No Subject

[Hallberg Rassy]

 Dear Friend  
 I have now a problem and would like to share with you and to 
receive, if  
 possible your opinion. 
 Hereinafter the picture of situation: 
 1.I'm presently involved in a customer profiling project for a 
large   mobile operator. 
 2.The goal is to set up a system able to anticipate the 
likelyhood of  churn of  customers 
 3.As a pilot step I extracted call records for 10000 active 
customers  plus 4000  churned 
 4.Using SPSS neural connection I made up a neural network based 
on a set 
 of 4000  active+4000 churned 
 5.The data was: calling patterns of july, agoust and september 
the   target was:  churn/no churn situation in december 
 6.The results was promising: 90% of real churn anticipated, with 
a   cut-off  probability of 80% 
 7.The same network was used on october, nov, dec. data to 
anticipate  
 march churn  the results dropped to a terrific 11% with the 
same cut-off  
 of 80%: totally  useless   
 I have formulated some hypotheses 
 A.The low time span (three month) is affected by 
seasonality 
 B.The data used are not sufficient to build a reliable 
network 
 C.The tool (SPSS Neural Connection) is not reliable  
 Could you give your opinion? 
 Many thanks in advance    
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