D365 Customer Insights helps unify customer data from multiple sources using a common data model. This allows for a 360-degree view of each customer and their journey across channels. It also enables more powerful AI and personalization by bringing together disparate customer data. The tool ingests data from various sources, maps it to a common schema, consolidates it into single customer profiles, enriches the profiles with AI and signals from Microsoft Graph. It then derives insights from this unified data to automate and optimize processes. These insights can be activated across channels through connectors and APIs.

3. Neuroscientist
CRM Partners
Data Enthousiast
Practice Manager

6. Unique customer profiles Activities Measures SegmentsPredictions
Status quo
• Customer data is spread across many
data sources
• There is no joint taxonomy to describe
customers and their journeys
• LOB apps and tools do analytics & ML
atop local data
D365 Customer Insights
• Is mapping custom data sources to
Microsoft Common Data Model and
thus helping with semantic integration
across the enterprise
• Is helping to unify customer data and
orchestrate the customer journey across
touch points and channels
• Is enabling better AI because of more
and better data
LOB
Geo & Brand

7. Omni-channel
support
Sales
ServiceMarketing
Lead generation
Campaigns
Website
Content
Next best
action
Cross-sell/upsell
Recommendations

8. Attract, convert, and retain customers
Personalize customer journey
Gain a 360° view of customers
Unify customer data (transactional, behavioral, demographic)

9. Channels of
engagement
Power BI
Microsoft Flow
PowerApps
Process optimization
and automation
Internal External
CONNECTORS
Data ActionInsights
Analytics
AI and ML
Unification
Conflate Enrich
Ingest Map and Match

10. Ingestion
Bring customer
and activity data
from all sources
Mapping and
matching
Identify and
understand profile
data from
transactional and
observational
sources
Conflation
Consolidate data
into a single
customer profile
with source lineage
Enrichment
Enrich profiles using
AI models and
proprietary signals
from Microsoft
Graph
Insights
Derive insights that
automate and
optimize processes
Action
Leverage insights
across all channels
of engagement
with connectors
and APIs

11. Ingestion
Bring customer
and activity data
from all sources
Mapping and
matching
Identify and
understand profile
data from
transactional and
observational
sources
Conflation
Consolidate data
into a single
customer profile
with source lineage
Enrichment
Enrich profiles using
AI models and
proprietary signals
from Microsoft
Graph
Insights
Derive insights that
automate and
optimize processes
Action
Leverage insights
across all channels
of engagement
with connectors
and APIs

12. Ingest
Conflate Enrich
Map and Match
Unification

14. Ingestion
Bring customer
and activity data
from all sources
Mapping and
matching
Identify and
understand profile
data from
transactional and
observational
sources
Conflation
Consolidate data
into a single
customer profile
with source lineage
Enrichment
Enrich profiles using
AI models and
proprietary signals
from Microsoft
Graph
Insights
Derive insights that
automate and
optimize processes
Action
Leverage insights
across all channels
of engagement
with connectors
and APIs

15. Insights

16. Insights

17. Insights

18. Ingestion
Bring customer
and activity data
from all sources
Mapping and
matching
Identify and
understand profile
data from
transactional and
observational
sources
Conflation
Consolidate data
into a single
customer profile
with source lineage
Enrichment
Enrich profiles using
AI models and
proprietary signals
from Microsoft
Graph
Insights
Derive insights that
automate and
optimize processes
Action
Leverage insights
across all channels
of engagement
with connectors
and APIs

19. Action

20. Insights

21. Insights

22. Action

24. Omni-channel
support
Sales
ServiceMarketing
Lead generation
Campaigns
Website
Content
Next best
action
Cross-sell/upsell
Recommendations

25. Traditional customer analytics
Custom build on analytics platform
Hard coded
Hard to adapt
Siloed apps
Time to implement measured in months
Requires deep technical expertise
Different stacks for storage, KPI calculations, ML,
app experiences
Compliance as an afterthought
Dynamics 365 Customer Insights
Finished SaaS solution
Configurable
Extensible
Insights embeddable into operational CRM of
choice
Time to implement measured in weeks
Ready to run by business users
Integrated in one finished solution based on
hyper-scale cloud platform
Compliant by design

27. …

30. Customer
Insights
DATA
INGESTION
WITH
DATAFLOW
1
• Data unification
• Measures
• Segmentation
• Visualization
• Intelligence
Unified (big) customer data
transactional + behavioral
Internal + external
AML
Dynamics 365 Azure
TRAINING
SCORING
Data is stored in ADLS Gen 2
in Microsoft Subscription
D365 CE
• Marketing
• Sales
• Service
• Market Insights
• Sales Insights
• Service Insights
CDS
Transactional data
CDS
CONNECTOR
Data source 1
Data source 2
Data source N
SEGMENT
EXPORT

31. Customer
Insights
• Data unification
• Measures
• Segmentation
• Visualization
• Intelligence
ADLS
Unified (big) customer data
transactional + behavioral
Internal + external
Data source 1
Data source 2
Data source N
AML
• Campaign Management
• Sales
• Customer Service
• ...
Dynamics 365 Azure 3rd party
DATA INGESTION
WITH DATAFLOW
TRAINING
SCORING
ACTIVATION
Data is stored in ADLS Gen2
in a Microsoft subscription
2

32. AML
DATA INGESTION
WITH ADF OR OTHER
3
Customer
Insights
• Data unification
• Measures
• Segmentation
• Visualization
• Intelligence
Unified (big) customer data
transactional + behavioral
Internal + external
Data source 1
Data source 2
Data source N
• Campaign Management
• Sales
• Customer Service
• ...
Dynamics 365 Azure 3rd party
TRAINING
SCORING
ACTIVATION
Data is stored in customer
own Azure Subscription
ADLS
READ/WRITE