I am forecasting the spending of customer based on the time series data set. I tried to build to models:
- regression. ´
With Arima model, I was able to forecast quite accurately the spending of customers on normal day. However, in both my data set and present reality, on every first day of month, due to monthly promotion, the customers' spending is always significantly higher than that on other days. Hence, with Arima models, at the moment I have not been able to forecast the customers' spending on first day of month accurately. With regression model, the predicted number for the customers' spending on first day of month was more accurate than that predicted with Arima model.
However, with an $R^2$ of only 50%, the fluctuation of predicted values for others days is very high. Can you please advise me methods that I can use to improve my models or is there any other models that can help me to predict the spending accurately on both normal days and first day of month? Here is a small part of my data