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Data mining for positive customer reaction to advertising in social media
Author(s)
Boonjing, Veera
Pimchangthong, Daranee
Date Issued
January 1, 2018
Type
Conference Paper
Abstract
Social media has become a source of large amounts of data that is extremely useful when data are analyzed properly. Data mining is one of the known techniques to analyze data to find hidden information from a large amount of available data without having prior hypotheses. The objectives of this research were to (1) find the most important factors influencing positive reactions from customers after seeing online advertising in social media, (2) find the most important factors influencing purchasing merchandise that are advertised online, (3) identify customer clusters characteristics that have positive reaction after seeing online advertising in social media, and (4) identify customer clusters characteristics that purchase merchandise after seeing online advertising in social media. The sample size of 370 is collected by questionnaires using convenience sampling method. Data mining with cluster analysis is used to analyze data. The findings indicate the characteristics of “product conscious” and “price conscious” clusters for customer’s reaction and purchasing after seeing online advertising in social media.
Citation
Lecture Notes in Business Information Processing, 311, 83-95, 2018