Easily differentiate between client segments by identifying patterns of behaviour. Using cluster analysis to find cohorts of clients that would be missed by traditional

Value Proposition

A basic customer insight analysis (customer segmentation) build on top of an integrated data analytic platform with machine learning capability (IBM Cloud Pak for Data) which brings values such as,

• Increase Customer Experience and Relationship
• Increase Customer Targeting Accuracy
• Increase Closing Rate
• Help Simulate Pricing
• Help Choose The Right Channel
• Accommodate Up-Sell and Cross-Sell

This customer segmentation analysis is build with IBM industry accelerator template that is included within IBM Cloud Pak for Data. To quickly utilize the template business user only need to provide data that are close to the sample excel file : account.csv, customer.csv, and customer_summary.csv. The analysis process from mapping business term, data refinery, model data creation, data visualization, and deployment already scripted into Jupyter Notebook, it can be modified if needed. Test environment also available on the same platform with graphical interface. Deployment also happen in the same platform and customer segmentation prediction can be consume directly with webservice or API.

IBM Solutions Used

IBM Watson Knowledge Catalog, Watson Machine Learning, Watson Studio, RStudio