Big Data and Marketing Analytics
Give your firm the ultimate competitive edge by attending this brand-new program on big data and marketing analytics, at the school that pioneered quantitative marketing.
In this program, you’ll acquire marketing analytics strategies and frameworks to increase ROI and improve your decision-making process based on customer insights. The application of these frameworks will focus on key areas including customer analytics, the measurement of value creation, product positioning, pricing, digital communication, and more. You’ll be equipped with the agility and creativity to make data-driven, insightful decisions in an increasingly analytical world.
By attending the program, you will:
- Master a strategic and scientific approach to marketing analytics that results in higher ROI.
- Learn how to make marketing spending more accountable and improve return on marketing investment.
- Gain an understanding of how to use and interpret data for more precise strategic and tactical marketing decision making.
- Learn to apply analytical frameworks for evaluating marketing strategies with a focus on value creation, customer analysis, product positioning, pricing, communications, and sales force management.
- Discover how to use algorithmic tools to further digital and non-digital marketing goals.
- Explore untapped opportunities for Big Data in your firm’s marketing strategies.
The program is offered in a convenient three-day format so you do not need to take extended time away from the office.
Gleacher Center, Chicago, IL
Sigmund E. Edelstone Professor of Marketing
Jean-Pierre Dubé is the Sigmund E. Edelstone Professor, an area editor for the Journal of Marketing Research, Marketing Science, Management Science, QME and the recipient of several MSI Research Grants, the recipient of a Kauffman grant, and a member of the editorial board and ad hoc reviewer for several academic journals.
Charles H. Kellstadt Professor of Marketing and Neubauer Family Faculty Fellow
Sanjog Misra is the Charles H. Kellstadt Professor of Marketing at the University of Chicago Booth School of Business. His research focuses on the use of structural econometric methods to study consumer and firm decisions. In particular, his research involves building data-driven models aimed at understanding how consumers make choices and investigating firm decisions pertaining to pricing, distribution and salesforce management issues.
Overall, I was extremely impressed with the approach of the BDMA program. Working with Big Data can be challenging if you do not think through what questions to ask and answer; this changed my perspective and I’m looking forward to driving innovation based on these learnings.
-Joe Veverka, Program Manager, Microsoft
Concepts learned will be particularly useful for:
- Mid- to senior-level executives responsible for translating marketing data into action and profits in B2B and B2C companies.
- Marketing, sales, brand and product managers, financial directors, and those who specialize in marketing analytics.
- Small business owners and entrepreneurs who want to focus their marketing spend.
- Executives who want to broaden their marketing analytics expertise.
Economic Value to the Consumer (EVC)
- Providing a substantive derivation of value
- Measuring value and the underlying willingness-to-pay by the customer
- Generating the value proposition
- Quantitative analysis for launching pricing and marketing in a new venture
Demand and Optimal Marketing Decision
- Using the EVC framework to study product demand and the marketer’s decision-making process
Demand Estimation: Conjoint Analysis
- Estimating EVC for products with intangible benefits
- Producing estimates of customer willingness-to-pay
- Customer profiling and segmentation
- Pricing and product configuration decisions
Demand Estimation: Marketing Mix Models and Elasticity Analysis
- Regression analysis to estimate demand
- The incremental effects of marketing variables
- Measuring return-on-investment from marketing decisions
- Formulating a pricing dashboard
Segments and Targeting Marketing
- Targeting across customer segments for profitability
- Personalizing to individual customers
Segments and Product Line Strategy
- Segmentation of product lines
- Frameworks to minimize cannibalization
Marketing to the Lifetime Value of the Consumer
- Using the razors and blades model
- The important role of time in applying the framework
Big Data and Big Analytics
- Data Types and Value
- Machine Learning and Marketing
- Building up the Analytic function
- Product Recommendation Systems
- Programmatic Advertising
- Message & Content Optimization
- Salesforce Analytics
- A/B Testing
- Multi-Touch Attribution
- Unified Measurement: MMM+MTA
Application at Scale
- Pricing at Scale
- Promotion Targeting
- Managing Analytics
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