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Innovations
from Retail
What Travel Can Learn
About Big Data,
Social Media & Customer
Analytics
Webinar
November 14, 2013
© 2013 IBM Corporation
Your hosts

K

Kevin May
Editor & Moderator

2

Gene Quinn
CEO & Producer

© 2013 IBM Corporation
Your panelists

K

Kurt Wedgwood
Travel & Transportation
Big Data Consultant
IBM

3

Tzaras Christon
EVP, Industry Sales
& Marketing
Aginity

© 2013 IBM Corporation
Big Data for the Travel & Transportation Industry

Innovations from Retail: What Travel Can Learn
About Big Data, Social Media & Customer
Analytics

Tzaras Christon
EVP
tchriston@aginity.com

Kurt Wedgwood
Big Data Consultant
wedgwood@us.ibm.com

© 2013 IBM Corporation
Poll no. 1
What role do you serve in the organization?
K

5

© 2013 IBM Corporation
Today's Objectives
Objectives

Agenda

 Benchmark T&T adoption in Big

1. T&T: Big Data Adoption Curve

Data
 Reveal leading edge learning from
Retail

 Provide ideas for action

2. T&T: Focus & Need in Big Data
3. Retail Learning: Optimizing around the
Customer Journey
4. Retail Learning: Real Challenges to
Capturing the Value
5. Retail Learning: Analytic Management
Platform
6. T&T: What’s next and how to get started
7. Q&A

6

© 2013 IBM Corporation
The Travel and Transportation industry is broad
Railroads

Freight Logistics

Travel Related
Services

Airport
Authorities

Passenger Rail

Maritime
Container
Shipping

Hospitality

Air Cargo

Airport
Management
Companies

Freight Rail

Trucking

Car Rental

Airline Service
Providers

Airport Service
Providers

Passenger
Terminals

Parcel Delivery

Global
Distribution
Systems (GDS)

Freight Rail
Terminals

Logistics Service
Providers

Cruise Lines

Ports and
Terminals

Travel Agencies /
Tour Operators

Airlines

Airports

Passenger
Airlines

Casinos
7

© 2013 IBM Corporation
Poll no. 2
What industry segment do you represent?
K

8

© 2013 IBM Corporation
A recent IBM/Oxford study highlights how
organizations are adopting big data
Big data adoption

Total respondents n = 1061
Totals do not equal 100% due to rounding

9

© 2013 IBM Corporation
Poll no. 3
When will your organization be in the engage stage?
K

10

© 2013 IBM Corporation
How much does your success rely on identifying and
serving emerging trends in this new landscape
45 of the top 100 global cities
will be in China by 2025, by
real GDP growth

62% growth rate of
unstructured data in the
enterprise, vs. 22% overall
enterprise data growth

80% of new applications
will include cloud delivery
or deployment

11

2:1 ratio of working age to
dependent population in
India, China, Japan, US,
Europe;
declining to ~1.5:1 by 2050

6.8 billion mobile phone
subscriptions worldwide

90% of data on the planet
was created in the past
two years alone

93% growth in number
of cyber attacks
since 2005

16 petaflop
computational speed
of IBM Sequoia
supercomputer

60% growth of spending
on marketing analytics
over the next 3 years

© 2013 IBM Corporation
Retail companies have focused on investments in growing
new revenue and connecting with customers

1
2
3
4
5
6
7

IT initiatives
that can grow
revenue and
increase
customer
intimacy

8
9
10

Source: IBM Institute for Business Value Analysis, “trends and Impacting technologies”, John Cato Gartner

12

© 2013 IBM Corporation
Travel & Transport Imperatives

Maximize availability
of assets and
infrastructure

Dramatically improve
the end-to-end
customer experience.

Travel &
Transportation

Improve operational
efficiency and reduce
environmental impact

13

Enhance services to
increase revenue and
manage capacity

© 2013 IBM Corporation
The Opportunity:
Optimizing the business around the Customer
Attributes that drive the Customer Journey

Industry Point of View: CEO
priority is Customer Insight

14

Our Experience: Optimizing on the
Right Journey Attributes Yields
>20% lift

© 2013 IBM Corporation
Capabilities:
3 Quantum's Customer Experience Optimization
Identify Me
Optimize the Touch
Point/Execution

Know Me
Optimize your data

Understand Me
Optimize the Journey Purpose
By Customer’s Personas

Pleasure

Pleasure Family

Business (Solo)

