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Second, for your specific situation, it sounds like you are trying to predict a binary variable (a categorical variable that can take on 2 values: yes the lead turned into an opportunity or no the lead did not turn into an opportunity). Here is a useful thread on developing a binary classification model.
If you are not interested in the variable selection process, the Forest Model may be the best tool to start with (this model can automate variable selection). Alteryx has two built in workflows for the Forest Model (Help -> Sample Workflow -> Predictive Analytics -> 7 Forest ModelsandHelp -> Sample Workflow -> Predictive Analytics -> 12 New Donor Score Sample), and a handy explanation of the output can be found here. Here is a video that walks through the process of building a random forest model: Build a Random Forest Model.
However, if you are interested in specific variables and/or don't mind manually choosing variables, Logistic Regression may be the best tool to begin with. A discussion on logistic regression can be found here, and a useful suggestion in that thread is to use the predictive starter kit, which can be downloaded here (Starter Kit). Here is a video that walks through the process of building a logistic regression model: Logistic Regression Using Alteryx.
As a final thought - keep posting to Community with questions you have along the way! It is a really powerful resource, and definitely here to help you! :)
Thanks and welcome to the exciting world of predictive!