I want to forecast new customers' energy consumption. Let's say I can construct a set of attributes to describe new and existing customers (e.g. size of business, type of business etc.) and I have the time series data on energy consumption of existing customers. However, I have no historical data on new customers' consumption.
If existing customers' consumption has seasonality but no trend, I could use the set of attributes to create a regression model to predict new customers' consumption based on existing customers' consumption. But what if existing customers' consumption has a trend? How do I know at which point of the timeseries I should start the forecasting?
If I want to forecast new customers' consumption for one year, how do I know at which point of this time series to start the forecasting?
I do not have a dataset yet, so I cannot provide data examples. The answers could include an idea on what types of additional information I would need (if any) to solve this problem. Enrgy consumption is just an example, my question is theoretical and could be generalized to any other field. Also, names of python libraries to deal with this problem would be welcomed!
Thank you for the help.