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Data Mining Strategies for CRM Negotiation Prescription Problems [chapter]

Antonio Bella, Cèsar Ferri, José Hernández-Orallo, María José Ramírez-Quintana
2010 Lecture Notes in Computer Science  
In some data mining problems, there are some input features that can be freely modified at prediction time.  ...  a regression problem, and (2) maximise profits and derive negotiation strategies.  ...  Conclusions This paper introduces a number of new contributions in the area of data mining and machine learning which can be useful for many application areas: retailing, control, prescription, and others  ... 
doi:10.1007/978-3-642-13022-9_52 fatcat:yfhpxlswsvg4nncr335npj2mfe

Using negotiable features for prescription problems

Antonio Bella, Cèsar Ferri, José Hernández-Orallo, María José Ramírez-Quintana
2010 Computing  
We illustrate the point in the area of Customer Relationship Management (CRM), where we deal with the general problem of prescription between products and customers.  ...  We introduce the concept of negotiable feature, which leads to an extended taxonomy of CRM problems of greater complexity, since each new negotiable feature implies a new degree of freedom.  ...  Keywords: data mining, profit maximisation, function inversion problem, global optimisation, negotiation, CRM, ranking, probability estimation, negotiable features, Montecarlo method.  ... 
doi:10.1007/s00607-010-0129-5 fatcat:f25lrbqfinhhbhtn73zhzi4qfq

ORANGE: Outcome-Oriented Predictive Process Monitoring based on Image Encoding and CNNs

Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba, Giuseppe Modugno
2020 IEEE Access  
We processed data of 1388 events logged on 29 months during the execution of 140 traces of the negotiation and sales management process into CRM.  ...  software company -MTM Project srl. 1 Coupling ORANGE to CRM, we are able to engage inputs and customers' performance data to predict success outcomes on their negotiations.  ...  Her current research interests include data mining with spatio-temporal data, data streams and event logs.  ... 
doi:10.1109/access.2020.3029323 fatcat:2r26nh7u7vgfxlhms2mleuwewe

Article Abstracts

2004 Interactive Marketing  
The final reference number under each abstract is also used for this purpose (see reprint service on p. 184) Article Abstracts Each abstracted article is awarded 0-5 stars for each of four qualities: (  ...  The bold items in the margin describe the subject matter and are keywords for text retrieval.  ...  Discusses future trends and strategy. Emphasises the need for data integrity and internal structural change.  ... 
doi:10.1057/palgrave.im.4340283 fatcat:e72kh7kx6ffbjkgladj32tsvva

Customer relationship management in call centers: The uneasy process of re(form)ing the subject through the 'people-by-numbers' approach

Catrina Alferoff, David Knights
2008 Information and organization  
But the detailed use of statistical data and information on both behaviour and performance is not just a problem for call center staff and their customers.  ...  In the following quote two CSRs discuss the problem that CRM codes for discounts to particular customers creates for their time performance, but also, interestingly, how a CSR might use their discretion  ... 
doi:10.1016/j.infoandorg.2007.10.002 fatcat:n4m2a2gx3rhe7mzyalule7kg6y

E-CRM dilemmas in developing markets: The case of a tourism company in Serbia

Alexandros Kapoulas, Dražen Ratković
2015 European Journal of Tourism Research  
They were identified as the key decision makers in the process of adoption of e-CRM at the "Alpha" tour operator.  ...  By using a case study methodology, this paper reflects the attitudes of top management in Serbia's biggest tourist agency regarding e-CRM implementation, where five top managers were interviewed, starting  ...  e-CRM practice for Serbian model of e-CRM in tourism.  ... 
doi:10.54055/ejtr.v9i.163 fatcat:lsmqgkgugnblbkxojge44rr7hi

Giant Food and Elensys: Looking Out For Customer Gross Privacy Invasion?

Mary J. Culnan
2005 Communications of the Association for Information Systems  
The case also provides an opportunity for students to grapple with the challenges of developing a "privacy sensitive" implementation strategy for Giant and for CRM programs more generally.  ...  This case describes the privacy issues surrounding Giant Food's decision to outsource a prescription drug compliance program to Elensys.  ...  This separation made it possible to do data mining operations on the prescription information without ever linking this information to specific patients.  ... 
doi:10.17705/1cais.01614 fatcat:6yojqqebprdzrmils6rocfi3xe

Abstracts

2006 Journal of Direct Data and Digital Marketing Practice  
Discusses website design, which should work equally well for all ages, and brand loyalty.  ...  Expects it not to be a burden on but a contributor to the economy: notes the trend for increasing numbers of men to continue working after 65.  ...  Discusses the development of one such course in data mining, positioned at the meeting point of marketing, IT and analytics.  ... 
doi:10.1057/palgrave.dddmp.4340568 fatcat:52iflbenavhsdack2rx7bfssma

