Powergen: The journey to marketing optimisation
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: marketing optimisation, propensity modelling, managing for value, data analysis
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Mark Perrett E.ON UK Newstead Court Little Oak Drive Annesley, Nottingham NG15 0DR, UK Tel: + 44 2476 181009 E-mail: [email protected]
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Powergen: The journey to marketing optimisation Mark Perrett Received: 5 January 2007
Abstract Use of propensity modelling to improve performance of direct marketing activity can be very effective on a campaign by campaign basis. Increasing sophistication in the way in which propensity models are applied can also demonstrate dramatic results. This article provides a case study to demonstrate the impact of applying different propensity models (value and channel propensity) within a service business, providing evidence of significant performance gains without any change to business processes. Journal of Direct, Data and Digital Marketing Practice (2007) 9, 76–83. doi:10.1057/palgrave.dddmp.4350068
Introduction Is Direct Marketing an art or a science? Probably both and it does not actually matter whether one favours the creative or the analytical facets — good practice requires strength in both areas. It is, however, clear that it is possible to bring a deeply analytical approach to direct marketing and achieve significant benefits in terms of effectiveness. From an organisational perspective, increased campaign response and lower sales costs will always be desirable, no matter how ‘customer centric’ an organisation claims to be. It is also likely, however, that improved customer targeting will actually decrease customer complaints about direct marketing. If one is contacting those who are more likely to respond to a targeted and relevant offer, in a channel that they are likely to prefer, surely that is better than antagonising them with irrelevant offers in inappropriate channels at the wrong time. This latter ‘side effect’ of better targeted direct marketing may well prove to be more value-enhancing in the long run than the obvious increases in response and conversion rates often cited as the ‘return on investment’ for propensity modelling and customer analytics. Customer contact is becoming a finite resource, and there are increasing numbers of consumers who are making significant efforts to opt out of direct marketing. Reference to Telephone Preference Service registrations over the past two years illustrates this point (Figure 1): There are few large B2C organisations that do not practise some form of propensity modelling, either through in-house facilities or via one of the many marketing services organisations that provide some
© 2 0 0 7 PALGRAVE MACMILLAN LTD 1746- 0166 $30.00 VO L .9 NO.1 PP 76– 83. www.palgrave-journals.com/dddmp
Journal of Direct, Data and Digital Marketing Practice
Powergen: The journey to marketing optimisation degree of analytics services. Not that many organisations, however, appear to have continued to the next logical stage of full marketing optimisation, across multiple campaigns, over an extended (six to twelve month) timescale. This pa
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