I don't have any specific toolchains to offer for that use-case. Instead I'll offer a general R
heuristic.
Every R
problem can be thought of wiht advantage as the interaction of three objects: an existing object, x , a desired object,y ,and a function,f, that will return a value of y given x$ as a argument. In other words, school algebra: f(x)= y. Any of the objects can be composites.
Taking the data at hand and the goal of the analysis (say, what variables are associated with marketing outcomes), what are the candidate functions? What needs done to prepare an appropriate object from the data, and what needs done to prepare a suitable object from the function return value?
This approach will avoid a lot of experimentation with examples not yet completely understood and will focus attention on essential aspects of problem definition.