How to represent time based periodic data for use in ML
Answering the question JahKnows asked in the comment above will help with finding the suitable solution for your use cases.

If you are not exactly sure what you are after, here are a few things you can do with a dataset like this:


One of the basic things you can do is to find customers that behave similarly. With the data that you have, you can consider the number of machines used by each customer in each month as features. In this case, each customer is described with 5 features. I would run a clustering algorithm against this data (of course leave CustId field out) and see how many types (clusters) of customers you have. 
Another thing to do is to run statistical analysis over the number of machines your customers use each month and find those that stand out from the rest of the population (customers). 
Another analysis you could do is to analyze the trend for each customer separately and based on their past behaviour, determine if the number of machines they have used in the past month was in accordance with their historical behaviour. In this case, you can take proper actions based on the shift of behaviour. E.g. a drop in the number of machines could mean the customer is having technical difficulties or churning.