ODM Product Recommendation for customer churn

We presented last week an important asset we have developed to integrate a predictive scoring with business rules and chatbot for doing product recommendation. This open source content, visible at https://github.com/ibm-cloud-architecture/refarch-cognitive-prod-recommendations, and includes how to use IBM Decision Composer to start modeling decision with Decision Model Notation, and move the content to IBM Operational Decision Management. Then we modified the data model and implement product recommendation rules. We highlight how to deploy ODM On IBM Cloud Private the Kubernetes platform, how to implement ODM simulation to find the best rules implementation to improve business impacts, and how to leverage churn scoring to propose discount.

This asset explains the integration with a chatbot developed with Watson Assistant, and a larger solution, named "green compute", which addresses a solution implementation and analytics reference architecture. The use case is detailed in this repository with a detailed demo script and all the code to run it, we explain how we built the machine learning with python spark API leveraging customer records, chat transcripts, and marketing campaigns. 

This is a very interesting contribution that we are improving over time.

The contributors are Guilhem Molines,  Mathew Voss, Joseph Luc Correa, Jordan Acock,  Zach Silverstein and myself.

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