Topics: AI | Data Science | Data Visualization | Deep Learning | Machine Learning | NLP | Python | R | Statistics

KDnuggets Home » News :: 2013 :: Sep :: Courses, Events :: Wharton Course: Customer Lifetime Value: Practical Methods and Applications ( 13:n23 )

Wharton Course: Customer Lifetime Value: Practical Methods and Applications


Customer Lifetime Value is a critical concept for any customer centric organization. This workshop looks at 2 major themes: contractual vs non-contractual settings, and probabilistic approach to modeling customer value.



Wharton Executive Education Course:

WhartonBringing Customer Lifetime Value to Life: Practical Methods and Applications

Feb 13-14, 2014, San Francisco. $2,600.

Apply Now    Download Materials.

Program Overview
Customer Lifetime Value (CLV) is a critical concept for virtually every organization that claims (or aspires) to be customer centric. At a granular level, it helps companies decide which tactics to use for which customer. At a more macro level, it is the key ingredient in calculating customer equity - which, in turn, drives overall corporate valuation.

The two-day workshop is organized around two major themes. The first, is the distinction between contractual and non-contractual settings. This dichotomy has important implications that merit discussion at a strategic level, and it points out the need for different modeling assumptions, operational steps, and validation methods when it comes to implementing CLV.

The second theme arises from the methodical approach that underlies all the analyses covered in the workshop, namely probability models. While less familiar than regression analysis and the wide array of methods that fall under the "data mining" umbrella, this class of models is uniquely well-suited for the challenges of computing CLV (e.g., the need for long-run forecasts). And it is remarkably simple from both a data management and model estimation standpoint (often requiring nothing more than an Excel spreadsheet for complete model implementation). Our coverage of probability models will be woven into the workshop as a "means toward an end," with modest (and "manager friendly") handling of the technical details and model implementation in Excel.

By the end of the workshop, participants will understand the critical concepts and techniques required to make meaningful and accurate statements about CLV in various managerial settings. Likewise, they will be keenly aware of the limitations and concerns of other approaches that are often used for similar purposes. Thus, besides having the skills to build models themselves, participants will know how to ask the right questions of consultants and IT vendors who offer services in this important area.

The workshop is taught by

  • Peter Fader, PhD, Faculty Director and Frances and Pei-Yuan Chia Professor, Professor of Marketing, Co-Director of the Wharton Customer Analytics Initiative, The Wharton School
  • Bruce Hardie, PhD, Professor of Marketing, London Business School

For more information and to register, visit here.


Sign Up

By subscribing you accept KDnuggets Privacy Policy