Version 1
: Received: 13 October 2023 / Approved: 13 October 2023 / Online: 17 October 2023 (03:32:06 CEST)
How to cite:
Elsaghair, W.S.; Atilla, D.C. Analys Using SPSS 23 Software for Monitoring Internet Technology Over Mobile Communications. Preprints2023, 2023100885. https://doi.org/10.20944/preprints202310.0885.v1
Elsaghair, W.S.; Atilla, D.C. Analys Using SPSS 23 Software for Monitoring Internet Technology Over Mobile Communications. Preprints 2023, 2023100885. https://doi.org/10.20944/preprints202310.0885.v1
Elsaghair, W.S.; Atilla, D.C. Analys Using SPSS 23 Software for Monitoring Internet Technology Over Mobile Communications. Preprints2023, 2023100885. https://doi.org/10.20944/preprints202310.0885.v1
APA Style
Elsaghair, W.S., & Atilla, D.C. (2023). Analys Using SPSS 23 Software for Monitoring Internet Technology Over Mobile Communications. Preprints. https://doi.org/10.20944/preprints202310.0885.v1
Chicago/Turabian Style
Elsaghair, W.S. and Dogu Cagdas Atilla. 2023 "Analys Using SPSS 23 Software for Monitoring Internet Technology Over Mobile Communications" Preprints. https://doi.org/10.20944/preprints202310.0885.v1
Abstract
With the rise of internet technology and the growth of mobile communications, the global economy has undergone a significant transformation, shifting towards digital and soft markets. As a result, great efforts have been made to establish virtual marketplaces that provide customers with an exceptional shopping experience. One crucial aspect of this new paradigm is marketing, which has led to the emergence of a new stage known as E-marketing. In E-marketing, understanding customer behavior is of utmost importance. Marketing teams and companies are eager to gain insights into how different customer segments react to their products. Marketing strategies are now developed based on customer information such as financial status, location, age, gender, and more. As a result, the abundance of customer data generated by these new commerce technologies has surpassed the capabilities of traditional data analysis methods. To extract valuable knowledge from this vast amount of data, data mining technologies have come into play. Techniques such as clustering, classification, and prediction are utilized to mine marketing data and uncover hidden patterns and trends. The impact of data mining on E-marketing has been the subject of analysis in this study. A questionnaire-based review was conducted to collect the necessary data, which was then analyzed using SPSS 23 software. The study's results demonstrate that data mining can significantly enhance the performance of E-marketing by providing intelligent and efficient predictions of customer behaviour. Moreover, this technology offers similar advantages for end-customers as well. By leveraging the power of data mining, companies can gain valuable insights, tailor their marketing efforts, and ultimately provide better products and services to their customers in the digital marketplace.
Keywords
internet technology; mobile communications; digital market; soft market; virtual market; shopping experience; e-marketing; customer behaviour
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
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.
