Wharton Customer Analytics

Research Opportunities

(Closed for Submission)

Predicting Customer Acquisition & Retention with Structured and Semi-structured Data

As America’s largest radio company with over 21 million subscribers SiriusXM Radio Inc. has carefully collected data which provides a “360 view” of its customers, including information on subscribers (and their vehicles in which they have SiriusXM radios), product usage, billing & payments, outbound/direct marketing to these subscribers, and customer service interactions. While customers may access the service via the internet and mobile phones, the majority of the users listen to SiriusXM in their vehicles. Most of the data is structured, but the customer service interactions—notes taken by call center representatives and emails sent by customers—are in free-text format. In addition, user listening logs—minute-by-minute logs of the radio stations users listened to—are available for those users who use the Internet service. Seeking new ways to leverage this data, SiriusXM will be providing researchers with this complete “360 view” for 300,000 subscribers who first started using their service during September 2009.

Questions of interest to SiriusXM include identifying current subscribers who are likely to deactivate (based on listening, payment or customer service records) and finding strategies to reduce churn. In addition, because many subscribers’ first introductions to SiriusXM are through a trial subscription they receive when they purchase a new car, SiriusXM is interested in predicting conversion to paid subscriptions for these users (based on listening, outbound marketing, or customer service records). In this way, the data provides an unusual opportunity to study acquisition at the individual level.

Note: This Research Opportunity is closed for proposal submissions.

Research Teams

GRANTEES OF THE SIRIUSXM RADIO DATA:

MEASURING THE IMPACT OF RETENTION EFFORTS WHEN MULTIPLE CAUSES OF CHURN ARE PRESENT

Eva Ascarza , Columbia University
Oded Netzer, Columbia University

DOES IT PAY TO BE SENTIMENTAL? EXAMINING THE USEFULNESS OF SENTIMENT ANALYSIS FOR PREDICTING CUSTOMER OUTCOMES WITH RESPECT TO CHURN, CONVERSION AND DELINQUENCY PROBABILITY

Sanjay Bapna , Morgan State University
Gregory Ramsey, Morgan State University

STAY OR CHURN? MANAGING CHURN WITH USAGE DATA

Tingting Fan , Stern School of Business, New York University
Sam Hui , Stern School of Business, New York University
Eitan Muller, Stern School of Business, New York University

CUSTOMERS, COMPLAINTS AND CORPORATE PROFITABILITY

Ke Li , Fox School of Business, Temple University
Eric Eisenstein , Fox School of Business, Temple University
Anthony DiBenedetto, Fox School of Business, Temple University

HABIT DYNAMICS AND ITS ROLE IN PREDICTING CUSTOMER CONVERSION AND ATTRITION

Yuping Liu-Thompkins , Old Dominion University
Leona Tam, Old Dominion University

PREDICTING CHURN THROUGH PRIOR VARIETY SEEKING BEHAVIOR

Alina Nastasoiu, Richard Ivey School of Business, Western University
Neil Bendle, Richard Ivey School of Business, Western University
Mark Vandenbosch, Richard Ivey School of Business, Western University

REDUCING CHURN AND IMPROVING FREE TRIAL CONVERSION WITH REAL-TIME PRICE OPTIMIZATION

Mark Ferguson, University of South Carolina
Michael Galbreth, University of South Carolina
Bikram Ghosh, University of South Carolina
Lianming Wang, University of South Carolina

Disclaimer

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