Forecast spending of customer

Question

Hi everyone,

I'm new user to R and I'm struggling with forecasting the spending of customer based on the time series data set which I attached to this post. I tried to build to models: ARM and regression. With ARM 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 ARM 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 ARM model. However, with an R-squared of only 50%, the fluctuation of predicted values for others days is very high. Does anyone have any ideas about which is the most suitable forecasting models I should apply here? Or is there anyway to improve my models such that I can be able to forecast most accurately the customers' spending on both first day of month and normal days? I am looking for the result showing <=1% difference between the predicted number and the real number. Many thanks!

spending forecasting.xlsx

unknown · Accepted Answer

For ETS, have you tried setting the trend to multiplicative?

Charity_K_Wilson · Accepted Answer

Would you mind uploading your workflow?  Under the Options tab is the option to "Export" your workflow.  It will package it up nicely so that we can look at it.  I'd love to see how you are setting up your Time Series.  I'd also like to see the Linear Regression.

There may be a way to use a covariate with the Time Series.  I just don't know which variables are your target variables, and which ones are the dependent variables.