Utility Customer Churn Radar
Probably the world’s most advanced utility customer loyalty prediction system
An unrivaled 12 years of liberalised market churn analysis, covering the entire global residential switching period, all liberalized regions, hundreds of thousands of customers and scores of utility companies, has been conducted by Dr Philip E. Lewis and his research teams. The result is a new state of the art churn predictor, integrating what is probably the most comprehensive understanding of utility customer loyalty dynamics available anywhere in the world.
This system is a precise method designed to integrate into existing or greenfield CIS/CRM systems. Depending on how it is applied it can be used to compliment loyalty prediction systems which utilities already have in place, or it can be used as a stand alone prediction system. The system makes use of the best available data, be it at a segment or (ideally) individual customer level. Its complexity depends upon the resources and CIS capabilities of the utility organization into which it is integrated and it can be up-scaled, down scaled or simply adjusted as the organization’s develops. It can even be applied and tested on a small, pilot scale as an initial introduction to the organization.
Unlike other, more simplistic systems, VaasaETT’s system Utility Customer Churn Radar enables the organization to learn about the complexities of its customers’ loyalty behaviour. Data which is received through the system is constantly analyzed to develop more accurate future understanding, formulation and therefore prediction. Despite the (variable and customizable) complexity of the data collection and analytics however, the output information provided to decision makers is extremely simple and strategically oriented. The operation of the system too, is easily manageable by typical marketing analysts.
The system makes use of a wide range of data, ranging from call centre information and customer background and demographics data, through to marketing research information, customer feedback and complaint information, price change, competitor analysis information and other market environment information, as well as past customer behaviour data and much more. All this information is then combined scientifically with rules and formulas representing state of the art knowledge concerning the dynamics of utility customer loyalty behaviour.
The outcome is a truly innovative and advanced integration of CIS data for the purpose of providing simple multi-user access to quick & regularly updatable customer loyalty predictions as well as the rapid consideration and identification of the likely impact of strategic responses and scenarios on both customer loyalty and value.
The system does not only provide temporary benefits, but promotes corporate transfer of knowledge for tactical and strategic use by marketing managers, CIOs, CFOs, CCOs & CEOs while ensuring that the core corporate knowledge remains in-house regardless of changes in personnel.
For more information please contact: Philip Lewis at +358 40 529 5852 or firstname.secondname@vaasaett.com
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December 4th, 2007