Business (Group)

15

© 2013 IBM Corporation
The Problem:
Digital Interaction Data is Growing

Mobile

Social

1.1B Smartphone Users
+92% Y/Y Internet Usage
>80% is App Usage

Search

Compare

972MM Users
+8% Y/Y

Gaming

130MM Users
+15% Y/Y

16

Pinterest

17MM Users
> +40x Y/Y

1.15B Users
+41% Y/Y

Commerce

51MM Users
+25x Y/Y

In-store Wireless Information Sharing
485MM Visitors
+40% Y/Y
90% of Retails plan to
improve the in-store
experience with Wifi in
the next 18 months

© 2013 IBM Corporation
The Problem:
Media, Customer and Transaction Data aren’t connected
Millions Of Attributes in the Journey…
Demographic
data

Attribut
es

Transacti
ons

ChainScale
History

Transaction
data
Guest
Purchas
es

Demographics

Characteri
stics

Booking
time to
Travel

Needs

Companion
types

E-mail /
Chat

Desires

Call
center
notes

Prefer
ences

Behavioral
data

17

Opinion
s

Inperson
dialogs

Web
clickstreams

Interaction
data

But which ones are
predictive of
opportunity and
risk?
•
•
•
•
•

Combination
Weight
Order
Timing
Execution
Context

© 2013 IBM Corporation
The Problem:
Time Spent on Low Value
Data
Prep
1

Poor Customer Identification

2

Siloed Data by Function, Division or BU

3

IT waterfall dictates business agility

4

Analytics isolated to reporting or “in application”

5

Analysis is one off and not extensible to ultimate
value

6
7

18

Disconnected from execution systems
Scare analytic resources focused on
overcoming IT hurdles

Smart
Analytics

“There was a 15,000% increase in job
postings for data scientists between
summer 2011 and summer 2012, which
spanned across all industries including
retail, banking, healthcare and airlines”
- HBR Sept 2012

© 2013 IBM Corporation
The Problem:
You Face A Fragmented Solution Landscape

19

© 2013 IBM Corporation
The Solution

POS

CoreMetrics

Metadata
Manager

ESP/
eMessage

Publisher

Customer
Insight Appliance (CIA)

Communication Channels
Campaign Management
IBM Campaign/
IBM Interact

An Analytic Management Platform
(AMP) that connects a three
dimensional view of your
customer to marketing execution
systems

Smarter
Commerce

Data Sources

Big Insights
(Hadoop)

Customer Analysis

Analytic
Manager
Customer Insights
and Reporting
(Cognos)
Presence
Zones

20

SPSS
Modeler

© 2013 IBM Corporation
The Solution:
Analytic Management Platform – Ending Fragmentation
CONNECTORS
Corporate EDW

Reporting and
Customer
Applications

• Analytics running at 10X
traditional methods
Marketing
Execution

• 50% reduction in IT cost

Big Insights

• Full Connected in 90 days

Customer
Experience
Management
.

21

• Actionable Insights in 2
weeks
Data
Management

Predictive Analytics

© 2013 IBM Corporation
Example 1: Large Eyewear Retailer
Challenge
• The client lacked a 3D view into its customer and product purchases across 9 Retail Brands online
and offline
• Product, sales and customer data was managed by multiple agencies and vendors.

Solution
• CIA deployed to create a connected Analytic driven enterprise: All customer data sources, analytic
functions and execution systems were connected in 89 days .
• Now segments and scoring of customers down to the individual level isolating the most critical
attribute to take action upon based on thousands of behavioral attributes

Result
Operational in 89 days
• 3 countries
• 10 years of customer data
• 9 different retail brands
• Custom KPI reports
• All powered by a couple
hundred indicative
customer behavioral
attributes

22
22

© 2013 IBM Corporation
Example 2: Finding Attributes that drive your business
CIA Standup  Predicting 95% of Path to Purchase: 3 Weeks






3 Brands: 4 Products
5 data sources
1710 total attributes (150 predictors)
3 weeks to load data, create
attributes, rank, model and score
Iterative adaptation with no data silos
Data mapping and load

Create Attributes

23

Rank Attributes

Implementation Timeline

Create Interaction Reports and Attribute
Heat Maps

Model Purchase Paths

Plot Audience on Purchase Paths

© 2013 IBM Corporation
Predicative Patterns that drive Prescription
Purchased Model x

