AGA-EEI presentation from April 2013 on IBM's work to help utilities successfully engage with the emerging "smart energy consumer"

1. © 2013 IBM Corporation
Lighting the Way: Understanding the
Smart Energy Consumer
John Juliano, IBM
EEI/AGA Conference and Exposition, Atlanta, GA, April 18, 2013

2. © 2013 IBM Corporation2
Agenda
IBM’s Global Utility Consumer Surveys
Strategic directions in response to findings
Customer Service and the Next Best Action
Contacts

3. © 2013 IBM Corporation3
IBM has surveyed over 17,000 people in 17 countries since 2007 to
learn more about tomorrow’s home energy consumer

4. © 2013 IBM Corporation4
The context for the questions in the prior surveys was that of a dramatically
different future for energy consumers
– Better information
– More control
– Better reliability and power quality
– More participation
– Greener
Since early 2009, many other surveys have come out with a similar focus on
what consumers will look for in the future
The consensus among these had been that many consumers are eager for the
enhanced reliability, control, and new programs and services that these
changes will bring
In our first two Global Utility Consumer Surveys (2007 and 2009),
we assessed the future wants and needs of residential customers

5. © 2013 IBM Corporation5
We developed a profiling that showed about 40% had active interest
in engaging - but one-third were likely to stick with the status quo
Two factors will
determine the nature
of the interface
between utilities and
consumers in the
future:
1. The degree to which
consumers take
initiative in
decision-making in
their energy supply
and usage toward
meeting specific
goals
2. The consumers’
disposable income
available for energy
choices in supply
and conservation
Disposable Income Available for Energy Choices
Low High
Decision-MakingInitiativeTaken
LowHigh
Passive Ratepayer (PR)
Frugal Goal-Seeker (FG) Energy Stalwart (ES)
Energy Epicure (EE)
An energy consumer who is relatively
uninvolved with decisions related to
energy usage and uninterested in
taking or unable to take added
responsibility for these decisions
An energy consumer who is willing to
take modest action to address specific
goals or needs in energy usage, but is
constrained in what they are able to do
because disposable income is limited
An energy consumer who has specific
goals or needs in energy usage, and
has both the income and desire to act
on those needs
A very high-usage energy consumer
relatively unconstrained by budget
limits, but with little or no desire for
conservation or active involvement in
energy control
Residential and Small Commercial Energy Customers - 2011
22%
(22% in 2009)
33%
(31% in 2009)
20%
(21% in 2009)
24%
(26% in 2009)
Sources: Valocchi, M, A. Schurr, J. Juliano, and E. Nelson, Plugging in the consumer: Innovating utility business models for the future, IBM Institute for Business Value, 2007;
IBM Global Utility Consumer Surveys 2009, 2011.

6. © 2013 IBM Corporation6
By 2011, in some parts of the world, issues emerged on more
immediate concerns that competed with those views of the future
Examples have been consumer confusion and uncertainty, negative press, and
valid yet troubling questions about privacy, cost, and distribution of benefits

7. © 2013 IBM Corporation7
What are their most important influences on knowledge
gained, opinions, and attitudes toward behavioral
change?
How do perceptions of providers and technological
change shape consumers’ expectations?
What levels of knowledge do they have on critical
elements that drive their perceptions and expectations?
What expectations do consumers have for energy
service and providers in the future – and what sets these
expectations?
The most recent survey focused on energy consumers’ potential
sentiment drivers – positive and negative

8. © 2013 IBM Corporation8
We found that, in aggregate, providers’ influence on messaging for
their customers is now outweighed by other sources
Percent of respondents that listed a particular information source as the one(s) to which
they are most likely to go to get information about energy cost, environmental impact,
alternative suppliers, or new programs and services (grouped)
Source: IBM 2011 Global Utility Consumer Survey
influences
45%
55%
38%
62%
0%
10%
20%
30%
40%
50%
60%
70%
Sources for which providers control
messages
Sources for which providers do not
control messages
NA/EU/ANZ/Japan, 2010
Growth regions, 2010

9. © 2013 IBM Corporation9
In 1979, a famous movie tagline noted “In space, no one can hear
you scream.”
influences
In the past, when someone had a bad experience with a company,
only the individual would experience it.
Now, the world can know about it in seconds.
In 2013, pretty much everyone
can hear you scream.

