This document discusses how various emerging technologies can impact marketing and customer engagement. It provides examples of using social listening and analytics to generate sales leads. Key points include: 1) Technologies like IoT, AR/VR, AI and social media are changing how marketing works and allowing more personalized interactions. 2) Social media provides opportunities to better understand customers, engage them, build the brand and generate recommendations. 3) By tracking M&A rumors on social media and linking it to a CRM system, a company can identify potential sales leads and notify the relevant account managers. 4) The process involves analyzing social data using NLP to extract deal details, checking against existing databases, merging with CRM

2. Cloud AI
Mobile Sharing
Make IOT
Social Human
Interact.
AR / VR
How does this change Marketing?

4. IOT & Sharing

6. Augmented Reality & AI

8. Social & AI

9. Insurance
cross-sell
Sports club
fan club

10. Marketing Targets
Other
Prospects
Customer
Posts
Social Media
Social
Query
Segment
Criteria
Scored
contact
Traditional
Segment
Criteria

11. Personalized
Interactions
Customers
Social
Segmentation
Microsoft Azure

13. Social & AI

14. Social: Biggest Opportunities - FIS
Customer Experience
Understand your customers
User expectations
Trends & Innovations
Learn from Competitors
Customer Engagement
Customer self-service
Social Media Marketing
Brand reputation & presence
Social campaigns
Consumer recommendations
Nurturing of Influencers
New Business
Models
Crowd sourced models
P2P lending
P2P Micropayments
Community Banking
Long tail
Risk
Management
Discover market and
customer risks in real
time
HR
A great place
communicate your
messages and spot
for top talents
Collaboration
Internal collaboration
to maximize the
network and
knowledge
Analytics &
Big Data
Generate actionable
signals and support
business decisions

15. 16
Lead Generation for Ernst &
Young – Transaction
Advisory Services
Push deal alerts to sales by tracking
and analyzing M&A rumors
connected to the CRM system
Example: Ernst & Young – Lead Generation
Merger
Acquisition
Investment
Seller
Deal Volume
Buyer
Target
Broker

16. Magic ? CRM System
Account – Sales
Relation
Social
Listening/Analytics
API
Data
Posts
Tweets
Rewteets
Likes
Shares
Sales Team
Actions
Phone CallsSignal Detection
Grouping
Distribution

17. Get
the data
1
STEP Analyze
the data
2
STEP Identify the
sales person
3
STEP Deliver deal
alert
4
STEP
►
Social listening/
monitoring to detect
and collect the data
►
Natural Language
processing to identify
target, buyer, deal
volume in the text
►
Create an M&A Event
►
Check with existing M&A
databases if case is
already identified
►
Merge with CRM data
to find out who is
responsible for that
account
►
Send mail/notification
and create and
opportunity

18. Analyze
the data
2
STEP
►
Natural Language
processing to identify
target, buyer, deal
volume in the text
►
Check with existing
M&A databases if case
is already identified
►
If not – you have a
rumor
Entry
Buyer Microsoft
Target Skype
Dealvolume n.a.
Post
«Microsoft may take over Skype»

19. Analyze
the data
2
STEP
►
Natural Language
processing to identify
target, buyer, deal
volume in the text
►
Check with existing
M&A databases if case
is already identified
►
If not – you have a
rumor
Entry
Buyer Microsoft
Target Skype
Dealvolume n.a.
Post
«Microsoft may take over Skype»
Post
«Microsoft buys Skype for 8.5 b$ »
Entry
Buyer Microsoft
Target Skype
Dealvolume 8.5 b $
Event
Buyer Microsoft
Target Skype
Dealvolume 8.5 b $

20. Analyze
the data
2
STEP
►
Natural Language
processing to identify
target, buyer, deal
volume in the text
►
Check with existing
M&A databases if case
is already identified
►
If not – you have a
rumor
Event
Buyer Microsoft
Target Skype
Dealvolume 8.5 b $
M&A Database
Buyer Microsoft
Target Skype
Dealvolume 8.5 b $
If not included  may be a rumor
?

21. Identify the
sales person
3
STEP
►
Merge with CRM data
to find out who is
responsible for that
account
Event
Buyer Microsoft
Target Skype
Dealvolume 8.5 b $
Rumor yes
CRM
Account Microsoft
Sales Max Higgs
Email m.higgs@contoso.com

22. CRM System
Account – Sales
Relation
Social
Listening/Analytics
API
Magic ?
Data
Posts
Tweets
Rewteets
Likes
Shares
Sales Team
Actions
Phone CallsSignal Detection
Grouping
Distribution
Magic ?
 API’s
 Natural Language
Processing
 Machine
Learning/Rule based

23. Personalized | Proactive | Predictive
Customer
engagement

24. API
Marketing Apps
Dynamics Marketing
Microsoft Social Engagement
Dynamics CRM

25. Transparent
Connected
Augmented
Creativity
Data Driven & Predictions
Automation & Integration
Human interactions
Trust
Personalized
Empowered

27. Questions ?Questions?