Automobile 1
95% of Model X Purchasers Follow 1 of 4 Paths
61-90 days
65%

46-60 days

Price
sensitivity

31-45 days
Unique
models
attribute

Model
Focus

16-30 days
Peak
sessions*

11-15 days
Sessions
drop

6-10 days
Sessions
flat

0-5 days
Session
peak

Large number of makes and models viewed, search on new and used, consider used brand

12%

Purchased
model

Brand

Sessions
drop

Session,
Search
and view
volume

NonDealer
sites

Purchased
model

Narrow number of makes and models, very low brand interaction

9%

Unique
model
views, pric
e

High search,
views,
unique
models

Search, vi
ew, model
s, price

Search, v
iews

Product

Price sensitive throughout search, visiting all dealers

9%

Search
volume,
1st time
views

Search,
unique
models

Search,
view,
dealers

Search, vi
ews, Price

High view count, Looking at all dealers

* Red text indicates make/model decision point

24

© 2013 IBM Corporation
Example 3: Apparel Retailer - Segmentation and
Optimization During Peak Season

Challenge

Solution

Benefits

 Blanket Marketing lacked
relevance and effective
conversion

 Aginity/IBM CIA System: Multiterabyte Customer Marketing
Solution with clickstream data
(Omniture), sales and customer
data

 200-400% increased
conversion

 Relevance: Over 200,000 unique
offers, increasing conversion and
retention

 Met Holiday Targets: Retailer
executed on promise to
positively impact the holiday
season bottom line

 Needed quick project setup to hit
projections in fast-approaching
Holiday season
 Online project had been stalled
for 5 months in jeopardy of
missing deadlines
25
25

2
5

 $14MM+ revenue in 4 weeks
over holiday

 79 Day Implementation
© 2013 IBM Corporation
Digital ambitions:
CMOs want to put the components of a strong digital
strategy in place

Source: IBM Institute of Business Value: CXO Study, 2013

26

© 2013 IBM Corporation
Voice over the board:
CEOs say customers come second only to the C-suite in
terms of the strategic influence they wield

“As customers gain more power over the
business via social media, their
expectations keep rising and their
tolerance keeps decreasing.” – CIO, Retail

Source: IBM Institute of Business Value: CXO Study, 2013

27

© 2013 IBM Corporation
Taking the next step with your strategy and execution
Big data adoption

Educate

Explore

Engage

Execute

Focused on knowledge
gathering and market
observations

Developing strategy
and roadmap based on
business needs and
challenges

Piloting big data
initiatives to validate
value and requirements

Deployed two or more
big data initiatives and
continuing to apply
advanced analytics

Join the business
community
Big data case
studies, whitepapers, book
s, and
IBM Institute for Business
Value reports
ibmbigdatahub.com

Blog
http://www.ibm
bigdatahub.co
m/blog/author/
kurt-wedgwood

Self-paced learning, exploration
with downloads & test environment
BigDatauniversity.com, YouTube Big Data
Channel

IBM
Readiness
Assessment
for Big Data
-Prioritized
business use
cases
-Recommend
big data
platform

Solution Design &
Custom Demo
-Validate business value of
the big data use case
-Demonstrate big data
capabilities to execute use
case

Enterprisewide big
data
initiatives
-Incremental value across
multiple use cases
-Leverage investment
from re-using the same
big data platform
-Enterprise data platform
to support analytics

Join the technical
community

28

© 2013 IBM Corporation
Poll no. 4
K
What’s the major challenge holding back your adoption?

29

© 2013 IBM Corporation
Thank You

Please Continue the Dialog
Tzaras Christon
EVP, Industry Sales & Marketing

Big Data Consultant

tchriston@aginity.com

30

Kurt Wedgwood

wedgwood@us.ibm.com

© 2013 IBM Corporation
Q&A
K

31

© 2013 IBM Corporation
Thank You!
Replay and presentation from today’s webinar will be
K
available at www.tnooz.com
Please send your questions to kevin@tnooz.com

32

© 2013 IBM Corporation

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Big Data, customer analytics and loyalty marketing

