Complimentary Executive Summary. To order the complete report, call Order online: EnergyCentral.com/UAIreport

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1 2012 Complimentary Executive Summary To order the complete report, call Order online: EnergyCentral.com/UAIreport annual customer analytics report

2 SECTION TITLE 04 Executive Summary 06 Introduction 07 Methodology and a look at study respondents 09 Defining analytics and customer analytics Table of Contents 10 Diving into customer analytics 10 Evolution of customer analytics 12 Market analysis 13 Meter data analytics rule, dude, at least for now 16 Energy efficiency gets high-tech with analytics 17 No end in sight for customer analytics possibilities and uses H. Christine Richards Lead analyst crichards@energycentral.com Mike Smith Principal-in-charge msmith@energycentral.com Guy K. Anderson Analyst Kim Gaddy Analyst Mary Ann Stewart Analyst 19 The people side of customer analytics, which isn t just customers 21 Activity now, and continued spending on the way 22 Customer analytics: boots on the ground 26 The solution and service provider landscape 29 conclusions 30 APPENDIX A: Utility in-depth interview summaries 64 APPENDIX B: Solution and service provider summaries 90 APPENDIX C: Online survey questions and answers 106 APPENDIX D: Analyst biographies The Utility Analytics Institute Reports are a publication of Utility Analytics Institute Group, a division of Energy Central. This report is Copyright 2012, Energy Central. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the express permission of Energy Central. Factual material contained herein is obtained from sources believed to be reliable, but the publishers are not responsible for any errors or omissions contained herein. 2 UTILITY ANALYTICS INSTITUTE annual customer analytics report

3 FIGURES AND TABLES List of Figures & Tables Figures Figure 1. Respondents by organization type Figure 2. Respondents by services offered Figure 3. Respondents by utility type Figure 4. Respondents by utility company size (metered customers) Figure 5. Respondents by region Figure 6. Respondents by primary job responsibility Figure 7. Respondent level of responsibility Figure 8. Utility analytics definition Figure 9. Key customer analytics areas Figure 10. Utility analytics deployment Figure 11. Primary focus of customer analytics initiative Figure 12. Utility analytics value chain Figure 13. Importance of customer analytics improvements Figure 14. Analytics value curve Figure 15. Importance of other customer analytics Figure 16. Key challenge with customer analytics initiatives Figure 17. Role of business divisions in customer analytics Figure 18. Customer analytics project status Figure 19. Approximate US $ value of current or planned projects Figure 20. Utility analytics value chain Figure 21. Respondent participation in customer analytics planning/execution Figure 22. Customer analytics deployment Figure 23. Primary focus of customer analytics initiative by company ownership Figure 24. Primary focus of customer analytics initiative by company size Figure 25. Primary focus of customer analytics initiative by region Figure 26. Importance of other customer analytics by company ownership Figure 27. Importance of other customer analytics by company size Figure 28. Importance of other customer analytics by region Figure 29. Customer analytics project status by company ownership Figure 30. Customer analytics project status by company size Figure 31. Customer analytics project status by region Figure 32. Approximate US $ value of current or planned projects by company ownership Figure 33. Approximate US $ value of current or planned projects by company size Figure 34. Approximate US $ value of current or planned projects by region Figure 35. Importance of customer analytics business drivers by company ownership Figure 36. Importance of customer analytics business drivers by company size Figure 37. Importance of customer analytics business drivers by region Figure 38. Importance of customer analytics improvements by company ownership Figure 39. Importance of customer analytics improvements by company size Figure 40. Importance of customer analytics improvements by region Figure 41. Role of business divisions in customer analytics by company ownership Figure 42. Role of business divisions in customer analytics by company size Figure 43. Role of business divisions in customer analytics by region Figure 44. Customer analytics spending changes over next one to two years by company ownership Figure 45. Customer analytics spending changes over next one to two years by company size Figure 46. Customer analytics spending changes over next one to two years by region Figure 47. Customer analytics spending changes over next three to five years by company ownership Figure 48. Customer analytics spending changes over next three to five years by company size Figure 49. Customer analytics spending changes over next three to five years by region Figure 50. Key challenge with customer analytics initiatives by company ownership Figure 51. Key challenge with customer analytics initiatives by company size Figure 52. Key challenge with customer analytics initiatives by region Tables Table 1. Customer analytics sub-segment definitions Table 2. North American customer analytics spending, 2011 to 2016 ($M) Table 3. Provider customer analytics coverage, and solutions and services provided Table 4. Respondents by organization type Table 5. Respondents by utility type Table 6. Respondents by services offered Table 7. Respondents by utility company size Table 8. Respondents by region Table 9. Respondents by primary job responsibility Table 10. Respondent level of responsibility Table 11. Respondent participation in customer analytics planning/execution Table 12. Customer analytics deployment Table 13. Primary focus of customer analytics initiative Table 14. Importance of other customer analytics Table 15. Customer analytics project status Table 16. Approximate US $ value of current or planned projects Table 17. Importance of customer analytics business drivers Table 18. Importance of customer analytics improvements Table 19. Role of business divisions in customer analytics Table 20. Customer analytics spending changes over next one to two years Table 21. Customer analytics spending changes over next three to five years Table 22. Key challenge with customer analytics initiatives UTILITY ANALYTICS INSTITUTE Annual customer analytics report 3

