Customer segmentation very important to make a decision, what action needed to increase revenue, build good relationship with customer and many more we can optimize the sales with customer segmentation. Customer segmentation would be give us a reference to take action for each customer in their segmentation, like a product differentiation, make a focus campaign for each customer and another strategy that we have. Customer segmentation made companies would be focusing with priority scale. This segmentation give us for reach the “star” customer with big purchase until “rare” customer with low purchase. The companies can be focus their energy, costs, and attention on that particular segment.
Since we have a customer segmentation problem, we will apply machine learning techniques to create proper customer segmentations.
This Online Retail data set contains all the transactions occurring for a UK-based and registered, non-store online retail between 01/12/2009 and 09/12/2011.
The dataset has been obtained from Kaggle.
Link: https://www.kaggle.com/carrie1/ecommerce-data
The following modelling approach was used in the project:
Loading and cleaning the raw data Exploratory Data Analysis Market Basket Analysis using Association Mining Customer Segmentation using RFM, The deatiled analysis can be found in the Rmd file