  • 1. Innovations from Retail What Travel Can Learn About Big Data, Social Media & Customer Analytics Webinar November 14, 2013 © 2013 IBM Corporation
  • 2. Your hosts K Kevin May Editor & Moderator 2 Gene Quinn CEO & Producer © 2013 IBM Corporation
  • 3. Your panelists K Kurt Wedgwood Travel & Transportation Big Data Consultant IBM 3 Tzaras Christon EVP, Industry Sales & Marketing Aginity © 2013 IBM Corporation
  • 4. Big Data for the Travel & Transportation Industry Innovations from Retail: What Travel Can Learn About Big Data, Social Media & Customer Analytics Tzaras Christon EVP tchriston@aginity.com Kurt Wedgwood Big Data Consultant wedgwood@us.ibm.com © 2013 IBM Corporation
  • 5. Poll no. 1 What role do you serve in the organization? K 5 © 2013 IBM Corporation
  • 6. Today's Objectives Objectives Agenda  Benchmark T&T adoption in Big 1. T&T: Big Data Adoption Curve Data  Reveal leading edge learning from Retail  Provide ideas for action 2. T&T: Focus & Need in Big Data 3. Retail Learning: Optimizing around the Customer Journey 4. Retail Learning: Real Challenges to Capturing the Value 5. Retail Learning: Analytic Management Platform 6. T&T: What’s next and how to get started 7. Q&A 6 © 2013 IBM Corporation
  • 7. The Travel and Transportation industry is broad Railroads Freight Logistics Travel Related Services Airport Authorities Passenger Rail Maritime Container Shipping Hospitality Air Cargo Airport Management Companies Freight Rail Trucking Car Rental Airline Service Providers Airport Service Providers Passenger Terminals Parcel Delivery Global Distribution Systems (GDS) Freight Rail Terminals Logistics Service Providers Cruise Lines Ports and Terminals Travel Agencies / Tour Operators Airlines Airports Passenger Airlines Casinos 7 © 2013 IBM Corporation
  • 8. Poll no. 2 What industry segment do you represent? K 8 © 2013 IBM Corporation
  • 9. A recent IBM/Oxford study highlights how organizations are adopting big data Big data adoption Total respondents n = 1061 Totals do not equal 100% due to rounding 9 © 2013 IBM Corporation
  • 10. Poll no. 3 When will your organization be in the engage stage? K 10 © 2013 IBM Corporation
  • 11. How much does your success rely on identifying and serving emerging trends in this new landscape 45 of the top 100 global cities will be in China by 2025, by real GDP growth 62% growth rate of unstructured data in the enterprise, vs. 22% overall enterprise data growth 80% of new applications will include cloud delivery or deployment 11 2:1 ratio of working age to dependent population in India, China, Japan, US, Europe; declining to ~1.5:1 by 2050 6.8 billion mobile phone subscriptions worldwide 90% of data on the planet was created in the past two years alone 93% growth in number of cyber attacks since 2005 16 petaflop computational speed of IBM Sequoia supercomputer 60% growth of spending on marketing analytics over the next 3 years © 2013 IBM Corporation
  • 12. Retail companies have focused on investments in growing new revenue and connecting with customers 1 2 3 4 5 6 7 IT initiatives that can grow revenue and increase customer intimacy 8 9 10 Source: IBM Institute for Business Value Analysis, “trends and Impacting technologies”, John Cato Gartner 12 © 2013 IBM Corporation
  • 13. Travel & Transport Imperatives Maximize availability of assets and infrastructure Dramatically improve the end-to-end customer experience. Travel & Transportation Improve operational efficiency and reduce environmental impact 13 Enhance services to increase revenue and manage capacity © 2013 IBM Corporation
  • 14. The Opportunity: Optimizing the business around the Customer Attributes that drive the Customer Journey Industry Point of View: CEO priority is Customer Insight 14 Our Experience: Optimizing on the Right Journey Attributes Yields >20% lift © 2013 IBM Corporation
  • 15. Capabilities: 3 Quantum's Customer Experience Optimization Identify Me Optimize the Touch Point/Execution Know Me Optimize your data Understand Me Optimize the Journey Purpose By Customer’s Personas Pleasure Pleasure Family Business (Solo) Business (Group) 15 © 2013 IBM Corporation