4 SECTION TITLE 2 North American customer analytics spending will grow by 32% per year from $180.4 million in 2011 to $718.9 million in 2016 EXECUTIVE SUMMARY Welcome to our third report, the Annual Customer Analytics Report, which rounds out a trilogy of utility analytics research reports completed so far by the Utility Analytics Institute. This time around, we re exploring customer analytics in greater detail. Utilities are certainly working to leverage smart meter data into advanced analytics capabilities for customer operations and customer engagement, and we re here to explore how utilities are taking their customer analytics into meter data analytics and beyond. To learn about customer analytics in the utility industry, we talked with about 120 utility companies and over 25 solution and service providers. Definition Customer analytics are the hardware, software, professional services, business processes and people that enable utilities to analyze data in order to better serve the utility and its customers. We segment customer analytics into two key areas: Customer operations: Analytics that focus internally on improving the efficiency and effectiveness of a utility s customer operations. This area includes meter data analytics, credit and collections, call center optimization, fraud detection, campaign management, customer segmentation, pricing optimization, and other customer operations. Customer engagement: Analytics that support utility interactions with customers and improve their relationship with the utility through improved service, lower costs and better customer experiences. This area includes categories such as demand response, energy efficiency, distributed generation management, and other customer engagement. 4 UTILITY ANALYTICS INSTITUTE annual customer analytics report

5 SECTION TITLE Key Findings Meter data analytics rule, dude, at least for now A significant majority of utilities are tackling customer analytics, and when they do, they re likely focusing on meter data analytics. However, this will change as analytics evolve. About 73% of utility companies have a customer analytics initiative, and within customer analytics, more than 40% of utilities focus primarily on meter data analytics. Data is key for the success of customer analytics initiative, and many utilities are working through smart meter data, but it doesn t mean that there aren t other important resources. Numerous data sources feed into customer analytics initiatives including customer data, weather data, demand side management data, survey data, rates, pilot data, GIS data, SCADA data, equipment data, load growth protocol groups, load growth shapes, company sales, demographics, and the list goes on. Energy efficiency gets high tech with analytics Even though many utilities may focus on meter data analytics, there are still plenty of examples of utilities taking on customer analytics in other areas. One area is energy efficiency, yes, the stereotypically non-high-tech world of weatherization and light-bulb changing, which came in second behind meter data analytics. About 27% of utility companies say that energy efficiency analytics is their primary focus. Much of the analytics in this space revolves around customer engagement and effectively marketing the right energy efficiency programs to the right customers. No end in sight for customer analytics possibilities and uses Utilities are big into meter data analytics and energy efficiency right now, but does that mean everything else is taking a back seat? No. Every customer analytics segment is of above average importance to utility companies. We also found examples of utilities already tackling more traditional analytics needs for the meter-to-cash process, as well as undertaking new customer analytics, such as measuring public sentiment, in addition to meter data analytics and energy efficiency efforts. The people side of customer analytics, which isn t just customers Utilities are facing challenges with employees, both those who develop and deploy analytics as well as those who use the analytics. Utility are facing challenges recruiting and developing the right folks who will build the analytics. On the user side, being able to figure out how to apply data in new ways can be a challenge, but so are the basics of how to access and use analytics. Activity now, and continued spending on the way About 73% of utility companies have some sort of customer analytics project either under way or in the planning stages. Of the utilities involved with customer analytics, 20% percent report that their projects are more than 50% complete. Over 26% of utilities moving forward with customer analytics are taking on projects worth more than $2 million. On top of that investment, about 84% of utilities reported that their customer analytics spending would continue to increase over the next one to two years, and 69% expected their spending to increase over the next three to five years. Between 2011 and 2016 we predict that North American customer analytics spending will grow by 32% per year, growing from $180.4 million 2011 to $718.9 million in Conclusions Utilities are primarily focusing on meter data analytics and energy efficiency at the moment, but there are many other customer analytics efforts under way. The customer analytics market is taking off, and utilities can take advantage of the growing data and analytics opportunities: Data quality is paramount. Data is the foundation of analytics initiatives. Data quality is not just a one-time effort, because new business objectives and data sources will keep rolling toward utility companies. Utilities need to develop processes to ensure a quality of data and integration that can support future customer analytics initiatives. Think beyond the meter. Sorting through meter data is critical right now, but what can your company do to ensure that you re bringing in right data sources, whether smart meter data or not? With your analytics investments, consider how those investments can serve your company beyond meter data analysis. Prepare your people for customer analytics. Customer analytics initiatives will become increasingly complex, and companies will need to develop or acquire the right skill sets to handle that complexity, or seek outside resources. For analytics users, encourage personnel to embrace analytics and seek out valuable opportunities to leverage the data. An analytics ambassador can help build confidence in analytics and encourage personnel across the company to get involved in analytics. UTILITY ANALYTICS INSTITUTE Annual customer analytics report 5

