Social media analytical CRM: a case study in a bank

عنوان Social media analytical CRM: a case study in a bank
نویسنده Duman, Ekrem
تاریخ انتشار: 2023
محل انتشار - IOS Press
موضوع Banking, CRM, NLP, Sentiment analysis, Social media
نوع دوره ای
زبان انگلیسی
دیجیتال بله
نسخه خطی خیر
کتابخانه: دانشگاه اوزیغین
شناسه دارایی کتابخانه 1064-1246
شماره ثبت b05cde10-d506-4e06-85ce-287a378905c2
محل کتابخانه Industrial Engineering
تاریخ 2023
متن نمونه The use of the social media (SM) has become more and more widespread during the last two decades, the companies started looking for insights for how they can improve their businesses using the information accumulating therein. In this regard, it is possible to distinguish between two lines of research: those based on anonymous data and those based on customer specific data. Although obtaining customer specific SM data is a challenging task, analysis of such individual data can result in very useful insights. In this study we take up this path for the customers of a bank, analyze their tweets and develop three kinds of analytical models: clustering, sentiment analysis and product propensity. For the latter one, we also develop a version where, besides the text information, the structural information available in the bank databases are also used in the models. The result of the study is a considerably more efficient set of analytical CRM models.
DOI 10.3233/JIFS-221619
Cilt 44
مشاهده در منبع دانشگاه اوزیغین دانشگاه اوزیغین - موتور جستجوی نسخه های خطی عثمانی
دانشگاه اوزیغین - موتور جستجوی نسخه های خطی عثمانی دانشگاه اوزیغین

Social media analytical CRM: a case study in a bank

نویسنده Duman, Ekrem
تاریخ انتشار 2023
محل انتشار - IOS Press
موضوع Banking, CRM, NLP, Sentiment analysis, Social media
نوع دوره ای
زبان انگلیسی
دیجیتال بله
نسخه خطی خیر
کتابخانه دانشگاه اوزیغین
شناسه دارایی کتابخانه 1064-1246
شماره ثبت b05cde10-d506-4e06-85ce-287a378905c2
محل کتابخانه Industrial Engineering
تاریخ 2023
متن نمونه The use of the social media (SM) has become more and more widespread during the last two decades, the companies started looking for insights for how they can improve their businesses using the information accumulating therein. In this regard, it is possible to distinguish between two lines of research: those based on anonymous data and those based on customer specific data. Although obtaining customer specific SM data is a challenging task, analysis of such individual data can result in very useful insights. In this study we take up this path for the customers of a bank, analyze their tweets and develop three kinds of analytical models: clustering, sentiment analysis and product propensity. For the latter one, we also develop a version where, besides the text information, the structural information available in the bank databases are also used in the models. The result of the study is a considerably more efficient set of analytical CRM models.
DOI 10.3233/JIFS-221619
Cilt 44
دانشگاه اوزیغین - موتور جستجوی نسخه های خطی عثمانی
دانشگاه اوزیغین شما در حال هدایت مجدد هستید...

لطفاً صبر کنید