2016 MAISY Utility Customer Databases, Software and Application Products
NEW FOR 2016 DATABASES: MAISY Databases have been extended to include additional residential psychographic data and 15-minute interval load data for
all customer records. 2016 databases reflect utility residential and commercial customer populations as of January 1, 2016.
MAISY Utility Customer Databases, Software and application products are an eneregy industry standard developed from informaton on more than 7 million individual electric utility customers. Individual cutomer records include detail on customer building, equipment, occupant, energy and hourly load characteristics for all US states, electric utility service areas and client-specified geographic areas.
2016 MAISY Utility Customer Databases - The full utility customer databases
Customer Segment Databases - Average or typical values for customer segments
ZIP Area Utility Customer Databases - ZIP-level averages
ZIP Databases With Solar Data - ZIP data plus PV data and future PV installations forecasts.
Customer Databooks - Summary customer, energy use and day-type/season load profiles for 436 customer segments
Software and Applications Products
MAISY EnergyApps Software - Access and analysis software
- NEW - Electric storage/PV application - Software analysis for battery and battery/PV markets and utility customers
Solar PV-Receptive Customer Leads - Model-based PV sales scores
Individual Customer Weather Risk Analysis - Risk assessment for REPs/ESCOs
Deciding on Segment Versus Individual Customer Databases
Segment versus Customer Data - How to determine the best customer information development strategy
Click here to see Answers to MAISY Database FAQ
NEW FOR 2016 DATABASES: MAISY Databases have been extended to include additional residential psychographic data and 15-minute interval load data for all customer records. 2016 databases reflect utility residential and commercial customer populations as of January 1, 2016
MAISY® (Market Analysis and Information System) Utility Customer Databases are the energy industry's most widely-used, authoritative source of utility customer energy use information available. MAISY database information has been used by utilities, energy service providers, energy service companies, equipment manufacturers, research organizations and other organizations interested in utility customer energy use. MAISY data have also been used to support US Department of Energy appliance and equipment efficiency standards development.
MAISY Utility Customer Databases include energy use, hourly loads, building, equipment, operating, occupant and other energy-related information for individual commercial and residential customers records including day-type (peak day, week day and weekend day for each of 12 months) and 8760 hourly loads for individual end uses as well as 15-minute whole building and end-use interval electric loads data.
Databases have been developed from information on more than 7 million individual utility customers throughout the US and Canada, providing a representative sample of residential and commercial for metropolitan areas, utility service areas, states and provinces.
Databases reflect information from hundreds of different customer and market data sources including onsite customer surveys, utility and fuel supplier billing data, government, association and proprietary data, and other sources including ongoing Jackson Associates utility customer data development. Databases are continuously updated to reflect important recent trends in the most important determinants of residential, commercial and industrial energy use.
Large customer samples within geographic areas maintain the diversity of actual customer populations, providing a more accurate analysis of customers, markets and market segments compared to "average" customer information.
Additional MAISY Utility Customer database topics are provided below.
|Individual Customer Data||Geographic Detail|
|Detailed Energy Use Information||Other Customer Data|
Note:Industrial data and databases are provided on a case-by-case basis. Contact Jackson Associates for further details.
The following links document database variables included in the Databases in more detail:List of Commercial Database Variables
List of Residential Database Variables
In addition to annual and monthly energy use, equipment, building, operating characteristics and other customer information, MAISY Databases include hourly electric, natural gas and fuel oil loads for each customer record. Hourly loads are available as day-type /month summaries (week day, weekend day, peak day for each of the 12 months) and in full-year 8,760 formats for electric, natural gas and oil energy use as whole-building loads and for individual end uses (e.g., space heat, air conditioning, etc.). Hourly loads data are presented for each customer record in an Excel workbook. 15-Minute load whole building electric load data are also available.
Load data are weather-adjusted to reflect normal hourly weather data. Users can access and evaluate hourly loads for individual customer records or for any grouping of customers defined by database variables (e.g., heating fuel, business type, square feet, number of children, etc.) The large number of customers in the databases and the database design permits users to develop hourly load information for detailed customer types and market segments based on relevant customer characteristics.
MAISY databases are developed specifically to support energy use and energy-related analysis of user-specified, detailed customer segments (e.g., households in single family dwelling units with incomes less than $25,000, small office buildings with electric space heating built before 1980, and so on).
This deep drill-down capability is provided by a database sample design that reflects knowledge of our clients’ applications. For example, if the population of customers includes a 10 percent electric space heating saturation, a random sample of 2000 would provide only about 200 electric space heating customers. However, with 20 commercial building types, the confidence interval around building-information would be quite high especially when one drills down to evaluate electric-heated buildings in different size categories. We know that electric space heating customers are of interest to our clients’ applications so we boost the number of electric space heating customers pulled from the master MAISY database to ensure that users can conduct multiple drill downs on electric space heating customers with confidence. We apply the same criteria with other important customer variables. MAISY database record weights automatically adjust for this “oversampling” so that total customers, energy use and other customer segment characteristics always correctly reflect population values.