6 INTRODUCTION 20 Respondents from 120 utility companies participated in our online survey. INTRODUCTION Welcome to our third report, the Annual Customer Analytics Report, which rounds out a trilogy of utility analytics research reports completed so far by the Utility Analytics Institute. This time around, we re exploring customer analytics in greater detail. Utilities are certainly working to leverage smart meter data into advanced analytics capabilities for customer operations and customer engagement, and we re here to explore how utilities are taking their customer analytics into meter data analytics and beyond. To better understand this emerging and rapidly evolving analytics market, we at the Utility Analytics Institute, a division of Energy Central, are creating a series of in-depth reports that will explore critical developments in the analytics marketplace. The reports include: Annual Market Outlook and Forecast available now Annual Grid Analytics Report available now Annual Customer Analytics Report May 2012 Best Practices & Case Studies August UTILITY ANALYTICS INSTITUTE annual customer analytics report

7 INTRODUCTION In this report, they ll walk you through: The definition of customer analytics The drivers, issues and growth in the customer analytics marketplace The stories of utilities moving into customer analytics The solution and service providers in this space As you go through this report, please note that we worked hard to provide you with the most essential analysis and guidance you ll need to be successful in the customer analytics marketplace. For those data hogs out there and you know who you are we also provide: Appendix A: summaries for utilities they interviewed in depth Appendix B: service and solution provider profiles Appendix C: each online survey question along with the answers they received to those Appendix D: analyst biographies Methodology and a look at study respondents Let s take some time to better understand who we were talking with to develop our findings. To learn about customer analytics in the utility industry, it made sense to go talk with utilities that are diving into analytics and a lot of them. We first conducted an online survey, which covered the questions listed in Appendix C, and received responses from about 120 utility companies. We then completed another 25 in-depth phone interviews with utilities that focused on the qualitative aspects of the customer analytics marketplace. We also talked with over 25 solution and service providers in the customer analytics space to learn about their offerings. In this section, we take a closer look at what utilities we connected with and how we ensured we got the right people in the right companies to discuss customer analytics. Utility companies only, please As you can see in Figure 1, out of the 268 total online survey respondents, about 120 were utility companies. We didn t allow the nonutility respondents to continue on with the survey. Solution and service providers who tried to get in on this survey were offered a chance to speak their minds in a separate interview. The report primarily focuses on the use of customer analytics in electric utilities (as shown in Figure 2), and all of our utility respondents provided electric service, but note that many respondents also provided other services. Slicing and dicing the utilities Utility Solution Consulting firm Government We not only wanted to see what utilities provider agency as a whole are thinking, but what different types of utilities are thinking. We first sliced Organization type Figure 1. Respondents by organization type UTILITY ANALYTICS INSTITUTE Annual customer analytics report 7 9% 17% 9% 21% 25 We completed more than 25 in-depth phone interviews with utilities that focused on the qualitative aspects of the customer analytics marketplace. 44% Utility Solution provider Consulting firm Government agency Other Note: See Question 1, Appendix C for additional detail.

