sizing. Examine theory on linear versus logistic regression tying back to the three use cases: infrequent purchase, annual purchase possibility, and weekly purchase.

Explore expansion from previous models to multiple product lines. Share techniques for appropriate audience sizing. Determine whether a contact strategy is appropriate at a high level across use cases.

Delve into expansion from campaign focus to lifetime value. Share techniques for appropriate audience sizing. Determine whether there is appropriate lifetime value across use cases.

Tie it all together into a coherent story for each use case. Share the latest in data ethics and privacy. Consider inherent error in predictive modeling and the associated risks.

Earn a Credential in Predictive Analytics for Marketing

After successful completion of this course, participants will receive credentials certified by the University of Chicago including a digital badge to recognize their achievement.

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Meet Your Instructor

Our highly trained instructors are courageous thinkers and passionate leaders who leverage years of industry expertise and up-to-date knowledge of terminology, tools, and trends to deliver an unparalleled learning experience. Through their rigorous discourse, cross-disciplinary collaboration, and field-shaping contributions, they create practical solutions and pioneering innovations that enrich our world.

David Cameron

Dave Cameron, MSc

Data and Marketing Analytics Expert

Dave Cameron has over twenty-five years of experience in data science and predictive analytics. He worked at Nielsen Holdings, the global measurement and data analytics company, serving in vice-presidential roles in data science, customer segmentation, and statistical methodology.

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Career Outlook

As consumers increasingly opt for having what they want when they want it, marketers are turning to predictive analytics to stay a step ahead and foresee their preferences. Today’s organizations want data-savvy marketing talent equipped to make sense of the growing volumes of information and ultimately drive sales. Over the past year, more than 380,000 marketing job listings were posted on LinkedIn.

# 7

The ranking of market research analyst in U.S. News and World Report’s 2024 Best Business Jobs.

12.84 %

The CAGR of the marketing analytics market over the next five years.

Potential Job Titles for Marketing Professionals with Predictive Analytics Expertise

  • Brand Analytics Manager
  • Chief Marketing Officer
  • Content Marketing Specialist
  • Customer Insights and Analytics Consultant
  • Customer and Marketing Analytics Manager
  • Data Engineer
  • Data Scientist
  • Digital Marketing Manager
  • Marketing Analyst
  • Marketing Data Analyst
  • Marketing Director
  • Marketing Manager
  • Predictive Analyst
  • Predictive Analytics Consultant
  • Predictive Analytics Specialist

Of Interest