MAISY Energy Use and Hourly Loads Databases Summary |
 
Deciding on Segment Versus Individual Customer DatabasesMAISY Utility Customer Information is available in three basic formats
While the market segmentation described above can identify attractive target markets, variation in individual customer characteristics wihtin customer segments often requires a second assessment step. Even though customer hourly load data are increasingly available from utilities, this information may not be available until the sales process has proceeded for several weeks or months. Evaluating customer loads in areas not yet served requires load data prior to initial customer contacts. MAISY Profiler software provides individual customer hourly load data by matching individual customer characteristics specified by the user (e.g., business/SIC type, building age, daily operating hours, etc.) with utility customer records in the full MAISY Database. These customer-specific loads can then be applied to conduct an initial business case analysis for the technology application prior customer contact and after customer contact to avoid investing additional marketing and sales resources for unattractive customer appliations. Profiler applications are customized for each client application and can include technology, business case and profitability analysis in addition to providing customer-specific hourly loads. The full MAISY Utility Customer Databases are available for clients who prefer to conduct their own analysis of utility customers. As indicated above, the appropriate MAISY data format depends on client analysis objectives. Selecting the wrong data format can actually provide the wrong answer to specific questions. To see an example see Assessing Retail Utility Market Profit Potentials: Pitfalls of Traditional Analysis. Jackson Associates Works With Clients to Define the Most Appropriate and Cost-Effective Customer Database Analysis StrategyWhile segment average loads are attractive because the smaller quantity of data is easy to work with and segment level databases are usally less expensive, data that are too highly aggregated suffer from a problem called aggregation error which means that the aggregation level is misrepresenting information of interest. For example, if customer value of a technology depends on specific electric load profile characteristics, and those load profile characteristics vary significantly among customers within a segment (e.g. fast-food restaurants > 10 kw and <30 kW peak demand), knowledge on the distribution of customer characteristics is more useful than the average of these characteristics for the entire sector. In fact, customer valuation for the average customer may show no market potential whereas 30 percent of customers could have an appropriate load profile worth pursuing with target marketing. This problem, which is illustrated with retail electricity provider customer profitability analysis, exists for technology analysis, marketing and sales analysis (see Assessing Retail Utility Market Profit Potentials: Pitfalls of Traditional Analysis.Jackson Associates (JA) works closely with clients to fully understand data needs and analysis applications providing recommendations for the most cost-effective analysis strategy to meet data needs. JA also provides free telephone support for MAISY database applications for organizations who prefer to obtain the full customer databases and conduct segment and individual customer analysis inhouse. |