8 INTRODUCTION Figure 2. Respondents by services offered 100% 80% 60% satisfying shareholders. As shown in Figure 3, 40% Investor-owned Municipal Cooperative District/federal approximately 55% of the utility respondents were from investor-owned utilities. The 20% remainder included 21% from municipalities, 17% from cooperatives and 7% representing Region % district or federal organizations. Going Electric Gas Water Wastewater Solid waste forward, we fold municipalities, cooperatives Note: See Question 3, Appendix C for additional detail. and district/federal organizations into a single category of public utility companies. 7% our respondents by company ownership structure, which we ultimately segment into investor-owned and public utility companies. This slicing is important because these groups face different influences and challenges from negotiating with regulators to answering to a city council to Figure 3. Once we sliced, then we diced the utility Respondents Electric Gas Water Wastewater Solid waste 17% companies by their size. The utilities by Region utility type represented a wide range of company sizes, which we measured by the number 55% of customers. As you can see in Figure 4, utilities with 1 million or more customers 1,000, , ,000-50,000-99,999 10,000-49,999 Fewer than 999, ,999 represented 35% of the respondents, 10,000 which is 21% a good representation because these utilities are typically the major players and influencers in 9.8 the marketplace. We 10.7 also captured many 9.8 other important segmentations. For the rest Investor-owned Municipal Cooperative District/federal of the report, we take the size segmentations Note: See Question 2, Appendix C for additional detail. shown in Figure 4 and cluster them into large utilities, or those with 500,000 or more 10% customers, medium-sized utilities with 100,000 to 499,999 customers, and small Figure 4. 11% utilities with fewer than 100,000 customers. Respondents by utility company size (metered 35% Another wrinkle for utility segmentation is customers) the region in which most of their customers 10% are located. You can see in Figure 5 that we have utilities from all over the United States 14% participating in the survey. About 9% of 21% respondents hail from outside United States. 1,000, , , , ,999 50,000-99,999 10,000-49,999 Fewer than 10,000 Note: See Question 4, Appendix C for additional detail. 8 UTILITY ANALYTICS INSTITUTE annual customer analytics report

9 INTRODUCTION Not just companies, but people count It s important to understand not only the types of utility companies we re talking with, but who within the utility company is providing us information. The people part of analytics is crucial to success of customer analytics initiatives. So we looked at respondents in terms of what business areas they worked in, and what level of responsibility they held within the company. Figure 5. Respondents by region 9% 20% 17% 26% 28% Engineering Maintenance Customer service Information technology Respondents reflect a variety of folks who are involved in customer analytics, including customer service, information technology and operations, as shown in Figure 6. As we ll see when we get into more of the study results, customer analytics isn t necessarily just about initiatives that involve customer service folks. We also understand how customer analytics impact people with a variety of job responsibilities. As shown in Figure 7, we obtained representation from across the responsibility spectrum with approximately 15% executives, 45% managers and supervisors, and the remaining 40% filling technical or staff positions. Defining analytics and customer analytics Before we get too far down the path of customer analytics, it s important to revisit the basic definition of analytics. Analytics are technologies, services, people and processes that enable utilities to transform data into actionable insights. This transformation includes four key areas: Collecting, managing, cleaning and storing data Extracting and analyzing data Reporting analysis results Making decisions and taking action Figure 6. Respondents by primary job responsibility U.S. Southeast U.S. Midwest U.S. West International U.S. Northeast Manager/ Supervisor Note: See Question 5, Appendix C for additional detail. Technical/staff Executive Engineering 47 Maintenance 39 Customer 13 service Information technology Regulatory Finance Other Operations Figure 7. Respondent level of responsibility 8% 4% 17% 13% 18% 6% 21% 21% 39% 47% 5% Note: See Question 6, Appendix C for additional detail. Manager/supervisor Technical/staff Executive Note: See Question 7, Appendix C for additional detail. UTILITY ANALYTICS INSTITUTE Annual customer analytics report 9

