Machine learning for Dynamics, Part 2: Making the most of machine learning with Dynamics 365 / CRM

Microsoft Dynamics 365/CRM customers have a number of machine learning tools at their disposal thanks to the solution's proximity to technology from Azure Machine Learning Studio and the Cortana Intelligence Suite (formerly the Cortana Analytics Suite). MSDynamicsWorld has covered a few of these capabilities already, such as our article earlier this year on ranking CRM leads using Azure ML and Microsoft's progress in offering pre-built tools for CRM users like Customer Insights.

However, for all its promise as a strategic asset, machine learning is sometimes viewed as a black box. Machine learning (ML) is not just a feature that you can select by checking a box in a CRM menu somewhere. And it's not a feature that one activates and never thinks about again. Rather it's a technique that power users and decision makers learn over time how to best apply to their own workflows. Over time, ML helps a business application like Dynamics 365 sales, marketing, and customer service apps learn and improve their predictive capabilities through access to growing sets of data, plus some trial and error.

Machine Learning in CRM - best practices

Stefano Tempesta, VP of Engineering at EF Education First and a Microsoft MVP, offers some tips for users to best apply machine learning tools within CRM.

First, understand that machine learning is really a tool built on data. So before a user begins reaping the rewards of machine learning, she needs to understand the data sources that the ML technology of Cortana Intelligence Suite or Azure will be drawing on.