Text Sentiment Analysis (finding patterns and business value from unstructured text data)
Large enterprises such as Banks often deal with large volumes of unstructured text data. Customer Complaints for example comes in the form of unstructured free text.
Due to large volumes of complaints, Banks need a way to quickly and efficiently analyse customer complaints. In other words, Banks need a way to "separate the signal from the noise".
One way to achieve this is to apply text sentiment analysis on the complaints text data so that you can isolate the very negative sentiment complaints cases and prioritise resources to resolve these complaints as soon as possible.
This is an example of summarising and visualising customer text data into actionable business insights that help businesses make optimal business decisions in an efficient manner.
For more details, please view the URLS of
1. Youtube clip explaining the process in more detail
2. Tableau Public Dashboards to see what is possible with Data Visualisation techniques
https://public.tableau.com/profile/kthang#!/vizhome/CustomerComplaints_USBanks_2017Yr/Story-3Visuals
