Ranking Dynamics CRM leads with Azure Machine Learning

Editor's Note: This article is an introduction to the session "Ranking CRM Opportunities with Azure Machine Learning" at CRMUG Summit EMEA 2017 on Thursday, April 6 at 9 AM. There, Stefano Tempesta will demo the solution end-to-end, just as it has been implemented, with Q&A to follow. 

Every day, a large educational organization receives thousands of expressions of interest by prospective students to attend program delivered at any of 150+ locations around the world.

How does the organization process all that information while providing swift and effective responses to applicants? They rank interests, which generate a lead in Dynamics CRM based on program, location, history, and literally hundreds of other criteria. Clearly, this cannot be done manually. The organization uses the power of outcome prediction algorithms in Azure Machine Learning.

This real-life use case will be presented at CRMUG Summit EMEA 2017 and will explore the foundation of Azure Machine Learning for building outcome prediction services, including:

• how data is collected and defined into a model
• how the model is trained and then scored
• and how the evaluation of the model is processed to generate the ranked outcome

Outcome prediction

Machine learning is a technique of data science that helps computers learn from existing data to forecast future behaviors, outcomes, and trends. Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. It is possible to work from a ready-to-use library of algorithms, use them to create models on an internet-connected PC, and deploy a predictive solution quickly. Azure ...