Data-Driven Marketing: Pricing, Bundling, and Customer Targeting, MIT short course, Cambridge, MA, 16-17 Jun 2008
Data-Driven Marketing: Pricing, Bundling, and Customer Targeting
June 16-17, 2008
Participants will spend 2 intensive days learning about how a firm can create innovative promotions that will achieve strategic objectives utilizing historical data sets. A firm’s objectives range from maximizing profit or revenue to maximizing market share in the presence of competition. Currently, firms attempt to solve this problem by employing disparate techniques from data mining and predictive modeling. However, a usable consistent methodology for promotion design is still lacking. This course will present a comprehensive approach for optimal promotion design, which integrates state-of-the- art data analytics, marketing science, and optimization. Marketing, merchandising, product managers, statisticians and data analysts will find this course invaluable.
TOPICS COVERED 1. Data Consolidation: How does one extract data relevant to optimizing promotions with respect to a given business objective? 2. Current Modeling Approaches: What models do people build today? Is a query a model? Why should marketing people care about models? Do all models provide the same utility? An overview of clustering and modeling techniques such as: k-means clustering, regression models, artificial neural networks,, decision trees, machine learning, and other techniques will be provided. 3. Global Modeling: How does one find distinguishable submarkets within a global market? Modeling customers’ utility. 4. Marketing Science: How do we innovate promotions? What impact models exist for various promotions? Does tracking help in successive iterations. 5. Surviving in a Competitive Environment: Modeling competition. Games and price wars. Strategic decisions vs. data-driven decisions. 6. Real-life Examples: Four real life examples will be presented: – book retailer: issues and challenges – computer retailer: issues and challenges – clothing retailer: issues and challenges – furniture retailer: issues and challenges