Savvy Leaders of Business Transformation and Competitive Advantage strategies are leveraging Artificial Intelligence (AI) and Machine Learning (ML) to deliver valuable insights and operational intelligence that help them prepare to be digital, understand their customers, and drive revenue growth in real-time.

1. 1© Cloudera, Inc. All rights reserved.
Using AI and ML to
Engage Customers and Drive Growth

2. 2© Cloudera, Inc. All rights reserved.
• Introductions
• AI/ML Overview and Challenges
• AI/ML Adoption Trends and Successes
• Leveraging AI and ML to Engage Customers and Drive
Growth
• Using the Cloudera Platform
• Success Stories and Use Cases
• SightPrism Demo
• Q&A
Agenda for Today’s Webinar

3. 3© Cloudera, Inc. All rights reserved.
Today’s Speakers
James Jeude
Vice President and Practice
Leader – Analytics and
Artificial Intelligence
David Larson
Business Insights Platform
Solutions Lead
Sean Anderson
Solutions Marketing –
Customer 360

4. 4© Cloudera, Inc. All rights reserved. 4© Cloudera, Inc. All rights reserved.
Cloudera at-a-glance
Customer success
Large enterprises fueling growth
48% 140%+
customer growth net expansion
Last 4 years
Global 8000
customers
Expansion driven
by data and new
use cases
Openpartner
network
Best of breed solutions
3000+
partners
Vast ecosystem
of solution &
service providers
Firsttomarket
Open source innovation
2008
founded
1600+
Clouderans
Global team doing
business in
28 countries
Big data innovators
from Google,
Yahoo and Oracle

5. 5© Cloudera, Inc. All rights reserved.
We deliver
the modern platform for machine learning and
analytics optimized for the cloud
ENTERPRISE GRADE
 Secure
 Performant
 Compliant
SCALABLE
 Elastic
 Cost-effective
 Lower TCO
RUNS ANYWHERE
 Cloud
 Multi-cloud
 On-premises

6. © 2017 Cognizant6
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Founded
in 1994 (CTSH, Nasdaq)
Headquarters
Teaneck, NJ
100+ Global
Delivery Centers
~256,800
Employees
Revenue
$13.49B in 2016
$7.21B in H1 2017
Revenue Mix
NA: 77.8%
Europe: 16%
RoW: 6.5%
OUR OVERVIEW
Newsweek’s
2015 World Green
Rankings
Forbes
Fast Tech 25
Fortune’s
Most Admired Companies
Years in a Row
Forbes
Global 2000
Fortune
500
Financial Times
Global 500
Cognizant (NASDAQ-100: CTSH) is one of the
world’s leading professional services companies,
transforming clients’ business, operating and
technology models for the digital era. Our unique
industry-based, consultative approach helps
clients envision, build and run more innovative and
efficient businesses. Headquartered in the U.S.,
Cognizant is ranked 205 on the Fortune 500 and is
consistently listed among the most admired
companies in the world.

7. 7© Cloudera, Inc. All rights reserved.
Cognizant and Cloudera deliver innovative and transformational business
solutions to clients. Together, we help clients perform better through a range of
integrated analytics and solutions based on Cloudera Enterprise.
We create an end-to-end blend of business and technology—including AI and
ML—solutions that reflect the future of analytics and data management and
deliver transformational value.
About the Cognizant and Cloudera Alliance
Offerings
 SightPrism
 BigFrame
 BigDecisions
40+ joint customers in
several industries,
including: banking and
finance, pharmaceutical
and life sciences,
information services,
consumer products,
insurance, and
automotive
30+ completed
Cloudera
implementations
Data Impact Award
winner for
excellence and
innovation in Big
Data application.
D&B, UBS, and
Credit Suisse

8. © 2017 Cognizant
An Intelligent Business rethinks every interaction
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Intelligent Experiences
CUSTOMERS
Intelligent Defense &
Compliance
EXTERNAL THREATS &
AUTHORITIES
Intelligent Offerings
PRODUCTS and
SERVICES
Intelligent Processes
BUSINESS
OPERATIONS
Intelligent Business

