QUESTION:

GLAUBERF@varejo.com.br wrote:

Dear list members:

I have a question and I hope you can help me.

I have a database with 22649 cases of clients who cancelled (I also
have another database with the clients that are still active, the
clients that did not cancel yet) their accounts that is modeled like
this:

IDClient       Month(n)  Month(n-1)      Month(n-2)     ...  Month(n-11)
Cancel Date

- IDClient is an identifier of the client (integer);
- Month(n) is how much the client spent is dollars on month n;
- Month(n-1) is how much the client spent is dollars on month n - 1;
- Month(n-2) is how much the client spent is dollars on month n - 2;
- ...
- Cancel Date is the date (mm/dd/yy) the client cancelled his account.

I need to design a model to predict, some months beforehand (maybe one
 or two), that a given client will cancel its account, so I can try to
 get in touch with him and try to change his idea.

What technique should I use ? Survival Analysis ? Any suggestion using
 SPSS 8.0 Professional ?

Can anybody help me ?

Best Regards,

Glauber Fonseca

ANSWER:

What you have is a time series problem where you wish to use historical
data in order to assess an unusual value for purposes of early warning
or intervention detection.  If the series has an internal auto-projective
nature or signal then when the "unusual" happens an intervention can be
detected. This doesn't mean that can forecast the event (death) it just
means that it maybe detectable in advance allowing corrective action to
be taken.

One of our clients is using/investigating  this in a banking application
where the bank wishes to be pro-active and sense a change in status.