Customer-Segmentation
Customer Segmentation using Python, Numpy, Pandas, Sckit learn, Scipy,matplotlib and seaborn
Dataset OnlineRetail.csv contains all the transactions occuring between 01-Dec-2010 and 09-Dec-2011 for a UK-based and registered non-store online retail.
Steps involve in the Customer Segmentation are categorized into following:
- Reading and Understanding Dataset.
- Cleaning the Data.
- Data Preparation.
- Building the Model.
- Final Analysis.
Dataset Description
Outlier Analysis Insights is shown below:
In the customer segmentation, I have used the K-Means CLustering Algorithm
K-Means is one of the simplest and useful Unsupervised Machine Learning Algorithm. To find the optimal number of clusters, I have used Elbow Method. Elbow method plot is shown below:
After performing all the necessary processing and implementing model, we have got different insights that shows relation between cluster and attributes:
1. Cluster ID VS Amount
1. Cluster ID VS Frequency
1. Cluster ID VS Recency