Development of a data analytics-driven information system for instant, temporary personalised discount offers

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dc.contributor.advisorBekker, James F.en_ZA
dc.contributor.authorEls, Zandalineen_ZA
dc.contributor.otherStellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.en_ZA
dc.date.accessioned2019-02-19T09:36:13Z
dc.date.accessioned2019-04-17T08:33:47Z
dc.date.available2019-02-19T09:36:13Z
dc.date.available2019-04-17T08:33:47Z
dc.date.issued2019-04
dc.descriptionThesis (MEng)--Stellenbosch University, 2019.en_ZA
dc.description.abstractENGLISH ABSTRACT: Enterprises have started including the targeting of customers with personalised discount offers in their business strategies in order to seek a competitive advantage over their peers. This innovation has been made possible by the integration of knowledge and new technology such as data analytics, mobile- and cloud computing and the internet-of-things. Along with these digital technologies, the emphasis on customer experience became the distinguishing factor amongst retail outlets. A novel approach is presented in this study to create personalised discount offers during a customer's visit to one of many participating retail outlets. It focuses on the individual customer's purchasing history, which makes it different from the loyalty programmes that are currently in use. A simulator is developed to create pseudo-customer data containing purchasing behaviour, whereafter a demonstrator is developed which provides a holistic view of the customer's behaviour in retail outlets. The demonstrator creates instant, temporary personalised discount offers based on the purchasing tendencies of that customer across various retail outlets. The model illustrates the utilisation of customer behavioural data to identify unique cross-selling and upselling opportunities to ultimately improve customer experience. The cross-selling and upselling creates opportunities for alternative revenue streams and this study provides a business case to display the business value of this system.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING: Ondernemings het begin om kli ente te teiken deur persoonlike afslagaanbiedings in hul sakestrategie e in te sluit ten einde 'n mededingende voordeel oor hul eweknie e te soek. Hierdie innovasie is moontlik gemaak deur die integrasie van kennis en nuwe tegnologie soos data-analise, mobiele- en wolkrekenaars en die internet-van-dinge. Saam met hierdie digitale tegnologie het die klem op kli enteervaring die onderskeidende faktor onder kleinhandelaars geword. `n Nuwe benadering word in hierdie studie aangebied om persoonlike afslagaanbiedings te skep tydens 'n kli ent se besoek aan een van die deelnemende kleinhandelwinkels. Dit fokus op die individuele kli ent se aankoopgeskiedenis, wat dit anders maak as die lojaliteitsprogramme wat tans gebruik word. `n Simulator is ontwikkel om pseudo-kli entedata te skep wat koopsgedrag bevat, waarna 'n demonstrator ontwikkel is wat 'n holistiese oorsig gee van die kli ent se koopgedrag in kleinhandelwinkels. Die demonstrator skep onmiddellike, tydelike persoonlike afslagaanbiedings gebaseer op die aankoopneigings van daardie kli ent by verskillende winkels. Die model illustreer die gebruik van kli entegedragdata om unieke kruis- en opverkoopsgeleenthede te identifiseer ten einde die kli ente-ervaring te verbeter. Die kruis- en opverkope skep geleenthede vir alternatiewe inkomstestrome en hierdie studie bied 'n besigheidsgeval om die besigheidswaarde van hierdie stelsel te vertoon.af_ZA
dc.format.extentxiv, 168 pages ; illustrationsen_ZA
dc.identifier.urihttp://hdl.handle.net/10019.1/106194
dc.language.isoen_ZAen_ZA
dc.publisherStellenbosch : Stellenbosch Universityen_ZA
dc.rights.holderStellenbosch Universityen_ZA
dc.subjectPersonalised discount offersen_ZA
dc.subjectData analyticsen_ZA
dc.subjectBig dataen_ZA
dc.subjectSurvival analysisen_ZA
dc.subjectCustomer purchase behavioren_ZA
dc.subjectCustomer behavior -- Data processingen_ZA
dc.subjectUCTD
dc.titleDevelopment of a data analytics-driven information system for instant, temporary personalised discount offersen_ZA
dc.typeThesisen_ZA
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Masters Degrees (Industrial Engineering)