10. © 2013 IBM Corporation10
Where consumers’ perceive a shortfall in attention, this presents a
potentially huge problem
Source: IBM 2011 Global Utility Consumer Survey
8%
16%
13%
18%
21%
27%
37%
44%
46%
50%
0% 10% 20% 30% 40% 50% 60%
Adopts new technologies
and ways of doing business
Invests in advanced
technologies
Helps me manage energy
use
Supplies cleaner energy
Treats me as a valued
customer
This describes my current provider My provider should focus on this
perceptions
29 point gap
28 point gap
31 point gap
21 point gap
19 point gap
Percent of respondents who believe that their current provider does/should
focus on specified activities or attributes

11. © 2013 IBM Corporation11
Source: IBM 2011 Global Utility Consumer Survey
Consumer perceptions are a strong driver of opinions on new
initiatives like smart grid and meter deployment
Percent of respondents who approve of plans to deploy smart meters for
each of five levels of privacy concern
0%
10%
20%
30%
40%
50%
60%
70%
80%
Strongly
disagree
Disagree Neutral/Unsure Agree Strongly agree
Reaction to statement "These technologies will put my privacy at risk."
Percent approving of SG/SM deployment
(NA/EU/ANZ/Japan)
Percent approving of SG/SM deployment (Growth)
perceptions

12. © 2013 IBM Corporation12
Source: IBM 2011 Global Utility Consumer Survey
The counter to these challenges is better engagement – better
communication and information to each consumer
43% 42%
52%
48%
52%
58%
67% 69%
75%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Willing to share
information on energy
usage
Likely to change energy
usage patterns to achieve
goals
Likely to actively leverage
new information about
consumption
No or Minimal
Knowledge
Moderate
Knowledge
Strong Knowledge
Percent of respondents expressing their likelihood of taking on specific
behaviors or behavioral changes
knowledge

13. © 2013 IBM Corporation13
Data source: IBM 2011 Global Utility Consumer Survey; Quote source: Quantitative Research into Public Awareness, Attitudes, and Experience of
Smart Meters (Wave 2), UK Dept. of Energy and Climate Change, February 21, 2013.
Higher levels of knowledge strongly correlated with increased belief
that new technologies and programs will bring benefits
35% 35%
43%
47%
40% 41%
50%
55%
50%
52%
61%
71%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Believe they will have a
positive impact environmentally
Believe they will have a
positive impact on energy
costs
Approve of the deployments
underway or proposed
Believe they will bring benefits
to their family
No or Minimal Knowledge Moderate Knowledge Strong Knowledge
Percent of respondents holding positive opinions of smart meters and smart
grid deployment plans locally (underway, proposed, or hypothesized)
knowledge
Two years after we released this data, the UK Government’s
Dept. of Environment and Climate Change (DECC) also noted
that “higher levels of perceived knowledge of smart meters were
correlated with increased support and interest.”

14. © 2013 IBM Corporation14
Consumers’ expectations for smarter energy products and services
will be further shaped by their experiences with other industries…
Source: Valocchi, M, A. Schurr, J. Juliano, and E. Nelson, Plugging in the consumer: Innovating utility business models for the future, IBM Institute for Business Value, 2007.
expectations

15. © 2013 IBM Corporation15
… which are often viewed as offering more personalization and
innovation around consumers’ specific needs
7%
9%
13%
14%
16%
16%
26%
Utility
Providers
Pay TV
Providers
Online
Retailers
Insurance
Providers
Telecom
Providers
Grocery
Retailers
Banks
Understands me and offers
products / services that are aligned
with my needs
Approaches me with innovative
products or services
Treats me like an individual and
delivers a personalized
experience
expectations
6%
9%
10%
16%
17%
20%
21%
Utility
Providers
PayTV
Providers
Insurance
Providers
Telecom
Providers
Online
Retailers
Grocery
Retailers
Banks
6%
9%
12%
14%
16%
21%
23%
Utility
Providers
Insurance
Providers
Pay TV
Providers
Grocery
Retailers
Banks
Online
Retailers
Telecom
Providers

16. © 2013 IBM Corporation16
How consumers feel about the evolution of their providers today
speaks to a need to refine, personalize, and target communications
Their influences are still skewed toward the traditional – but
increasingly these are sources that are from places where utilities
have no control over the tone or accuracy of the messages
Consumers have mixed perceptions of their current providers and
what they will be able to do in the future – and where there are
negative perceptions, more negative reactions are likely
For customer buy-in to smart grid and smart meter plans, providing
knowledge is an absolute necessity – the more consumers learn
about what is occurring, the more favorable they are toward it
They have been promised – explicitly or implicitly – great benefits
from the smart grid revolution, and their expectations are that
those promises will be fulfilled
What can be done to keep perceptions (positive and negative) aligned
with reality? How can expectations be shaped by providing more and
better knowledge in the context of the most effective influences?

17. © 2013 IBM Corporation17
Agenda
The 2011 IBM Global Utility Consumer Survey
Strategic directions in response to findings
Customer Service and the Next Best Action
Contacts

18. © 2013 IBM Corporation18
Today’s consumers demand that we know them as more than a
demographic, a zip code, or a transaction history.
At the same time, they are
exhibiting a digital body
language that gives us a look
into their passions, opinions,
and sentiments – but it
comes in the form of
millions of pieces of data
from hundreds of sources.
We must be able to
determine what new insights
that data offers.