  • 16. The Problem: Digital Interaction Data is Growing Mobile Social 1.1B Smartphone Users +92% Y/Y Internet Usage >80% is App Usage Search Compare 972MM Users +8% Y/Y Gaming 130MM Users +15% Y/Y 16 Pinterest 17MM Users > +40x Y/Y 1.15B Users +41% Y/Y Commerce 51MM Users +25x Y/Y In-store Wireless Information Sharing 485MM Visitors +40% Y/Y 90% of Retails plan to improve the in-store experience with Wifi in the next 18 months © 2013 IBM Corporation
  • 17. The Problem: Media, Customer and Transaction Data aren’t connected Millions Of Attributes in the Journey… Demographic data Attribut es Transacti ons ChainScale History Transaction data Guest Purchas es Demographics Characteri stics Booking time to Travel Needs Companion types E-mail / Chat Desires Call center notes Prefer ences Behavioral data 17 Opinion s Inperson dialogs Web clickstreams Interaction data But which ones are predictive of opportunity and risk? • • • • • Combination Weight Order Timing Execution Context © 2013 IBM Corporation
  • 18. The Problem: Time Spent on Low Value Data Prep 1 Poor Customer Identification 2 Siloed Data by Function, Division or BU 3 IT waterfall dictates business agility 4 Analytics isolated to reporting or “in application” 5 Analysis is one off and not extensible to ultimate value 6 7 18 Disconnected from execution systems Scare analytic resources focused on overcoming IT hurdles Smart Analytics “There was a 15,000% increase in job postings for data scientists between summer 2011 and summer 2012, which spanned across all industries including retail, banking, healthcare and airlines” - HBR Sept 2012 © 2013 IBM Corporation
  • 19. The Problem: You Face A Fragmented Solution Landscape 19 © 2013 IBM Corporation
  • 20. The Solution POS CoreMetrics Metadata Manager ESP/ eMessage Publisher Customer Insight Appliance (CIA) Communication Channels Campaign Management IBM Campaign/ IBM Interact An Analytic Management Platform (AMP) that connects a three dimensional view of your customer to marketing execution systems Smarter Commerce Data Sources Big Insights (Hadoop) Customer Analysis Analytic Manager Customer Insights and Reporting (Cognos) Presence Zones 20 SPSS Modeler © 2013 IBM Corporation
  • 21. The Solution: Analytic Management Platform – Ending Fragmentation CONNECTORS Corporate EDW Reporting and Customer Applications • Analytics running at 10X traditional methods Marketing Execution • 50% reduction in IT cost Big Insights • Full Connected in 90 days Customer Experience Management . 21 • Actionable Insights in 2 weeks Data Management Predictive Analytics © 2013 IBM Corporation
  • 22. Example 1: Large Eyewear Retailer Challenge • The client lacked a 3D view into its customer and product purchases across 9 Retail Brands online and offline • Product, sales and customer data was managed by multiple agencies and vendors. Solution • CIA deployed to create a connected Analytic driven enterprise: All customer data sources, analytic functions and execution systems were connected in 89 days . • Now segments and scoring of customers down to the individual level isolating the most critical attribute to take action upon based on thousands of behavioral attributes Result Operational in 89 days • 3 countries • 10 years of customer data • 9 different retail brands • Custom KPI reports • All powered by a couple hundred indicative customer behavioral attributes 22 22 © 2013 IBM Corporation
  • 23. Example 2: Finding Attributes that drive your business CIA Standup  Predicting 95% of Path to Purchase: 3 Weeks      3 Brands: 4 Products 5 data sources 1710 total attributes (150 predictors) 3 weeks to load data, create attributes, rank, model and score Iterative adaptation with no data silos Data mapping and load Create Attributes 23 Rank Attributes Implementation Timeline Create Interaction Reports and Attribute Heat Maps Model Purchase Paths Plot Audience on Purchase Paths © 2013 IBM Corporation
