Development of a data analytics-driven information system for instant, temporary personalised discount offers
dc.contributor.advisor | Bekker, James F. | en_ZA |
dc.contributor.author | Els, Zandaline | en_ZA |
dc.contributor.other | Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. | en_ZA |
dc.date.accessioned | 2019-02-19T09:36:13Z | |
dc.date.accessioned | 2019-04-17T08:33:47Z | |
dc.date.available | 2019-02-19T09:36:13Z | |
dc.date.available | 2019-04-17T08:33:47Z | |
dc.date.issued | 2019-04 | |
dc.description | Thesis (MEng)--Stellenbosch University, 2019. | en_ZA |
dc.description.abstract | ENGLISH 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.abstract | AFRIKAANSE 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.extent | xiv, 168 pages ; illustrations | en_ZA |
dc.identifier.uri | http://hdl.handle.net/10019.1/106194 | |
dc.language.iso | en_ZA | en_ZA |
dc.publisher | Stellenbosch : Stellenbosch University | en_ZA |
dc.rights.holder | Stellenbosch University | en_ZA |
dc.subject | Personalised discount offers | en_ZA |
dc.subject | Data analytics | en_ZA |
dc.subject | Big data | en_ZA |
dc.subject | Survival analysis | en_ZA |
dc.subject | Customer purchase behavior | en_ZA |
dc.subject | Customer behavior -- Data processing | en_ZA |
dc.subject | UCTD | |
dc.title | Development of a data analytics-driven information system for instant, temporary personalised discount offers | en_ZA |
dc.type | Thesis | en_ZA |