Comprehensive course analysis
Who should attend
- Marketing and digital marketing managers who want to upskill and improve their marketing ROI by using the latest tools—without having to depend on an analytics team
- Analysts who want to develop better models and algorithms to draw marketing insights, and also specialize in marketing related applications of analytics, such as recommendation engines, customer segmentation, ROI optimization and more
- Product and Business Managers who want a deeper understanding of customer behavior, and to use those insights to improve product iterations, boost profitability, and develop marketing best practices
- Brand Managers who want to take a more data-backed, scientific approach to branding initiatives and communication, gain insights on their customers’ preferences and profiles, and thus create brands that are able to earn loyal customers
About the course
Successful marketing requires harnessing the power of the best available tools to acquire the intelligence necessary to make informed decisions and gain a competitive edge. Marketing professionals with the knowledge, skills, and experience to leverage data to achieve their goals will hold a significant competitive advantage.
The Marketing Analytics - Strategies to Optimize ROI program explores the principles and strategies of a data-driven approach to marketing and how to apply those in the real world. Drawing on real-world use cases from successful companies like Netflix and Booking.com, you’ll learn how to build predictive models to inform marketing decisions, and leverage analytics to optimize marketing ROI. Through practical tools and techniques, you will gain valuable insights into your customers and what drives their purchasing decisions. You will also learn to use the Customer Lifetime Value formula to guide marketing and product decisions throughout the consumer journey, and follow four key steps for implementing an innovative marketing analytics initiative in your organization when the program concludes.
- Make Informed Marketing Decisions Based on Analytics
- Apply Analytic Tools, Models, and Frameworks to Optimize Marketing ROI
- Leverage Analytics and Experimentation to Gain a Competitive Advantage
- Develop Marketing Strategy for Customer Acquisition, Development, and Retention
- Create Innovative Marketing Analytics Initiatives in Your Organization
Module 1 | Introduction to Marketing Analytics: How to Unleash the Power of Data
Learn the principles of Marketing Analytics and how to apply them in the real world through a fundamental marketing measurement called Customer Lifetime Value. Once you determine how valuable a customer is to a company throughout the entire consumer lifecycle, from acquisition to development to retention, you can use that insight to guide marketing and product decisions at each step of the customer journey.
Module 2 | Predictive Models for Marketing Analytics
Learn how to use predictive modeling, the fastest growing branch of marketing analytics and the basis of modern business intelligence systems. We will show you how to execute two fundamental predictive models and build your own predictive models to generate marketing insights.
Module 3 | Customer Segmentation and Targeting
We explore factor analysis, a broadly applicable data consolidation tool that is key to marketing research and customer segmentation and targeting. By considering two cases in parallel—one from Charles Schwab and one from Booking.com—we learn how factor analysis helps create a customer segmentation map, generate core customer insights, and serve as a foundation for your marketing strategy.
Module 4 | Personalized Targeting and Recommendation Systems
Using big data, we apply marketing analytics for targeting and personalization. Our hands-on approach leverages actual data and shows you how to build a targeting and recommendation system that incorporates real-time location data from mobile devices for targeting.
Module 5 | Pricing Analytics
We explain the basics of pricing, including different ways it is established and what makes an ideal price. Using data collected for a technology startup, we delineate best practices for using survey methods to generate a price—a particularly valuable tool when preparing a product launch. We also look at a versatile pricing tool called conjoint analysis.
Module 6 | Marketing Experimentation
We reveal the key tool for marketing measurement: A/B testing or experimentation. A case study in digital advertising provides a real-world introduction to this topic. Proceeding step by step, from the design phase through implementation to the evaluation of an actual A/B test, this case study delves into the major issues to consider when running experiments and prepares you to set up your own A/B test.
Module 7 | Digital Advertising Analytics
We examine the most important concepts and metrics in digital advertising, including various payment methods, programmatic advertising, auctions, and quality scores. Learn about key challenges digital marketers face as they attempt to further customize individuals' marketing communications experience.
Module 8 | Strategic Outlook in Marketing Analytics
To ensure a successful implementation of your marketing analytics initiatives, we will illustrate how to build a strong analytics team, again using actual success stories. We will also show you how to recognize the limitations of marketing analytics, including common pitfalls in managing a marketing analytics project, and outline strategies to avoid them.
The eight-week Marketing Analytics program culminates with a capstone project in which you will create a slide deck that outlines the four steps necessary to implement an innovative marketing analytics initiative at your organization.
Education PhD, Psychology, Cornell University AB, Psychology, Yale University Positions Held At Haas since 2010 2016-present, Associate Professor of Marketing, Haas School of Business 2010 – 2016, Assistant Professor of Marketing, Haas School of Business External Service and Assignments Journa...
Education PhD, Economic Analysis and Policy, Stanford University MS, Mathematics, University of Arizona MA, Economics, University of Arizona MA, Quantitative Methods and Information Systems, Warsaw School of Economics BA, Quantitative Methods and Information Systems, Warsaw School of Economic...
Education PhD, Management (Marketing), INSEAD, France PhD, Computer Science, Eotvos Lorand University, Hungary MSc, Mathematics, Eotvos Lorand University, Hungary Positions Held At Haas since 2008 2008 – present, Assistant Professor of Marketing, Haas School of Business External Se...
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