Beyond the Equator (Principles): A Forum on Community Benefit Sharing in Relation to Major Land Alteration Projects and Associated Intellectual Property Issues in Cultural Heritage Held at the Meeting of the Society for American Archaeology, Honolulu, 5 April 2013

John R. Welch, Ian Lilley
2013 International Journal of Cultural Property  
Several participants recommended specific practices for information and benefit sharing; others offered more general strategies  ...  Such critiques continue to emerge despite decades of confrontations, negotiations, and collaborations, as well as many recent advances in environmental protection and mitigation.  ...  obtaining data pertinent to these agendas, and to interpret and mobilize data sets in ways that generally prioritize CRM practitioner and client interests.  ... 
doi:10.1017/s0940739113000258 fatcat:bvk3dztw3vc7fnvry5xvilmaou

Segmentation and customer insight in contemporary services marketing practice: why grouping customers is no longer enough

Christine Bailey, Paul R. Baines, Hugh Wilson, Moira Clark
2009 Journal of Marketing Management  
Acknowledgements The authors would like to thank representatives of Barclays, BT Global Services, Cisco Systems, O2 and the Post Office for agreeing to take part in the study.  ...  When the segmentation strategy was launched in 2004, managers had no products for which they owned the customer data, only 'anonymous transactions', relying on external market research data to understand  ...  Consequently, O2 installed predictive data-mining software, which enabled it to produce large volumes of customer response predictions very quickly.  ... 
doi:10.1362/026725709x429737 fatcat:tpseqy6debcapaqhf5uiummrwy

The Translated Strategic Alignment Model: A Practice-Based Perspective

Isabelle Walsh, Alexandre Renaud, Michel Kalika
2013 Systèmes d information & management  
These dashboards involved data analysis, data mining and business intelligence.  ...  For example, if business strategy is expressed through managerial IT needs to implement some CRM software, and if commercial staffs do not perceive the need for this specific software in their work context  ...  about interviews and interviewees Appendix C1: Interviews conducted in corporations A (year 2008), B (year 2009) and C (years 2008-2009) while people were solving or attempting to solve identified problems  ... 
doi:10.3917/sim.132.0037 fatcat:pcl2oiggijdfli5t2terbnuxc4

Abstracts

2000 Interactive Marketing  
Abstracts Each abstracted article is awarded 05 stars for each of four qualities: (1) depth of research (2) value in practice (3) originality of thinking (4) readability for non-specialists.  ...  No abstract is included for any article awarded less than seven stars overall.  ...  to business analysts), data mart (specialised set of information on a particular aspect of the enterprise), and data mining (analysis of data for undiscovered relationships), as well as such acronyms  ... 
doi:10.1057/palgrave.im.4340086 fatcat:hwaqmnjj2rhqhf5by6ewnyacfy

Decision Support System Based on Effective Knowledge Management Framework To Process Customer Order Enquiry [chapter]

Chike. F.
2010 Decision Support Systems  
They therefore need to develop an effective knowledge management strategy both for the benefit of their employees and customers in order to support decision making process and thereby remain sustainable  ...  There is a need therefore to develop robust decision support systems to capture, store, share and leverage data, information and knowledge.  ...  Such information can be used for quoting, approving and negotiation.  ... 
doi:10.5772/39455 fatcat:usqqtfn6qvcvjncgwdualwypnq

Using big data in telecommunication companies: A case study
English

Rehman Sajjad, Al-Raqom Dhary
2020 African Journal of Business Management  
Big Data was managed by using diverse systems such as Cloudera Data Hub (CDH) and SaaS. For data security, these companies made different arrangements.  ...  Three companies used big data systems for diverse functions and applications. These companies needed to develop competent professionals for data management, security, and other applications.  ...  The strategy of data management requires the implementation of a CRM system to avoid poor customer data quality.  ... 
doi:10.5897/ajbm2019.8874 fatcat:6qvfp35o3netrmbu577qq2slt4

Work of being an adult patient with chronic kidney disease: a systematic review of qualitative studies

Javier Roberti, Amanda Cummings, Michelle Myall, Jonathan Harvey, Kate Lippiett, Katherine Hunt, Federico Cicora, Juan Pedro Alonso, Carl R May
2018 BMJ Open  
Search strategy is included in supplementary appendix 1. For a first set of studies, titles and abstracts were independently screened by AC, MM and CRM, disagreements resolved by JH.  ...  See figure 1 for screening and selection process. data extraction and analysis Data outlining study characteristics are shown in table 2.  ... 
doi:10.1136/bmjopen-2018-023507 pmid:30181188 pmcid:PMC6129107 fatcat:s6q3e33dhjbw5m3yyk42w2hqf4
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