An approach to improving marketing campaign effectiveness and customer experience using geospatial analytics

Brink, Michael Philippus (2017-03)

Thesis (MEng)--Stellenbosch University, 2017.

Thesis

ENGLISH ABSTRACT: This thesis discusses a case study in which a South African furniture and household goods retailer wishes to improve its marketing campaigns by employing location-based marketing insights, and also to prioritise customer satisfaction. This thesis presents two methods of achieving these improvements to the retailer’s business. The first method uses customer delivery addresses and population data (for a sample area) to identify the location-based profiles of customers. The locations are restricted to regions within Gauteng, and key variables such as age, race, income, and family size are used to create the customer profiles. The second method builds on the intelligence produced by the customer profiles by presenting an option for improving location-based marketing campaigns. This is achieved by identifying customer clusters based on the home addresses to which purchased goods were delivered. A grid-based clustering method is applied using the sample area contained in Gauteng. This thesis shows how spatial data can be used to solve the business problems presented by the furniture retailer. The findings show how the dwelling types of customers can be used to explain why some areas are more clustered than others. This study summarises how customer profiles and location-based density clusters can be used to improve the retailer’s strategic marketing strategies, and also improve the customer experience by enhancing customer-product association logic. Several recommendations are made to improve on the results produced in this study.

AFRIKAANSE OPSOMMING: Hierdie tesis bespreek ’n gevallestudie waarin ’n Suid Afrikaanse meubel-en-huishoudelikegoedere handelaar beoog om hul bemarkingsveldtogte te verbeter deur plek-gebaseerde bemarkingsinsigte en verder, om kliënt-tevredenheid te prioriteseer. Die tesis stel twee metodes voor wat mik om die verbeteringe te bereik. Die eerste metode maak gebruik van ’n steekproef kliënte se huisaddresse waarheen aflewerings plaasgevind het vir meubels en ander huisgoedere wat gekoop is. Bevolkingsdata is gebruik om die administratiewe areas te identifiseer waarin die verskeie kliënte se addresse geleë is. Profiele is geskep vir al die geografiese segmente van die kliënte. Die word bepaal deur die grense van al die munisipale distrikte binne Gauteng. Veranderlikes soos ouderdom, inkomste, gesinsgrootte, en ras word gebruik om die segmente te klassifiseer. Die tweede metode bou op die intelligensie wat in die eerste metode geskep is deur kliëntebondels te identifiseer. ’n Roosterbondelings metode is toegepas op die steekproefruimte wat omskryf is deur die area van Gauteng. Hierdie tesis wys hoe die gebruik van ruimtelike data gebruik kan word om die besigheidsprobleme, wat voorkom in die gevallestudie, op te los. Die resultate wys verder hoe die woning tipes van sekere bondels gebruik kan word om te verstaan waarom sekere bondels digter voorkom as ander. Die studie som op hoe kliënteprofiele en plek-gebaseerde kliëntebondels waarde kan toevoeg deur die kleinhandelaar se bemarkingsstrategië te verbeter asook die kliënte-tevredenheid. Verskeie aanbevelings word voorgestel om die resultate in die tesis te verbeter en die studie te vergroot.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/101034
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