Abstract Details
Activity Number:
|
192
|
Type:
|
Contributed
|
Date/Time:
|
Monday, August 5, 2013 : 10:30 AM to 12:20 PM
|
Sponsor:
|
Section on Statistics in Marketing
|
Abstract - #309359 |
Title:
|
Simulation and Modeling of Churn and Customer Lifetime Value in Mobile Applications
|
Author(s):
|
Alex Zolot*+ and Yakov Keselman
|
Companies:
|
Medio Systems and Medio Systems
|
Keywords:
|
churn and LTV ;
empirical Bayes ;
Maximum A-Posteriori Probability ;
HMM ;
Kaplan-Meier estimate ;
simulation
|
Abstract:
|
Developers of mobile applications need to know the effect of various app features on their customers' churn and lifetime value (LTV). The only available data often are activity log files for short period of observation, and "truth info" about churn and LTV is absent, so even being able to reliably label customers as "churned" or "active" is a challenge.
We describe variations of the MAP (Maximum A-Posteriori Probability), HMM (Hidden Markov Model), and the empirical Bayes approach that we have developed to address the problem.
For non-parametric analysis of data, we generalized Kaplan-Meier technic used in survival analysis to the case of "fully censored" data, i.e., when the dates for both, "birth" and "death", and even facts of "death" are unknown.
We have validated our approaches both on simulated data (where the truth is known) and on real data.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2013 program
|
2013 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.