> If ARIMA models produce decent results for your use case I would try to improve the ARIMA model through additional data, rather than switching to deep learning.

ARIMA models cannot take into consideration special scenarios or even multivariate features (Like location and time). It's good for simple forecasting but when you need more "human like" predictions we are betting on neural networks.

For example we would instinctively know that sales of turkey goes up on Thanksgiving. ARIMA model cannot factor this but RNN/LSTM should be able to (Theoretically speaking).