  • 24. Predicative Patterns that drive Prescription Purchased Model x Automobile 1 95% of Model X Purchasers Follow 1 of 4 Paths 61-90 days 65% 46-60 days Price sensitivity 31-45 days Unique models attribute Model Focus 16-30 days Peak sessions* 11-15 days Sessions drop 6-10 days Sessions flat 0-5 days Session peak Large number of makes and models viewed, search on new and used, consider used brand 12% Purchased model Brand Sessions drop Session, Search and view volume NonDealer sites Purchased model Narrow number of makes and models, very low brand interaction 9% Unique model views, pric e High search, views, unique models Search, vi ew, model s, price Search, v iews Product Price sensitive throughout search, visiting all dealers 9% Search volume, 1st time views Search, unique models Search, view, dealers Search, vi ews, Price High view count, Looking at all dealers * Red text indicates make/model decision point 24 © 2013 IBM Corporation
  • 25. Example 3: Apparel Retailer - Segmentation and Optimization During Peak Season Challenge Solution Benefits  Blanket Marketing lacked relevance and effective conversion  Aginity/IBM CIA System: Multiterabyte Customer Marketing Solution with clickstream data (Omniture), sales and customer data  200-400% increased conversion  Relevance: Over 200,000 unique offers, increasing conversion and retention  Met Holiday Targets: Retailer executed on promise to positively impact the holiday season bottom line  Needed quick project setup to hit projections in fast-approaching Holiday season  Online project had been stalled for 5 months in jeopardy of missing deadlines 25 25 2 5  $14MM+ revenue in 4 weeks over holiday  79 Day Implementation © 2013 IBM Corporation
  • 26. Digital ambitions: CMOs want to put the components of a strong digital strategy in place Source: IBM Institute of Business Value: CXO Study, 2013 26 © 2013 IBM Corporation
  • 27. Voice over the board: CEOs say customers come second only to the C-suite in terms of the strategic influence they wield “As customers gain more power over the business via social media, their expectations keep rising and their tolerance keeps decreasing.” – CIO, Retail Source: IBM Institute of Business Value: CXO Study, 2013 27 © 2013 IBM Corporation
  • 28. Taking the next step with your strategy and execution Big data adoption Educate Explore Engage Execute Focused on knowledge gathering and market observations Developing strategy and roadmap based on business needs and challenges Piloting big data initiatives to validate value and requirements Deployed two or more big data initiatives and continuing to apply advanced analytics Join the business community Big data case studies, whitepapers, book s, and IBM Institute for Business Value reports ibmbigdatahub.com Blog http://www.ibm bigdatahub.co m/blog/author/ kurt-wedgwood Self-paced learning, exploration with downloads & test environment BigDatauniversity.com, YouTube Big Data Channel IBM Readiness Assessment for Big Data -Prioritized business use cases -Recommend big data platform Solution Design & Custom Demo -Validate business value of the big data use case -Demonstrate big data capabilities to execute use case Enterprisewide big data initiatives -Incremental value across multiple use cases -Leverage investment from re-using the same big data platform -Enterprise data platform to support analytics Join the technical community 28 © 2013 IBM Corporation
  • 29. Poll no. 4 K What’s the major challenge holding back your adoption? 29 © 2013 IBM Corporation
  • 30. Thank You Please Continue the Dialog Tzaras Christon EVP, Industry Sales & Marketing Big Data Consultant tchriston@aginity.com 30 Kurt Wedgwood wedgwood@us.ibm.com © 2013 IBM Corporation
  • 31. Q&A K 31 © 2013 IBM Corporation
  • 32. Thank You! Replay and presentation from today’s webinar will be K available at www.tnooz.com Please send your questions to kevin@tnooz.com 32 © 2013 IBM Corporation

