Clustering Analysis Performed on the Customers of a Mall based on some common attributes such as salary, buying habits, age and purchasing power etc, using Machine Learning Algorithms.
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. Spending Score is something you assign to the customer based on your defined parameters like customer behavior and purchasing data.
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.
From Udemy's Machine Learning A-Z course.
I am new to Data science field and want to share my knowledge to others
By the end of this case study , you would be able to answer below questions. 1- How to achieve customer segmentation using machine learning algorithm (KMeans Clustering) in Python in simplest way. 2- Who are your target customers with whom you can start marketing strategy [easy to converse] 3- How the marketing strategy works in real world