For a business, the cost of acquiring new customers is typically high when compared to retaining existing customers. Because of this, managing customer churn is an essential requirement of a successful business. Customer churn is the percentage of customers that stopped using your company’s product or service during a ceratin time frame. Of course retaining all your customers is an impossible task, however, being able to predict which customers might leave in the future gives businesses valuable insights into their customers and their business.
As part of a project, I was given the Northwind database to generate valuable analytical insights that could be of value to the company. The Northwind database is a sample database created by Microsoft for a fictitious company called Northwind Traders which imports and exports consumables around the world. For this, I would need to come up with a couple questions to be used for hypothesis testing. The first question I was to answer was:
For our first project I had my first attempt at data analysis. The data I used was the Kings County House Sales dataset which includes the data for houses that were sold in Kings County, Washington in 2014 and 2015. This dataset contains many different variables along with the prices each house was sold for and during my analysis I came across a problem trying to figure out the best way to see the relationship between bedrooms/bathrooms and price.
Growing up, never in my wildest dreams would I have imagined that I would be making a living making YouTube videos. Of course YouTube only gained widespread popularity once I was graduating high school, but even then, I thought I would go into a normal career path, being either a banker, accountant, or lawyer. A career path that would be palatable for my parents. Because of that, even though I had an interest in computers and computer science, I decided to study finance in college, choosing a major in my parents interests and not my own.