10 INTRODUCTION Figure 8 summarizes the utility analytics definition in terms of functions, technologies and business applications, and the roles of people and process. Note that we divide analytics functions into three areas: grid analytics, customer analytics and other analytics. Diving into customer analytics In this report, we focus on customer analytics. At a high level, customer analytics are the hardware, software, professional services, business processes and people that enable utilities to analyze data to better serve the utility and its customers. These areas can include meter data analytics and meter data management systems, credit and collections, call center optimization, fraud detection, campaign management, customer segmentation, pricing optimization, revenue protection and demand response programs. These analytics applications do not include traditional customer information systems. Figure 8. Utility analytics definition ANALYTICS Hardware Software Services Process People Grid analytics Evolution of customer analytics The retail, financial and telecommunications industries have long focused on customers analytics to survive in a world of cutthroat competition. For example, telecommunications providers are willing to invest in customer segmentation and marketing analytics to avoid customer churn, because bringing a customer on board can cost upward of $500 per person. In the intensively competitive grocery industry, one grocer, armed with information gathered from its loyalty program, sent out customized mailers 451,800 different versions to 1.2 million cardholders. Furthermore, the targeted mailers featured personalized greetings from area management. From the mailer and subsequent interactions with customers, one regional manager alone received 3,000 Christmas cards. Collected data Customer analytics Other analytics With the exception of deregulated utility markets, most utilities just don t face this sort of intense competition that drives many companies to invest in customer analytics. Historically, electric utilities delivered one thing: electricity, to one group: everyone. Utilities primarily focused on the meter-tocash process and things like how to improve billing and offer more efficient customer service. Traditional customer information and relationship management systems provided much of what utility companies needed. How things are changing New data, new programs, new pricing and even new competition (think solar energy providers) are changing the customer analytics scene for most utility companies. Utilities offer so many programs from time-of-use pricing to demand response and there are more coming on board every day with the onslaught of green energy programs and the potential of home energy management and electric vehicles. Directing these numerous programs to the right target markets would ensure greater participation and help utilities save on marketing costs. Aging customer information systems aren t going to cut it anymore. Diving a little bit deeper, as you can see in Figure 9, we segment these increasingly sophisticated analytics into two key areas: Customer operations: Analytics that focus internally on improving the efficiency and effectiveness of a utility s customer operations. This area includes meter data analytics, credit and collections, call center optimization, fraud detection, campaign management, customer segmentation, pricing optimization, and other customer operations. Actionable insights 10 UTILITY ANALYTICS INSTITUTE annual customer analytics report

11 INTRODUCTION Customer engagement: Analytics that support utility interactions with customers and improve their relationship with the utility through improved service, lower costs and better customer experiences. This area includes categories such as demand response, energy efficiency, distributed generation management, and other customer engagement. Figure 9. Key customer analytics areas Customer analytics Customer operations Customer engagement Meter data analytics Demand response Credit and collections Call center optimization Energy efficiency Fraud detection Table 1 defines each of these customer operations and customer engagement categories. Campaign management Customer Pricing optimization Other Distributed generation Other Table 1. Customer analytics sub-segment definitions Customer operations Meter data analytics Analytics that support meter data collection, estimation and validation activities. This area includes meter data management systems. Credit and collections Analytics that optimize the cash flow of utility companies, including billing, collections, and low-income customer programs. Call center optimization Analytics that assist utilities with planning and managing call center operations to accurately forecast workload and schedules and improve call center business processes to deliver better customer service and contribute to the utility s bottom line. Fraud detection Analytics that assist utilities with identifying, managing and preventing fraudulent activities. Campaign management Analytics that provide support for planning and tracking capabilities for customer marketing campaigns to enable utilities to effectively allocate marketing resources. Customer segmentation Analytics that assist utilities with segmenting customers into discrete groups that share similar characteristics to enable utilities to effectively serve and interact with those groups. Pricing optimization Analytics that support the planning and adjustment of electricity prices in response to changing demand and supply needs. Other customer operations Analytics that serve customer operations business processes, but do not fit into one of the above categories. Customer engagement Demand response Analytics that assist with modeling, planning and managing utility demand response programs, and communicating demand response requests to customers. Energy efficiency Analytics that assist utilities and utility customers with reducing the amount of energy required to for products and services. Distributed generation management Analytics that assist utilities and utility customers with planning, implementing and managing distributed resources including distributed generation, storage and electric vehicles. Other customer engagement Analytics that serve customer engagement business processes, but do not fit into one of the above categories. GET MORE CUSTOMER More than 100 insightful pages with nearly 80 tables and charts. Order your copy today: UTILITY ANALYTICS FINDINGS or call INSTITUTE Annual customer analytics report 11