19. © 2013 IBM Corporation19
Transacti
ons
Orders
Payment
history
Usage
history
Purchase
stage
E-mail /
Chat
Call
center
notes
Web
click-
streamsIn-person
dialogs
Opinions
Prefer
ences
Desires
Needs
Characte
ristics
Demo-
graphics
Attribute
s
Demographic
data
Transaction
data
They demand we know more, in part, because they are telling us
so much more in so many more ways
Interaction
data
Behavioral
data

20. © 2013 IBM Corporation20
Geography
Income
Age
Most segmentation approaches focus on two or three dimensions
Transactions
Sales
20
Anticipating consumer needs has relied on segmentation
approaches that are too limited to give views of individuals
These are typically not actionable because customers are more complex
than 2 or 3 dimensions – leaving them unable to truly seize the
opportunities that customer uniqueness presents

21. © 2013 IBM Corporation21
Demographic
data
Transaction
data
Interaction
data
Behavioral
data
Descriptive analytics
Predictive analytics
Prescriptive analytics
Transacti
ons
Orders
Payment
history
Usage
history
Email /
Chat
Call
center
notes
Web
click-
streamsIn-person
dialogs
Opinions
Prefer-
ences
Desires
Needs
Character
-istics
Demo-
graphics
Attributes
Purchase
stage
To do this, we need to make
use of:
New analytics to make
sense of this complex
and intricate data
Multi-dimensional
models developed to
explain or predict
customer
We can move from simply reacting to a customer contact to
predicting the next best action that meets the consumer’s need

22. © 2013 IBM Corporation22
A useful approach uses Feature Vectors to give customers
personalized profiles that can be meaningfully clustered
A Feature Vector is a model of the customer’s response (historical or predicted) to one
specific aspect of the value proposition
Each Feature Vector is like a gene strand in DNA, describing a facet of customer
behavior
Theses building blocks that can be assembled into larger models of customer behavior
Action Clusters are aggregates of customers into groups that illustrate similar
behavioral propensities across many Feature Vectors
Age +Age +Age +Age +
Income +Income +Income +Income +
GeographyGeographyGeographyGeography
PreferredPreferredPreferredPreferred
Channel(sChannel(sChannel(sChannel(s))))
Length ofLength ofLength ofLength of
Time asTime asTime asTime as
CustomerCustomerCustomerCustomer
AnnualAnnualAnnualAnnual
EnergyEnergyEnergyEnergy
UsageUsageUsageUsage
ZipZipZipZip
CodeCodeCodeCode
Needs andNeeds andNeeds andNeeds and
OpinionsOpinionsOpinionsOpinions
Expressed viaExpressed viaExpressed viaExpressed via
Social MediaSocial MediaSocial MediaSocial Media
PredictedPredictedPredictedPredicted
Retention RiskRetention RiskRetention RiskRetention Risk
History ofHistory ofHistory ofHistory of
OnOnOnOn----TimeTimeTimeTime
BillBillBillBill
PaymentPaymentPaymentPayment
PredictedPredictedPredictedPredicted
CustomerCustomerCustomerCustomer
Lifetime ValueLifetime ValueLifetime ValueLifetime Value
ProbabilityProbabilityProbabilityProbability
Of New Product orOf New Product orOf New Product orOf New Product or
Service PurchaseService PurchaseService PurchaseService Purchase
EngagementEngagementEngagementEngagement
PreferencesPreferencesPreferencesPreferences
with Energywith Energywith Energywith Energy
ProvidersProvidersProvidersProviders

23. © 2013 IBM Corporation23
Source: IBM Institute for Business Value survey data 2010, n=21,740
Attitude
Cluster
Security-
oriented
individualist
Demanding
support-
seeker
Loyal
quality-
seeker
Price-
oriented
minimalist
Support-
seeking
skeptic
Informed
optimizer
% of
total
13% 12% 19% 18% 21% 17%
Key theme "I know what I
want and
organize
myself"
"I need personal
advice"
"I trust my
Energy
Provider and
remain a loyal
customer"
"I do not like
Energy
Providers –
make it cheap
and stay
away"
"I need advice
but prefer to
keep distance
from my
Energy
Provider"
"I take time to
research to
find the best"
23
But “attitude” is only one of what could be several key “feature vectors” that
affect Energy customer behavior. For example, some Loyal Quality Seekers
might prefer to use the Web while others might not, and thus “attitude” and
“preferred channel” are feature vectors that might need to be estimated
separately (depending on correlation between the two vectors).
An Engagement Preferences Feature Vector helps define how
customers want to engage with providers

