THE INVESTIGATION OF ONLINE CUSTOMER COMPLAINTS IN THE BANKING SECTOR BY TEXT MINING
- Customer Complaints, Text Mining, Clustering Analysis
- Müşteri Şikayetleri,
- Metin Madenciliği,
- Kümeleme Analizi
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The goal of this study is to obtain new gains that would provide benefits to businesses from customer complaints that customers offer voluntarily and free of charge. In line with this purpose, in this study, 25,390 online customer complaints concerning banks operating in the retail banking sector in Turkey were analysed by data mining method. By using the clustering method in data mining analysis, complaints were grouped, familiar words, similar or the words used together of the complaints were identified.
As a result of the analysis done, the most frequently mentioned banks among customer complaints and the subjects that customers complained about most were determined. It was revealed that the subjects that the bank customers complain about most within the relevant periods were “branch, credit card fee, cancellation, customer service, subscription fee”. Also, the result emerged that bank customers used the words “unfair” and “victimisation” when expressing their dissatisfaction.
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