Commercial and Residential Customer Segment Databases include hourly & 15-minute electricity use and other segment average values derived from the full MAISY Utility Customer Databases including information on more than 7 million US utility customers. Individual utility customer records are processed and utility customer information is developed to reflect customers within each customer segment. Electricity use is provided as hourly or 15-minute electric loads for customer segments defined by customer characteristics, location (service area, weather zone, zip code, etc.) electricity use and other factors.
Customer segment database information supports new technology product development and market assessment, marketing and sales market sizing and evaluations, and other applications that utilize information on markets and market segments.
In addition to electric load data, additional information is provided for each segment including number of customers and average or typical characteristics of customers in each segment. The table below illustrates typical detail associated with both Commercial and Residential Databases.
Segment definitions (e.g., ranges of floor space, peak kW, annual kWh, household income, etc.) are determined in collaboration with JA clients to meet technology development and/or marketing needs.
- How do hourly or 15-minute load profiles vary across customer segments and what are the impacts on product design and system cost?
- How do customer financial benefits vary across customer segments?
- Which customer segments should marketing and sales campaigns focus on to offer the greatest customer energy bill savings?
- What customer characteristics are most closely associated with the greatest energy bill savings?
- What operational strategy maximizes customer electric bill savings given utility rate structures and incentives?
- How many potential customers are associated with different customer segments?
- What are the implications of load profiles on technology performance, control strategies, lifetime, and other operating and maintenance issues?
- Apply segment-specific load profiles in marketing material targeted to individual segments
- Apply segment-specific load profiles in direct sales contacts to illustrate operation and economic benefits to prospective customers
- Scale load profiles using customer annual or monthly energy use to develop customer hourly load estimates
Segment electric load data is provided in Excel Workbooks as illustrated with the Example workbook below, making access and evaluation easy and facilitating data export to other platforms.
Standard MAISY databases are provided in Excel workbooks which include a variety of standard Excel data processing capabilities.
Jackson Associates also develops custom database interfaces to facilitate and automate client-specific analysis needs. MAISY EnergyApps provide analysis based on user-specified customer segment characteristics of interest such as SIC/NAICS code, floor space, operating hours, ZIP codes etc. (Commercial) or income, demographics, ZIP codes, etc. (residential) along with application detail such as cost of service characteristics, pricing products and so on. EnergyApps are available to support REP, ESCO, combined heat and power analysis, demand response, energy efficiency and other applications.
EnergyApps extend the level of customer information and analysis detail significantly with internal EnergyApp modeling and analysis. For example, if the user specifies a zip code in the user interface, weather adjustments are applied to heating, air conditioning and ventilation energy use and hourly loads.The following links provide additional MAISY database information Additional information on MAISY EnergyApps
The MAISY system permits users to select individual customers or customer segments based on dozens customer characteristics. Pick any combination of business type, floor space, operating schedules, space heating fuel, year of construction and many other variables to zero in on a specific customer type or market segment.
What about other load-profiling systems that offer 12, 36 , 75 or some other limited number of fixed customer segments? To represent 13 commercial business types; electric, gas and oil heat; small, medium and large buildings requires 117 prototypes or "typical" buildings. Add in age categories and more than 200 "fixed prototypes" would be required, well beyond the scope of these "fixed" systems. With MAISY, customer and segment selections provide hundreds of possible definitions with nearly unlimited choices of customer characteristics. Only MAISY provides the detail and flexibility required to reflect the extensive customer and segment detail required in today's energy markets.
Relying on "prototype and typical" is similar to analyzing a "typical" family which consists of two adults and 0.6 children - it may reflect an average but it may also provide misleading results when used to understand customers and markets, to develop programs to fit the needs of individual customer segments, to evaluate the profitability of serving these customers or to evaluate markets for new technologies.
Sources of load profile data which rely on fixed customer segments (e.g. large, medium and small offices) typically develop hourly load data with engineering models (e.g., DOE2) of a single "prototype" building. The aggregate nature of these representations misses the variation that exists among individual buildings within these segments, hiding important market information. For instance, a particular electric rate structure may provide a competitive profit based on an entire segment's single prototype load profile; however, analysis of subsets of the segment (which can be performed with MAISY but not with the "prototype or typical" load profile approach) may reveal significant diversity in profit levels across customer sub-segments such that some customers are provided power at a loss while profit margins on other customers result in cream-skimming targets for other suppliers.
Similarly, evaluating markets for new technologies or potentials for energy efficiency initiatives requires consideration of the full range of customers within a market or utility service area. The average load profile may reflect little potential hiding the fact that a significant portion of the market with different load characteristics provides great potential. For more information on this topic see Avoiding "Prototype" and Average Load Data Aggregation Errors.