In Excel's data mining tools there is a "Key Influencers" tool which will look at a dataset which is perhaps customers and whether or not they converted to a given goal (e.g. a flag that equals 1). It then tells you the most influential factors in reaching that goal,( e.g. Gender=Male and Age=30-45). What would be equivalent algorithm in R to achieve a similar outcome.
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The algorithm used in the "Analyse Key Influencers" tool in excel is a variation on the Naive Bayesian algorithm for classification. The explanation from Microsoft may be found here:
The naive Bayes algorithm has been implemented in several packages, though most notably the e1071 package by David Meyer. It can be found on CRAN and a decent tutorial on implementing the algorithm may be found here:
I would caution you to ensure that your predictor variables are independent and to avoid multicollinearity in your models, as the algorithm ignores dependencies and is thus "naive" or "stupid".