CRM Business/Technical Analyst
Microsoft Business Solutions MVP
Over 8 Years with Microsoft Dynamics (GP, AX
2 Patents with Azure ML
3. • How many of you are Dynamics End Users ?
• How many of you are Partner Employees /
• How many of you have tried out Azure ML ?
• How many call yourself technical ?
4. • Machine Learning and AI Concepts
• How they Apply to Dynamics 365
• Azure ML – Introduction
• How you can use Machine Learning with Dynamics
10. Qualify Develop Propose Close
Predictive Lead Score
with External Data
Lead from Post
2 - The lead will be routed to
telemarketing. Telemarketer contacts
John only 2 minutes after his post and
adds further information to the lead based
on the phoneconversation with John.
3 - Based on the updated lead
information CRM performs
predictive lead scoring with
both internal and external (bing)
4 - As the predictive lead score is > 80 (hot lead) the lead is
automatically classified as sales qualified lead and routed to sales
rep. Furthermore CRM automatically creates opportunity record.
Sales rep performscustomer call and is adding further
information (budget, timeline, role of contact, other signals)
5 - Based on the updated opportunity
information CRM performspredictive
Sales rep opensthe opportunity and
understandscurrent score, probability to close.
7 - Based on the opportunity
information CRM system provides
recommendation to sell e.g.
6 - CRM is displaying reasoning (signals
identified). Sales rep receives information
through which step probability to win can be
increased (suggest referencecall with specific
8 - Sales rep picks up the information and
is closing the now bigger deal faster.
Intelligent Customer Engagement with CRM, Azure ML & IoT
1 - John (CIO at 123 Health) is tweeting in
regard to a Contoso product(medical
measurement device). Through MSE we
automatically determine intent and create
lead from twitter post
15. TodayFirst thing in the morning, open the CRM
App to be welcomed with the new
16. Scrolling up we can see it’s a feed of
Looks like Maria recently asked me to set
up a meeting via email.
17. Relationship Analytics
Automatically capture rich signals
from Exchange* and CRM to
determine relationship health, risk
and best next action
Find who are the top contacts for
Accounts & Opportunities and
who in your team can best help
Determine if you are spending
your time on the right
opportunities, stakeholders and
Coach and guide your sales team
based on accurate activity data
19. Data Science is far too complex today
• Access to quality ML algorithms, cost is high.
• Must learn multiple tools to go end2end, from data acquisition, cleaning
and prep, machine learning, and experimentation.
• Ability to put a model into production.
This must get simpler, it simply won’t scale!
20. Reduce complexity to broaden participation
Microsoft Azure Machine Learning
Features and Benefits
• Accessible through a web browser,
no software to install;
• Collaborative work with anyone,
anywhere via Azure workspace
• Visual composition with end2end
support for data science workflow;
• Best in class ML algorithms;
• Extensible, support for R OSS.
21. Microsoft Azure Machine
Features and Benefits
Rapid experimentation to create a
Immutable library of models, search discover
Rapidly try a range of features, ML algorithms
and modeling strategies;
Quickly deploy model as Azure web service to
our ML API service.
25. • Option 1 – Azure ML Previews*
• Option 2 – Opportunity Model
• Option 3 – Build your Own ML Integration
*Azure Machine Learning integration with CRM Online is only
available for instances in the North America (NA) region.
26. • Preview feature: Create and manage models to make product
31. • Available at opportunity.codeplex.com
• Opportunity Scoring uses a machine learning model trained on past
sales data to predict the eventual probability that the sale will be
• Template architecture and End to End Reference
WHAT IS THE OPPORTUNITY MODEL
• Dynamics CRM: USE MACHINE LEARNING TO CALCULATE
HAPPINESS INDEX – Manny Grewal
• Predictions in Dynamics CRM with custom Azure Machine
Learning integrations - Lucas Alexander
OPTION #3 – BUILD YOUR OWN AZURE ML INTEGRATION
38. • Machine Learning Concepts
• Azure ML CRM Preview Features
• Azure ML with and End to End Solution
39. 1. Sign up for Azure ML Trial and play
2. Download Opportunity Scoring Model, and test it
3. Review Scenarios
40. MORE RESOURCES !
OPPORTUNITY SCORING MODEL FROM MICROSOFT
CORTANA INTELLIGENCE WITH SQL SERVER
GARTNER ON AI AND MACHINE LEARNING
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(image of prizes tbc)
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