Problem Statement: This data set is created only for the learning purpose of the customer segmentation concepts , also known as market basket analysis . I will demonstrate this by using unsupervised ML technique (KMeans Clustering Algorithm) in the simplest form.You are owing a supermarket mall and through membership cards , you have some basic data about your customers like Customer ID, age, gender, annual income and spending score. Problem Statement You own the mall and want to understand the customers like who can be easily converge [Target Customers] so that the sense can be given to marketing team and plan the strategy accordingly.
1)The count is 200 means we have records of 200 customers with us. 2)The minimum age of customer in our data is 18 yrs and maximum age is 70. The mean here is 38 and median is 36.Here Mean>Median means our data has high outliers ie more of youngsters prefer to go malls. 3)The minimum annual income of customer is 15k$ and maximum is 137k$.T The mean and median here is 60k$ and 61k$ respectively. 4)Spending Score is something you assign to the customer based on your defined parameters like customer behavior and purchasing data.Here the minimum spending score assigned is 1 and maximum ranges till 99.Both mean and median is 50.