Media selection for database marketers

Hughes, Arthur Middleton; Mang, Paul Y.

doi:10.1002/dir.4000090109

Cited by 25 publications

(27 citation statements)

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“…According to the research of Arthur Hughes [10] where the variables R, F and M is the value of the attributes recency, frequency and monetary, and the parameter λ r , λ f and λ m is the weights of the variables R, F and M. As usual, the weights are set by personal experience. Although it makes the calculation simple and fast, the result is not good enough to justify objectivity and impartiality.…”

Section: Rfm Customer Relationship Management Modelmentioning

confidence: 99%

The Application of Bayesian Classification Theories in Distance Education System

Ma¹,

Wei

Hu³

et al. 2011

IJMECS

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Abstract-With the vigorous application of distance education in recent years, the biggest challenge that the learners and managers are facing today is how to institute the training courses and choose the learning resources according to the personal characteristics of learners. It is subjective to arbitrarily decide the learning resources. This study presents a new constructional method, based on the Bayesian networks of courses relationship. This method uses the feedback of learning resources from the learners and examination results of training courses as data samples. And a new procedure is presented, joining quantitative value of RFM model and naïve Bayesian algorithm, to classify the learners and offer more support to make decision. Moreover, the experimental results demonstrate that the algorithm is efficient and accurate, and the Bayesian network method can be used in other Electronic Commerce System

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Section: Rfm Customer Relationship Management Modelmentioning

confidence: 99%

The Application of Bayesian Classification Theories in Distance Education System

Ma¹,

Wei

Hu³

et al. 2011

IJMECS

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“…For instance, lifestyle surveys, focus groups, customer surveys, market research, and geographical socioeconomic data included in published official government census statistics can be used to categorise people (e.g. Andon, Baxter, & Bradley, 2001;Blattberg, 1987;Hughes & Wang, 1995;Sturdy & Morgan, 1993).…”

Section: Finding Out About the Customermentioning

confidence: 99%

“…see Hughes & Wang, 1995;Jenkinson, 1995) and extensive and advanced information systems have become central to the marketing function (Talvinen, 1995). Consequently, for the information technology profession, provision of "data warehousing" has become routine (Cooper, Watson, Wixom, & Goodhue, 2000).…”

Section: Finding Out About the Customermentioning

confidence: 99%

“…Behavioural segmentation based on the actual purchase behaviour of customers can also be used to clarify categories in relation to the dimensions of recency of last purchase, frequency of purchases, types of purchases, and amount spent, although such factors are extremely changeable (e.g. Blattberg, 1987;Gordon, 1998: 95-96;Hughes & Wang, 1995). As Reich (1991: 277) has noted, categorisation of people is increasingly carried out on the basis of socioeconomic census data, sorted and aggregated by postcode areas.…”

Section: Customer Segmentationmentioning

confidence: 99%

“…Segmentation and associated CRM strategies can be used in relation to customer targeting and retention strategies, media/channel selection for advertising and promotion, product features, pricing, discounting, customer service and support (e.g. Dwyer, 1989;Hughes & Wang, 1995;Jackson, 1992;Keane & Wang, 1995).…”

Section: Customer Segmentationmentioning

confidence: 99%

See 2 more Smart Citations

Beyond Privacy: The Ethics of Customer Information Systems

Boyce¹

2002

InSITE Conference

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The rise of an ostensibly customer-centred corporate culture in the 1980s recognised the importance of "knowing the customer". As a result, customer information systems and associated practices of marketing, customer segmentation, and customer accounting have become significant elements in corporate customer-focus strategies. This paper discusses a range of ethical considerations that flow from the use of customer information systems and critically examines these systems in their organisational and social context. It is well-recognised that customer information systems give rise to concerns of privacy, but this paper raises perhaps more important ethical issues that relate to organisational transformation and significant links to issues of access, equity, alienation, and social exclusion.

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Customer lifetime value: Marketing models and applications

Berger

Nasr

1998

Journal of Interactive Marketing

751

451

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Customer lifetime value has been a mainstay concept in direct response Department at the School of marketing for many years, and has been increasingly considered in the Management, Boston University. field of general marketing. However, the vast majority of literature on the topic (a) has been dedicated to extolling its use as a decisionmaking criterion; (b) has presented isolated numerical examples of its calculation/determination; and (c) has considered it as part of the general discussions of profitability and discussed its role in customer acquisition decisions and customer acquisition/retention trade-offs. There has been a dearth of general modeling of the topic. This paper presents a series of mathematical models for determination of customer lifetime value. The choice of the models is based on a systematic theoretical taxonomy and on assumptions grounded in customer behavior. In NADA I. NASR is a doctoral student in Marketing at the School addition, selected managerial applications of these general models of of Management, Boston University. customer lifetime value are offered.

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Media selection for database marketers

Cited by 25 publications

References 0 publications

The Application of Bayesian Classification Theories in Distance Education System

The Application of Bayesian Classification Theories in Distance Education System

Beyond Privacy: The Ethics of Customer Information Systems

Customer lifetime value: Marketing models and applications

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