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Multiple Campaigns with Multiple Decision Trees

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Occasional Contributor
Posts: 14

Multiple Campaigns with Multiple Decision Trees

Hi,

 

I have multiple campaigns and their performance data. 

 

I built one decision tree for each campaign to determine the most important independent variables and the rules that can be implemented for each campaign.  Each tree gives me leaves/ segments that tells me the group of customers least or most likely to respond to each campaign. 

 

However, it turns out that my clients want to have just one tree to do the similar job.  However, my trees look so different from each other that I don't know how to build just one tree to do it.

 

Any ideas? 

Super Contributor
Posts: 336

Re: Multiple Campaigns with Multiple Decision Trees

Hey Eric,

What does your data look like?

 

For each campaign your target is a binary target? E.g. either campaignA=1 or campaignA=0.

 

If you have variables like that for each campaign (campaignA, campaignB, campaignC, etc), you can write SAS code to create a new nominal target. Example, for each observation campaign equals a value in {A,B,C,...}.

 

You can then train a decision tree that classifies each person to one of those campaigns.

 

Does that help?

Thanks,

Occasional Contributor
Posts: 14

Re: Multiple Campaigns with Multiple Decision Trees

Hi, Miguel:

Each campaign's target is a binary variable, i.e., Y=1 if customer click and Y=0 if customer didn't click on the web link.

 

I actually built a decision tree with nominal target variable exactly by doing what you suggested.  However, my concern is that not all customers were exposed to all my 4 campaigns.  

 

In other words, it didn't really make sense to say that customer John prefered Campaign A over Campaign B, because John was only exposed to Campaign A, but not Campaign B.

 

 

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