12 SECTION APPENDIX TITLE D APPENDIX D: Analyst biographies H. Christine Richards, lead analyst Christine is a senior research analyst with the Utility Analytics Institute. Christine is researcher and writer whose areas of expertise include the utility industry, smart grid, utility analytics, renewable energy, economic development, regional planning and landscape architecture. Christine received her master s degree from Cornell University and graduated summa cum laude with a Bachelor of Science degree from Colorado State University. Mike Smith, principal-in-charge Mike is a 22-year veteran of the utility smart grid/it/ automation, information services and media business. He has served in a variety of leadership, research, sales, marketing, and positions throughout his career. In his two most recent positions, he was vice president and general manager, North America, for Spintelligent, a global leader in delivering events and media to the utility industry, and he was senior vice president of Sierra Energy Group, the research and analysis division of Energy Central. Mike has a Bachelor of Arts degree in economics from San Jose State University. Guy K. Anderson, analyst Guy s involvement with information technology covers more than 40 years. As a senior analyst and program manager with Sierra Energy Group, he manages the development and execution of the company s Enterprise Solution IntelliLead and works as a senior analyst and writer on proprietary consulting assignments, including writing market reports. Guy is a graduate of Trinity College in Hartford, Connecticut, and completed marketing studies at University of North Carolina in Charlotte. Kim Gaddy, analyst Kim Gaddy is currently engaged as an analyst supporting several different research initiatives at the Utility Analytics Institute and Energy Central. Previously, Kim held the position of senior director, client solutions for Vertex Business Services where her responsibilities ranged from product/services strategy development to the formation and management of strategic partnerships to business development. She has expertise in advanced analytics, demand side management, and customer management services. Kim has over 20 years of experience in the utilities and telecommunications sectors. Earlier in her career, Kim held leadership positions at AT&T in product management, regulatory affairs and sales. She holds a BBA from Texas Tech University and an MBA from St. Edward s University. Mary Ann Stewart, analyst Mary Ann Stewart is a licensed professional civil engineer with a diverse background in government, research, utility industry and consulting. She has worked in journalism, municipal works engineering, environmental regulatory policy and analysis, federal research programs, utility IT management, independent power production, and management consulting. A frequent speaker and writer on utility business and IT topics, Mary Ann is an analyst on numerous Energy Central publications and research initiatives. 12 UTILITY ANALYTICS INSTITUTE annual customer analytics report

13 SECTION TITLE Call it a two-decade seismic shift. The smart grid has sparked a world where change is the only constant. Evolving technology has generated unprecedented data volume and complexity with more to come. Fortunately, with these challenges come opportunities. Utility analytics professionals are in a position to transform many of their grid and customer operations as a direct result of learning how to leverage this new data-rich world. Energy Central s Utility Analytics Institute is the place where analytics leaders turn to for answers. The Utility Analytics Institute offers expertise, deep research, and networking venues to those who oversee grid and customer operations and are tasked with interpreting the data. Current services include: Education Learn, question and find answers to the challenges inherent in the new world of data analytics from the Executive Insight Series of reports. Networking From webinars to the Spring Summit and Fall Forum, utility professionals and solution providers connect to openly discuss and interpret the complex issues in data analytics. Custom Resources New custom research or personalized consulting? Draw upon unbiased research and consulting services from respected and experienced senior analysts and consultants. These professionals are committed to the energy industry and are passionate about providing guidance to analytics professionals. The Utility Analytics Institute s mission is to deliver the deepest understanding, knowledge, and expertise on how utilities are applying analytics to improve business practices, primarily as related to customer and grid areas of focus. We understand that utility professionals need timely and trusted information, direction, solutions and insights to navigate this often complex world of data analytics. Operations, decisions, and investments all depend upon it. Contact the Utility Analytics Institute for more on how that applies to you or UtilityAnalytics.com UTILITY ANALYTICS INSTITUTE Annual customer analytics report 13

14 THE ANNUAL CUSTOMER ANALYTICS REPORT IS NOW AVAILABLE: 2Two 1. Convenient Ways to Buy: 2. Purchase your report online at: Call and request the Annual Customer Analytics Report 2012 Annual customer analytics report Report contributors H. Christine Richards / Lead analyst Mike Smith / Principal-in-charge Guy K. Anderson / Analyst Kim Gaddy / Analyst Mary Ann Stewart / Analyst