24. © 2013 IBM Corporation24
Predicted Retention Risk, used in the airline industry, could be a valuable
Feature Vector where competition is emerging in energy
Service recovery & loyalty architecture
EmotionalSignal
Mighty Eagle
Airlines
Platinum FF#
941827614
Emotional Signal
Date
∑experiences
Transactions
from Data
Warehouse
Observations
DemographicDemographic
DescriptionsDescriptions
External Data
ExternalExternal
FactorsFactors
(Weather)(Weather)
Variables
ServiceService
RecoveryRecovery
Treatments
Analytic
Information
Store
(Emotional Index)
Consolidated Data
Information Formation
• Pre-Processed Decisioning Scores
• Financial Performance
• Profile & Attribute Analysis
• Goal Priorities & Constraints
• Risk Adjusted Lifetime Value
• Forecasted Treatment Response
Feature Vector
Development
24

25. © 2013 IBM Corporation25
Personal Attributes
• Identifiers: name, address, age,
gender, occupation…
• Interests: sports, pets, cuisine…
• Life Cycle Status: marital, parental
Personal Attributes
• Identifiers: name, address, age,
gender, occupation…
• Interests: sports, pets, cuisine…
• Life Cycle Status: marital, parental
Relationships
• Personal relationships: family, friends
and roommates…
• Business relationships: co-workers
and work/interest network…
Relationships
• Personal relationships: family, friends
and roommates…
• Business relationships: co-workers
and work/interest network…
Products and Interests
• Personal preferences of products
• Product Purchase history
Products and Interests
• Personal preferences of products
• Product Purchase history
Social Media based
360-degree
Consumer Profiles
Life Events
• Life-changing events: relocation,
having a baby, getting married, getting
divorced, buying a house…
Life Events
• Life-changing events: relocation,
having a baby, getting married, getting
divorced, buying a house…
Revealed intent to buy Life events
Location announcements
Intent to move into/out of area
I'm thinking about buying a home in Buckingham Estates per a
recommendation. Anyone have advice on that area? #atx
#austinrealestate #austin
I'm thinking about buying a home in Buckingham Estates per a
recommendation. Anyone have advice on that area? #atx
#austinrealestate #austin
Looks like we'll be moving to New Orleans sooner than I thought.
Looks like we'll be moving to New Orleans sooner than I thought.
College: Off to Stanford for my MBA! Bbye chicago!
College: Off to Stanford for my MBA! Bbye chicago!
I'm at Starbucks Parque Tezontle http://4sq.com/fYReSj
I'm at Starbucks Parque Tezontle http://4sq.com/fYReSj
I need a new digital camera for my food pictures, any
recommendations around 300?
I need a new digital camera for my food pictures, any
recommendations around 300?
What should I buy?? A mini laptop with Windows 7 OR a
Apple MacBook!??!
What should I buy?? A mini laptop with Windows 7 OR a
Apple MacBook!??!
Timely Insights
• Intent to buy various products
• Current Location
Timely Insights
• Intent to buy various products
• Current Location
25
Further intelligence based on social media analysis leads to “360o
Consumer Profiles”, which add depth and richness to the analysis

26. © 2013 IBM Corporation26
Build the
capability to do
this at massive
scale
5
Generate insights
in real time that
are predictive, not
just historical
4
Interconnect
social media data,
other forms of
digital data and
transaction data
to paint a more
vivid picture of
each customer
2
Instrument all the
key touchpoints to
gather the right
data on each
customer
1
Run the right
analytics, at the
right time, on the
right customer
to generate new
ideas on whom
to serve and how
to best serve that
individual
3
Valuecreated
Capabilities over time
Understanding each customer as an individual does not happen
immediately, but follows a progression path over time

27. © 2013 IBM Corporation27
Agenda
The 2011 IBM Global Utility Consumer Survey
Strategic directions in response to findings
Customer Service and the Next Best Action
Contacts

28. © 2013 IBM Corporation28
Demonstration: Next Best Action in Utility Customer Service
Information
Analytics
Speaking
with the
customer
Building
predictive
models
Defining the
Next Best
Action
Creating
marketing
offers
Establishes the
Information
Supply Chain
Operations

29. © 2013 IBM Corporation29
Demonstration: Next Best Action in Utility Customer Service

30. © 2013 IBM Corporation30
Agenda
The 2011 IBM Global Utility Consumer Survey
Strategic directions in response to findings
Customer Service and the Next Best Action
Contacts

31. © 2013 IBM Corporation31
For questions and additional information, please contact:
John Juliano
juliano@us.ibm.com (240) 361-8157
Cheryl Linder
cheryl.d.linder@us.ibm.com (503) 533-2117
Vickie Dorris
vdorris@us.ibm.com (423) 622-1498
http://www-935.ibm.com/services/us/gbs/thoughtleadership/ibv-knowledge-is-power.html
Consumers have been
promised a lot with respect to
the “new world of the smart
grid”. And they want what’s
been promised to them.