Forecasting an individual based on a representative group
I think you are doing a supervised classification problem.  You have labelled data — previous customers, which you could label as different groups (e.g. high spend / low spend) along with predictors about the customer — their details (e.g. age).  

You could think of each of these customer details representing dimensions on a plot, wth your task being to find out where different groups of customers are clustered along these dimensions.  Once you know that you can predict what group a new customer will likely belong to, based on their details.

There are many methods for solving this sort of problem, including but not limited to support vector machines, gradient descent and nearest neighbour.  Which one you choose will depend on the amount and sort of data you have.  A really good guide if you are starting out is this flowchart in the SciKit learn documentation, which isn't exhaustive, but gives a useful overview.