[ Data Mining au service du marketing digital: Cas des produits bancaires ]
Volume 29, Issue 4, July 2020, Pages 1327–1336
Rajaa AMZILE1 and Karim Amzile2
1 Département sciences de gestion, Université Mohammed V Rabat, Faculté des sciences juridiques, économiques et sociales, Agdal, Rabat, Morocco
2 Département sciences de gestion, Université Mohammed V Rabat, Faculté des sciences juridiques, économiques et sociales, Agdal, Rabat, Morocco
Original language: French
Copyright © 2020 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Through this literature review, we have explored the various scientific articles that have been exploited by Data Mining techniques in the banking sector and specifically Digital Marketing, namely the prediction of customers interested in a banking product. We have succeeded through a variety of articles in tracking the behavior of some Data Mining algorithms and their uses, using bank data. These techniques have also allowed us to determine the best parameters for each Data Mining method. In this review, we have used the results of different evaluation tools for all the methods used, which has enabled us to easily choose the appropriate prediction model. Several Software have been used as a programming tool to clarify each of the techniques of Data Mining, Therefore, we cannot say that an algorithm is the best since the results differ from one category to another of the data used.
Author Keywords: Big data, data mining, digital, marketing, Genetic Algrotihm.
Volume 29, Issue 4, July 2020, Pages 1327–1336
Rajaa AMZILE1 and Karim Amzile2
1 Département sciences de gestion, Université Mohammed V Rabat, Faculté des sciences juridiques, économiques et sociales, Agdal, Rabat, Morocco
2 Département sciences de gestion, Université Mohammed V Rabat, Faculté des sciences juridiques, économiques et sociales, Agdal, Rabat, Morocco
Original language: French
Copyright © 2020 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Through this literature review, we have explored the various scientific articles that have been exploited by Data Mining techniques in the banking sector and specifically Digital Marketing, namely the prediction of customers interested in a banking product. We have succeeded through a variety of articles in tracking the behavior of some Data Mining algorithms and their uses, using bank data. These techniques have also allowed us to determine the best parameters for each Data Mining method. In this review, we have used the results of different evaluation tools for all the methods used, which has enabled us to easily choose the appropriate prediction model. Several Software have been used as a programming tool to clarify each of the techniques of Data Mining, Therefore, we cannot say that an algorithm is the best since the results differ from one category to another of the data used.
Author Keywords: Big data, data mining, digital, marketing, Genetic Algrotihm.
Abstract: (french)
À travers cette revue de littérature, nous avons exploré les différents articles scientifiques qu’ont exploité les techniques du Data Mining dans le secteur bancaire et bien précisément le Marketing digital à savoir la prédiction des clients intéressés par un produit bancaire. Nous avons réussi à travers une panoplie d’articles de suivre le comportement de quelques algorithmes du Data Mining ainsi que leurs utilités, en utilisant des données bancaires. Ces techniques nous ont également permis de déterminer les meilleurs paramètres de chaque méthode du Data Mining. Dans cette revue, nous avons exploités les résultats de différents outils d’évaluation de toutes les méthodes utilisées, ce qui nous a permet de choisir avec aisance le modèle de prédiction adéquat. Plusieurs Logiciels ont été utilisé comme outil de programmation pour éclaircir chacune des techniques du Data Mining, Par conséquent, nous ne pouvons pas dire qu'un algorithme est le meilleur vu que les résultats se différent d’une catégorie à une autre de données utilisées.
Author Keywords: Big data, data mining, digital, marketing, algorithme génétique.
How to Cite this Article
Rajaa AMZILE and Karim Amzile, “Data Mining at the service of digital marketing: Case of banking products,” International Journal of Innovation and Applied Studies, vol. 29, no. 4, pp. 1327–1336, July 2020.
