This document discusses using survival analysis techniques to understand customer attrition and lifetime value. It provides examples of survival analysis distributions, estimation methods like the Cox proportional hazards model, and applications to a direct mailing case study. The case study uses survival analysis to examine how payment method, product switches, downgrades, income and household density affect customer retention and lifetime value, finding that loyal customers spend more over time.

1. Applications of Survival Analysis to Customer Management Henry Stewart Briefing for Users of Marketing Analytics 4 December 2008, Mayfair Conference Centre, Marble Arch, London William De Genst

2. Survival Analysis

3. Survival Analysis Understanding Customer Attrition

4. Survival Analysis Techniques

5. Survival Analysis Distributions of lifetimes

6. Survival Analysis Distributions of lifetimes

7. Survival Analysis Joining Time Time Survey end Actual Time Time from common origin Distributions of lifetimes

8. Survival Analysis Estimation

9. Survival Analysis Estimation

10. Survival Analysis Trial contract Non-trial contract Log-rank test (Mantel-Haenszel) Chisq= 30.2 on 1 degrees of freedom, p= 3.98e-08 Estimation

11. Survival Analysis Cox proportional hazards model

12. Survival Analysis Cox proportional hazards model Var  SE(  ) z p v 1 0.09 0.03 3.19 0.01 v 2 -0.35 0.19 -1.83 0.06 v n -0.34 0.38 -0.90 0.37

13. Survival Analysis Schoenfeld residuals ~ time Martingale residuals ~ covariate Cox proportional hazards model

14. Survival Analysis Cox proportional hazards model Smoothed term

15. Lifetime Value Analysis Customer Lifetime Value

16. Lifetime Value Analysis time Survival probability Customer spend time Marketing campaign Initial cost Initial return Loyal customers spend more over time Return on investment Customer Lifetime Value

17. Case Study Cost of a Direct Mailing Campaign

18. Case Study Free trials Year 1 renewal Cost of a Direct Mailing Campaign

19. Case Study DD cancelation Free trials going on to other products Original Payment Method

20. Case Study Payment method as strata Decreased hazard: More product switches Method payment Downgrading (customer finds fee unjustified for usage) Increased income Increased hazard: Higher household density Cost of a Direct Mailing Campaign coef exp(coef) se(coef) z p productswitches -0.21 0.81 0.08 -2.58 0.01 methodswitches -2.76 0.06 0.15 -17.99 0.00 downgrades -1.63 0.20 0.58 -2.80 0.01 income 0.03 1.03 0.01 1.76 0.08 HHdensity 0.06 1.06 0.03 1.95 0.05

21. Case Study - Loyal customers tend to spend more over time - Free trial customers that subsequently subscribe to a paid subscription gradually spend more, to reach same level as paid subscribers Paid Free trial Cost of a Direct Mailing Campaign

22. Case Study break-even in week 65 Cost of a Direct Mailing Campaign

23. Case Study Cost of a Direct Mailing Campaign

24. Conclusions