Hinweis der Redaktion

  1. Thank you Gene and Kevin for the introductions and to all of you for taking this hour out to join the webinar.To Open, we just wanted to share with everyone who is in the audience. Using you keyboard would you please answer the poll?
  2. upd
  3. We’d like to do our own Poll, here and see how it compares
  4. Doing a quick switch from retail to T&T, I wanted to call out what IBM has defined as our major Trav & Trans imperatives that are represented in one or many of our clients major strategic intiatives:Maximize availability of assets and infrastructureDramatically improve the end-to-end customer experience.Improve operational efficiency and reduce environmental impactEnhance services to increase revenue and manage capacityAs in the prior slide, we will focus on the customer, and you should know that BigData&analytics is central to all 4 of these imperatives.Tzaras, would you take our lead in going further into the Dramatically improve the end-to-end customer experience?
  5. Do we want to highlight the predictive prescriptive bubbles?Specify which data lives in the Corp DW & what is in the Mrkting DWAttributes
  6. Dark Gray = CIABlue = Connected systemsCIA is a marketing hub that brings disparate systems togetherWe are highlighting integration with a select list. This is A list of connections, not THE list of connections.Advance to see a list of typical integration pointsThe next slide is a duplicated slide to make the animations work right. If changes are made here, we will want to duplicate them there.
  7. Line through representing CIA that pulled everything together.
  8. Consider changing order in solution column…also what did they really do?
  9. Tzaras, thank you for the great examples. I believe you really captured how other companies are differentiating themselves in this enriched world of customer information.Tying to your last example, In IBM’s CXO study, we found that CMOs (across industries) are currently working on integrating cross channel to capture all customer interaction and proactively reachout through all touchoints, the use analytics for customer insight, and the use of social networks to foster collaboration beyond brand development to new channels, business models and products/services.Note the numbers don’t ad up, missing today – 3 years. And the first one adds over 100%.
  10. The CMO, and now the CEO, are really adjusting their ways as, the voice of the customer is being not only heard, but invited into the organization in new ways.In fact, In IBM’s 2013 CXO study, theCEOs told us that customers come second only to the C-suite in terms of the strategic influence they wield. When asked, “Who has the most influence on your strategic vision and business strategy?” 55 percent of interviewed CEOs cited customers. This not only underscores the need to act now, but the amount of process change that is happening across all industries.
  11. So, we have shared a lot. We To better understand the big data landscape, we asked respondents to describe the level of big data activities in their organizations today. The results suggest four main stages of big data adoption and progression along a continuum that we have labeled Educate, Explore, Engage and Execute.In each of these stages, IBM has offerings to help you on your journey.Educate: Building a base of knowledge (24 percent of respondents)In the Educate stage, the primary focus is on awareness and knowledge development. Almost 25 percent of respondents indicated they are not yet using big data within their organizations. While some remain relatively unaware of the topic of big data, our interviews suggest that most organizations in this stage are studying the potential benefits of big data technologies and analytics, and trying to better understand how big data can help address important business opportunities in their own industries or markets. Within these organizations, it is mainly individuals doing the knowledge gathering as opposed to formal work groups, and their learnings are not yet being used by the organization. As a result, the potential for big data has not yet been fully understood and embraced by the business executives. IBM offerings: IBM BIG DATA HUB – the Big Data Hub is intended to be your source for information, content and conversation regarding big data analytics for the enterprise – filled with whitepaper, books, videos, customer case studies, etcIBM Briefings and Solution Centers – face to face opportunity for big data education and ability to bring your business and IT team together to get on the same page about big dataBig data University and YouTube Big Data channel – learn at your own pace – downloads, test environment and sandboxExplore: Defining the business case and roadmap (47 percent)The focus of the Explore stage is to develop an organization’s roadmap for big data development. Almost half of respondents reported formal, ongoing discussions within their organizations about how to use big data to solve important business challenges. Key objectives of these organizations include developing a quantifiable business case and creating a big data blueprint. This strategy and roadmap takes into consideration existing data, technology and skills, and then outlines where to start and how to develop a plan aligned with the organization’s business strategy. IBM Offering – IBM can come in and do a Big Data workshop briefing to help your business team prioritized the best use cases to apply big data based on impact to the business from a strategic, business value and TCO standpoint. Likewise IBM can recommend the big data platform that will support the business use casesIN SOME CASES, where your business has already identified the business use case, we can proceed with helping you design the solution and prove it out in a Proof of ConceptEngage: Embracing big data (22 percent)In the Engage stage, organizations begin to prove the business value of big data, as well as perform an assessment of their technologies and skills. More than one in five respondent organizations is currently developing POCs to validate the requirements associated with implementing big data initiatives, as well as to articulate the expected returns. Organizations in this group are working – within a defined, limited scope – to understand and test the technologies and skills required to capitalize on new sources of data. IBM offering: Proof of Concept is an important stage – for IBM this does NOT mean experiments and test environments. Instead it is helping clients after they’ve identified the business use case to have their big data environment, with IBM’ value add technologies on top of hadoop, to have this big data platform supporting their business environment. It is an important validation and learning phase before clients deploy across multiple use cases and across the enterpriseExecute: Implementing big data at scale (6 percent)In the Execute stage, big data and analytics capabilities are more widely operationalized and implemented within the organization. However, only 6 percent of respondents reported that their organizations have implemented two or more big data solutions at scale – the threshold for advancing to this stage. The small number of organizations in the Execute stage is consistent with the implementations we see in the marketplace. Importantly, these leading organizations are leveraging big data to transform their businesses and thus are deriving the greatest value from their information assets. With the rate of enterprise big data adoption accelerating rapidly – as evidenced by 22 percent of respondents in the Engage stage, with either POCs or active pilots underway – we expect the percentage of organizations at this stage to more than double over the next year. IBM VALUE: Only IBM has the full breadth of big data platform to support analytics needs across the enterprise and across multiple business use cases. We have the platform to support the operational requirement of big data business use cases, ability to scale as volume of data grows, variety of types of data to handle real-time and the need to have visibility and trusting the data that the big data platform provides.