Effizienter Kundensupport: Rationalisierung von E-Mails durch Sentimentanalyse und Themenklassifizierung
Managing and pinpointing the most frequent incidents and requests by email can be challenging. Our objective was to thoroughly examine the inbox, scrutinize the contents of the emails to determine the sentiment, and classify them into topics.
Neue mobile Anwendungen, die Sie im Auge behalten sollten
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Welche neuen mobilen Anwendungen für soziale Medien werden 2022 verfügbar sein?
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Neue Social-Media-Anwendungen als Marketingtrichter nutzen
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Probieren Sie Twitter Spaces oder Clubhouse auf dem iPhone aus
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Mit welcher Anwendung experimentieren Sie gerade?
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Effizienter Kundensupport: Rationalisierung von E-Mails durch Sentimentanalyse und Themenklassifizierung
Businesses receive an overwhelming number of customer emails on a daily basis. Managing and pinpointing the most frequent incidents and requests can be challenging. Our objective was to thoroughly examine the inbox, scrutinize the contents of the emails to determine the sentiment, and classify them into topics. These topics are subsequently utilized to generate superior content on the support website, ultimately leading to a substantial reduction in customer contacts.
Welche Daten wir verwendet haben
Export of the inbox folder from Outlook with 1090 emails.
Zielsetzungen
— Finding patterns within emails
— Finding topics within the inbox
— Identifying «hot topics» with sentiment analysis
Liefergegenstände
— 2D Map to browse and search for emails and keywords
— Topic modelling
— Management report in order to highlight fields of action
