SciELO - Scientific Electronic Library Online

 
vol.31 número3Improved energy budgeting process using measurement and verification principlesExploring factors that influence the mainstreaming of gendered energy interventions in poor urban environments: a structured literature review índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Articulo

Indicadores

Links relacionados

  • En proceso de indezaciónCitado por Google
  • En proceso de indezaciónSimilares en Google

Compartir


South African Journal of Industrial Engineering

versión On-line ISSN 2224-7890
versión impresa ISSN 1012-277X

Resumen

DROOMER, M.  y  BEKKER, J.. Using machine learning to predict the next purchase date for an individual retail customer. S. Afr. J. Ind. Eng. [online]. 2020, vol.31, n.3, pp.69-82. ISSN 2224-7890.  http://dx.doi.org/10.7166/31-3-2419.

Targeted marketing has become more popular over the last few years, and knowing when a customer will require a product can be of enormous value to a company. However, predicting this is a difficult task. This paper reports on a study that investigates predicting when a customer will buy fast-moving retail products, by using machine learning techniques. This is done by analysing the purchase history of a customer at participating retailers. These predictions will be used to personalise discount offers to customers when they are about to purchase items. Such offers will be delivered on the mobile devices of participating customers and, ultimately, physical, general paper-based marketing will be reduced.

        · resumen en Africano     · texto en Inglés     · Inglés ( pdf )

 

Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons