The dataset we have contains collection of customer information including customer ID, name, surname, gender, age, region, job classification, date joined and balance. Let’s see what kind of actionable insights we can extract from this data.
First, let’s set a customer baseline:
Now that you can see visual representation of this UK’s bank customer data, let’s dig deeper.
This dashboard shows us that England is represented mostly by white collar workers. This is probably due to the fact that London is the financial capital of Europe.
Representation of white collar workers is low in Scotland. Customers predominantly are males in their late 40s and 50’s.
Data for Wales shows above average representation of Mid-high balances.
Northern Ireland is mostly represented by younger females.
So what could this UK bank do with these insights?
For one, the bank’s marketing department can now laser-target their promotions and really match their offers to the potential customers.