9. © 2017 Cognizant
Employers are investing in skills …
9

10. © 2017 Cognizant
… while AI is catching up on ‘intelligence’
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11. © 2017 Cognizant
Focus on “Thinking” - we start with the definition of AI
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AI is an area of computer science that
focuses on machines that learn.*
The “Intelligence” means implementation of human thinking.
The “Artificial” allows a scale and reach that will transform
everything we know about personal and business life.
* Malcolm Frank, Paul Roehrig and Ben Pring.
“What to do When Machines Do Everything.”

12. © 2017 Cognizant
How can a “Machine that Learns” transform the world?
Machine Learning (ML)
Traditional Programming = Rules AI = Learn by Example
You must know the answer in advance AI learns from experience
5

13. © 2017 Cognizant
So, if Machines can Learn, what is the role of business?
Who is doing the
teaching?
How do you give AI good
examples to learn from, and not
bad?
And how does AI
return the wisdom
of its thinking?
6

14. © 2017 Cognizant
Identify AI business opportunities to embrace the AI future
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What data flows in to AI? Where does
it come from?
Is there an AI platform and computing
power for AI?
Machinery
Material
Three M Model
How does AI fit into business process?
How does AI make money?Model
Master the Three M model to identify your AI opportunities

15. © 2017 Cognizant
Challenges in executing the “Three M” Model
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Is the data organized, cleaned, and
available?
Does the platform have sufficient
computing power?
Machinery
Material
Challenges
to the
Three M Model
Is the cost attractive? Can the results
get where needed, quickly?Model
Cloudera to the rescue!

16. © 2017 Cognizant
AI Adds Value in Many Ways
1. Reduce costs
2. Improve product and service quality
3. Introduce new experiences and new
revenue
4. Improve safety and quality of life
5. Improve society
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17. © 2017 Cognizant17
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AI Challenges – the downside …
Complete reliance on AI for decisions can cause irrecoverable damage
including loss of lives & reputation in the industry
Ethical question: A car accident involving
potential loss of life is inevitable. Does the car
hit two adults or one child?
Anomalies! Self-driving cars accident rates are
5X that of human-controlled cars… because
they cannot bend or break traffic laws as
human drivers regularly do.
Artificial Intelligence
needs a human touch!
KID?

18. © 2017 Cognizant18
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… and more examples
Lack of human touch (emotions) can cause irrational decision
making
If we need AI to
supervise AI,
who’s watching
that AI?
Threat to
Out-of-
control
Feedback
Loops

19. 19© Cloudera, Inc. All rights reserved.
Trends in AI/ML

20. 20© Cloudera, Inc. All rights reserved.
Age of Machine Learning
20
Cost of compute
Data volume
Time
Machine
Learning
NO
Machine
Learning
1950s 1960s 1970s 1980s 1990s 2000s 2010s

21. 21© Cloudera, Inc. All rights reserved.
Spark Use Cases
Top Use Cases Data Processing (55%), Real-Time Stream
Processing (44%), Exploratory Data Science (33%) and
Machine Learning (33%).
3 out of 8 are employing Spark in data science research

22. 22© Cloudera, Inc. All rights reserved.
PATTERN
RECOGNITIO
N
ANOMALY
DETECTIO
N
PREDICTION
SELF-SERVICE
INTELLIGENCE
SECURE
REPORTING
REAL-TIME
ANALYTICS
MACHINE LEARNING ANALYTICS
Enterprise-proven machine learning and analytics
700+CUSTOMERS RUN
ON
750+CUSTOMERS RUN
ON

