Demand forecasting with marketing budget data

I'm trying to build a demand forecasting model to predict future daily orders of an online food takeout service (similar to UberEats or DoorDash). My first model uses a univariate approach, which is basically an ensemble of statistical models such as Auto ARIMA, ETS, BSTS, etc. Now, I want to build upon this by adding features related to marketing budget/spend because that's always been a big push for sales, however, the data that I have is only on a monthly level, which makes sense because things like promotional campaigns can only be planned at a high level. So my question is, how can I integrate this data into my forecast model? Any other tips on improving the model accuracy (e.g. what features can be added) are also appreciated. Thanks!