Each financial quarter I collect data on the number of potential clients, contacted potential clients, and potential clients that become actual clients. I have this quarterly data going back only 6 years (6*4=24 total time steps). If I want to generate forecasts for this vector (three metrics) for the upcoming quarter what are my best bets in terms of statistical/ml models? The business is very dependent on the economy so I think it would be interesting to include a few external quarterly metrics such as unemployment rate to improve the forecast if possible. Can anyone help me reason through the best way to approach this?
I don't often deal with time series data and when I do it typically has had tons of data available so often go to more complex models (many-to-one LSTMs, GRUs etc) but I don't think those will work well in this case. I would like to do better than just a moving average, does anyone have any insight into what models would be most appropriate here?