23. 23© Cloudera, Inc. All rights reserved.
C360 and Required Capabilities

24. 24© Cloudera, Inc. All rights reserved.
Customer 360 – Key Use Cases
Churn Prevention & Customer
Retention
Targeted Marketing & Personalization
Proactive Care
• Churn Modeling & Prediction
• Rotational/ Social Churn
• Customer Lifetime Value
• Sentiment Analytics
• Price Elasticity Modeling
• Customer micro-segmentation
• Next Best Offer
• Campaign Analytics
• Geo-Location Analytics
• Recommendation Models
• Proactive Care Dashboard
• Customer Lifetime Value
• Subscriber Analytics
• QoS Analytics
• Real-Time Alerts
Campaign Optimization
• Customer micro-segmentation
• Retention
• Up-Sell
• Geo-Location Analytics
• Campaign Analytics

25. 25© Cloudera, Inc. All rights reserved.
Customer 360 Journey
• Marketing Systems
(Salesforce, Omniture, CRM)
• Clickstream Data
Primary
Data Source
• Clickstream
• NPS Systems
• Support Call Logs
• Social Feeds
Primary
Data Source
Understand Your Customer Learn Behaviors Improve Interactions
• Shopping Cart Platforms
• Geolocation
Primary
Data Source

26. 26© Cloudera, Inc. All rights reserved.
How to Iteratively Build a True Customer 360?
Customer
Data Source
Start with ingesting the
“best” version of your
customer profile
Find your common
identifiers across
datasets: customer
name, number, IMEI,
IMSI
IMEI
ChannelsPurchase History
Add New Data SourceCommon IdentifierCurrent Source
Enrich with additional
demographic information
(purchase history or channels)
from other systems / sources
Deliver A Use Case
Deliver a specific use case based
on the profile with new data
sets:
• Customer Lifetime value
• Next Best offer
• Omni Channel
Enrich Your Profile
• Enrich your customer
profiles with purchase
behavior
• Continue to enhance
with each new use case
Location Clickstream
Continue to add new data sources iteratively to
enhance your customer profile with new use cases
Call center
Social Media Apps
External
Data
New Data Sources
OPERATIONS
Cloudera Manager
Cloudera Director
DATA
MANAGEMENT
Cloudera Navigator
Encrypt and KeyTrustee
Optimizer
BATCH
Sqoop
REAL-TIME
Kafka, Flume
PROCESS, ANALYZE, SERVE
UNIFIED SERVICES
RESOURCE MANAGEMENT
YARN
SECURITY
Sentry, RecordService
FILESYSTEM
HDFS
RELATIONAL
Kudu
NoSQL
HBase
STORE
INTEGRATE
BATCH
Spark, Hive, Pig
MapReduce
STREAM
Spark
SQL
Impala
SEARCH
Solr
SDK
Partners

27. 27© Cloudera, Inc. All rights reserved.
Cloudera Enterprise – The Platform for Customer 360
Location
Social
Clickstream
BI Tools
Online & Mobile Apps
Billing/
Ordering
CRM/ Profile
Marketing
Campaigns
Search
EDW
N/W Logs
Call Center
Apps
Network
Other Structured
Sources
Internal Systems External Sources
BI Solutions Real-Time AppsSearch Data Science
Workbench
SQL
Machine
Learning
Systems Data
OPERATIONS
Cloudera Manager
Cloudera Director
DATA
MANAGEMENT
Cloudera Navigator
Encrypt and KeyTrustee
Optimizer
BATCH
Sqoop
REAL-TIME
Kafka, Flume
PROCESS, ANALYZE, SERVE
UNIFIED SERVICES
RESOURCE MANAGEMENT
YARN
SECURITY
Sentry, RecordService
FILESYSTEM
HDFS
RELATIONAL
Kudu
NoSQL
HBase
STORE
INTEGRATE
BATCH
Spark, Hive, Pig
MapReduce
STREAM
Spark
SQL
Impala
SEARCH
Solr
SDK
Partners

