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

Thesis (MEng)--Stellenbosch University, 2017.

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Bibliographic Details
Main Author: Brink, Michael Philippus
Other Authors: Van Rensburg, Antonie
Format: Thesis
Language:en_ZA
Published: Stellenbosch : Stellenbosch University 2017
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access_status_str Open Access
author Brink, Michael Philippus
author2 Van Rensburg, Antonie
author_browse Brink, Michael Philippus
Van Rensburg, Antonie
author_facet Van Rensburg, Antonie
Brink, Michael Philippus
author_sort Brink, Michael Philippus
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (MEng)--Stellenbosch University, 2017.
format Thesis
id oai:scholar.sun.ac.za:10019.1/101034
institution Stellenbosch University (South Africa)
language en_ZA
last_indexed 2026-06-10T12:41:40.401Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2017
publishDateRange 2017
publishDateSort 2017
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/101034 An approach to improving marketing campaign effectiveness and customer experience using geospatial analytics Brink, Michael Philippus Van Rensburg, Antonie Stellenbosch University. Faculty of Engineering. Dept. Industrial Engineering. Advertising -- House furnishings UCTD Geospatial data Consumer satisfaction Marketing -- Management -- Data processing Thesis (MEng)--Stellenbosch University, 2017. 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. 2017-02-14T14:43:25Z 2017-03-29T12:00:24Z 2017-02-14T14:43:25Z 2017-03-29T12:00:24Z 2017-03 Thesis http://hdl.handle.net/10019.1/101034 en_ZA Stellenbosch University 108 pages : illustrations application/pdf Stellenbosch : Stellenbosch University
spellingShingle Advertising -- House furnishings
UCTD
Geospatial data
Consumer satisfaction
Marketing -- Management -- Data processing
Brink, Michael Philippus
An approach to improving marketing campaign effectiveness and customer experience using geospatial analytics
title An approach to improving marketing campaign effectiveness and customer experience using geospatial analytics
title_full An approach to improving marketing campaign effectiveness and customer experience using geospatial analytics
title_fullStr An approach to improving marketing campaign effectiveness and customer experience using geospatial analytics
title_full_unstemmed An approach to improving marketing campaign effectiveness and customer experience using geospatial analytics
title_short An approach to improving marketing campaign effectiveness and customer experience using geospatial analytics
title_sort approach to improving marketing campaign effectiveness and customer experience using geospatial analytics
topic Advertising -- House furnishings
UCTD
Geospatial data
Consumer satisfaction
Marketing -- Management -- Data processing
url http://hdl.handle.net/10019.1/101034
work_keys_str_mv AT brinkmichaelphilippus anapproachtoimprovingmarketingcampaigneffectivenessandcustomerexperienceusinggeospatialanalytics
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