How significant the variables like "id", "region code" etc are in the predictive modelling?
That depends on the problem and the data. Usually, at hackathons, there are at least several thousand id's and hundreds of region codes in your data and your task is to train on one dataset and predict on another dataset with new customers in existing regions.

In this case, you can exclude the id-column. Other categorical variables like region, age-group, race, etc, are usually relevant. The region code can be used as a categorical variable, but it depends on the number of regions. If there are hundreds of region codes in your data, map these codes to a larger region. For example, assume your data contains the region codes of all American counties. The easiest way to go is to map each county to its respective federal state and use the state instead of the county.