I have a dataset consisting of purchasing history from an e-commerce website. The columns consist of customer id
, product id
, postal code
, quantity of products purchased
, date of the purchase
. There are thousands of different customer ids, hundreds of product ids, and some million rows.
I ran ARIMA modelling for forecasting the purchased quantities of a given product. Now I want to try other methods for analysing the dataset, but cannot find models which could fit the dataset well. What other models could I run in order to gain more insight on this data?