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© 2013 IBM Corporation
Lighting the Way: Understanding the
Smart Energy Consumer
John Juliano, IBM
EEI/AGA Conference and ...
© 2013 IBM Corporation2
Agenda
IBM’s Global Utility Consumer Surveys
Strategic directions in response to findings
Customer...
© 2013 IBM Corporation3
IBM has surveyed over 17,000 people in 17 countries since 2007 to
learn more about tomorrow’s home...
© 2013 IBM Corporation4
The context for the questions in the prior surveys was that of a dramatically
different future for...
© 2013 IBM Corporation5
We developed a profiling that showed about 40% had active interest
in engaging - but one-third wer...
© 2013 IBM Corporation6
By 2011, in some parts of the world, issues emerged on more
immediate concerns that competed with ...
© 2013 IBM Corporation7
What are their most important influences on knowledge
gained, opinions, and attitudes toward behav...
© 2013 IBM Corporation8
We found that, in aggregate, providers’ influence on messaging for
their customers is now outweigh...
© 2013 IBM Corporation9
In 1979, a famous movie tagline noted “In space, no one can hear
you scream.”
influences
In the pa...
© 2013 IBM Corporation10
Where consumers’ perceive a shortfall in attention, this presents a
potentially huge problem
Sour...
© 2013 IBM Corporation11
Source: IBM 2011 Global Utility Consumer Survey
Consumer perceptions are a strong driver of opini...
© 2013 IBM Corporation12
Source: IBM 2011 Global Utility Consumer Survey
The counter to these challenges is better engagem...
© 2013 IBM Corporation13
Data source: IBM 2011 Global Utility Consumer Survey; Quote source: Quantitative Research into Pu...
© 2013 IBM Corporation14
Consumers’ expectations for smarter energy products and services
will be further shaped by their ...
© 2013 IBM Corporation15
… which are often viewed as offering more personalization and
innovation around consumers’ specif...
© 2013 IBM Corporation16
How consumers feel about the evolution of their providers today
speaks to a need to refine, perso...
© 2013 IBM Corporation17
Agenda
The 2011 IBM Global Utility Consumer Survey
Strategic directions in response to findings
C...
© 2013 IBM Corporation18
Today’s consumers demand that we know them as more than a
demographic, a zip code, or a transacti...
© 2013 IBM Corporation19
Transacti
ons
Orders
Payment
history
Usage
history
Purchase
stage
E-mail /
Chat
Call
center
notes...
© 2013 IBM Corporation20
Geography
Income
Age
Most segmentation approaches focus on two or three dimensions
Transactions
S...
© 2013 IBM Corporation21
Demographic
data
Transaction
data
Interaction
data
Behavioral
data
Descriptive analytics
Predicti...
© 2013 IBM Corporation22
A useful approach uses Feature Vectors to give customers
personalized profiles that can be meanin...
© 2013 IBM Corporation23
Source: IBM Institute for Business Value survey data 2010, n=21,740
Attitude
Cluster
Security-
or...
© 2013 IBM Corporation24
Predicted Retention Risk, used in the airline industry, could be a valuable
Feature Vector where ...
© 2013 IBM Corporation25
Personal Attributes
• Identifiers: name, address, age,
gender, occupation…
• Interests: sports, p...
© 2013 IBM Corporation26
Build the
capability to do
this at massive
scale
5
Generate insights
in real time that
are predic...
© 2013 IBM Corporation27
Agenda
The 2011 IBM Global Utility Consumer Survey
Strategic directions in response to findings
C...
© 2013 IBM Corporation28
Demonstration: Next Best Action in Utility Customer Service
Information
Analytics
Speaking
with t...
© 2013 IBM Corporation29
Demonstration: Next Best Action in Utility Customer Service
© 2013 IBM Corporation30
Agenda
The 2011 IBM Global Utility Consumer Survey
Strategic directions in response to findings
C...
© 2013 IBM Corporation31
For questions and additional information, please contact:
John Juliano
juliano@us.ibm.com (240) 3...
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Understanding the Smart Energy Consumer 2013 Slide 1 Understanding the Smart Energy Consumer 2013 Slide 2 Understanding the Smart Energy Consumer 2013 Slide 3 Understanding the Smart Energy Consumer 2013 Slide 4 Understanding the Smart Energy Consumer 2013 Slide 5 Understanding the Smart Energy Consumer 2013 Slide 6 Understanding the Smart Energy Consumer 2013 Slide 7 Understanding the Smart Energy Consumer 2013 Slide 8 Understanding the Smart Energy Consumer 2013 Slide 9 Understanding the Smart Energy Consumer 2013 Slide 10 Understanding the Smart Energy Consumer 2013 Slide 11 Understanding the Smart Energy Consumer 2013 Slide 12 Understanding the Smart Energy Consumer 2013 Slide 13 Understanding the Smart Energy Consumer 2013 Slide 14 Understanding the Smart Energy Consumer 2013 Slide 15 Understanding the Smart Energy Consumer 2013 Slide 16 Understanding the Smart Energy Consumer 2013 Slide 17 Understanding the Smart Energy Consumer 2013 Slide 18 Understanding the Smart Energy Consumer 2013 Slide 19 Understanding the Smart Energy Consumer 2013 Slide 20 Understanding the Smart Energy Consumer 2013 Slide 21 Understanding the Smart Energy Consumer 2013 Slide 22 Understanding the Smart Energy Consumer 2013 Slide 23 Understanding the Smart Energy Consumer 2013 Slide 24 Understanding the Smart Energy Consumer 2013 Slide 25 Understanding the Smart Energy Consumer 2013 Slide 26 Understanding the Smart Energy Consumer 2013 Slide 27 Understanding the Smart Energy Consumer 2013 Slide 28 Understanding the Smart Energy Consumer 2013 Slide 29 Understanding the Smart Energy Consumer 2013 Slide 30 Understanding the Smart Energy Consumer 2013 Slide 31
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Understanding the Smart Energy Consumer 2013

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

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Understanding the Smart Energy Consumer 2013

  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 29. © 2013 IBM Corporation29 Demonstration: Next Best Action in Utility Customer Service
  30. 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. 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.

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

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