28. 28© Cloudera, Inc. All rights reserved.
Key Enabling Capabilities
Ideal for real-time analytics on
IoT and time series data.
Simplifies Lambda architectures
for running real-time analytics on
streaming data
Leading analytic SQL engine
running natively in Hadoop. Impala
provides the fastest insights, at
high-concurrency, with the familiar
access necessary for powering BI
and analytics across the business.
Kudu: Real-Time Offers Impala: Self Service BI Data Science Workbench
Collaborative hub for enterprise
data science and an integrated
development environment for
running Python, R, & Scala with
support for Spark

29. 29© Cloudera, Inc. All rights reserved.
Published research subscription service
Delivers cutting edge advances in applied ML / AI
Accelerates adoption in large enterprises
Drives demand for our platform
Applied research for machine
learning and data science
Continued machine
learning innovation
29© Cloudera, Inc. All rights reserved.

30. 30© Cloudera, Inc. All rights reserved.
Open, best-of-breed
platform ecosystem
SI and resellers
Software & OEM
Data Systems
Platform & cloud

31. 31© Cloudera, Inc. All rights reserved.
Business Value Outcome Case Studies
Machine Learning Recommender
System for Next Best Call @ Top 5 US
Bank
Intelligent Alignment of Call Targets
@ Global Life Sciences Company
Using Machine Learning to Drive
Revenue @ a Top Cosmetics Retailer
• Lack of data integration
• 25% of a CSRs time spent trying to decide
next best call to make
• Need to improve CSAT
• Align and optimize Agent size and target lists
lists for improved quality of interactions
• Grow high-value Customers captured during
Web browsing
• Focus on Shopping Cart conversations,
Upsell, Cross-Sell using Hyper-Personalization
Personalization
• Daily Customer and Call log data
consolidation
• Machine Learning models to determine and
emerge targeted and personalized
interactions
• UI / UX development
• Modeled Physician activity through digital
and Call Center interactions
• Differential receptivity and responsiveness
analyses for target call intensity measures
• Smart AI alignment of call staff to targets
based on geography, specialty, and value
• Created multi-sourced, multi-dimensional
view of marketplace and Customers
• Unsupervised Machine Learning to identify
Customers Segments
• Associate Mining to quantify product
association of Customer segments
• 15% more calls made after implementation
with increased conversation rates
• Transitioned 70,000+ doctors to a digital /
Call Center sales support approach, without
losing any market share, saving 70% of
promotional costs
• 23% increase in Shopping Basket
conversations and a 6% increase in annual
sales through Upsell and Cross-Sell
SituationSolutionOutcomes

32. 32© Cloudera, Inc. All rights reserved.
SightPrism™ provides actionable insights across the
Omni-Channel Customer analytic ecosystem
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Omni-Channel Journeys
 View the Customer Journey as
they experience it. Understand
their behavior, key influencers,
challenges, unmet needs at
various touchpoints
 Provides valuable insight on
how Customer Experience can
be improved
KPIs to Track
 Identify the factors which
effect business impact and
need active monitoring
 Become more agile in
responding to needs of the
quickly evolving Customer
Digital “Halos”
+
Actual Reality Differentiation
 Code Halos are recoding the
Customer Experience by making
meaning from the digital
information that surrounds
people, organizations and
devices
 Actual Reality adds unique
insight and perspective
Analytics for Intelligent
Personalization
 Create an action plan on how to
generate insights from data
collected from various touch
points coupled with internal
data, using analytics, and
thereby enhancing Customer
Experience

33. 33© Cloudera, Inc. All rights reserved.
What Next?

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Solutions
Gallery

35. 35© Cloudera, Inc. All rights reserved.
Q&A

36. 36© Cloudera, Inc. All rights reserved.
Thank you
James Jeude – james.jeude@cognizant.com | https://www.linkedin.com/in/james-jeude-b84672/
David Larson – david.larson@cognizant.com | https://www.linkedin.com/in/davidalarson
SeanAnderson – sanderson@cloudera.com | https://www.linkedin.com/in/sean-anderson-41479b17/