Predicting sales that will convert

[Rouche]

Hi everyone, 

I have a question about a machine learning problem that I am trying to solve.  I have a column called "Sale_coverted" which are all quotes that did convert over a period of time.  Then I have a column "Active quotes_last 3 months" and all the possible variables that might have an impact on the whether the quote will convert or not.   What I am looking for is to find is whether an active quotes will convert or not, i.e. yes or no.  I have not yet had success with the runs.  Can someone perhaps assist me a bit with this? 

Currently I have converted some columns to dummy variables and other string columns to numeric values.  Have also added the machine learning tools (boosted model, forest model, decision tree, svm) but need some help with the determining of conversion for the column "active quotes_last 3 months".

As far as I understand it, the models will predict on the column 'sale converted' as to whether a sale converted or not.  I have watched a few videos on predictive analytics, but it has not dealt with an instance like this.  So if someone can suggest videos / courses that might contain a lot of information on predictive analytics in Alteryx, that would also be appreciated.

Thank you for helping!

[JaeLim]

Hi @Rouche ,

Interesting problem you are trying to solve there, maybe the alteryx "Pearson Correlation" tool will be a good start in measuring the strength of your different possible variables against your independent variable (i.e. Sales Converted).

If you could please share your dataset/ workflow for clearer context.

[Rouche]

Hi JaeLim, 

Thank you for your quick answer!  Yes, it is indeed a very interesting problem. 

The correlation tool will provide me with the correlation between the variables of interest.  What I need to accomplish is to determine the probabilities that current quotes will likely or not likely convert.  This is the point at which I am unsure as to how to proceed.