[Music] foreign [Music] this is a demonstration of the sentiment analysis capability that could be used by the customer support agents uh in order to better prioritize the cases by taking emotional context into consideration as well for the purpose of this demonstration imagine that I am a subscriber of the media streaming company and I'm trying to log into their app in order to watch their show however I noticed that I keep getting kicked out of the app giving me concerns if my account got hacked so I decide to communicate with the support of the media streaming company using the communication channel of my choice which is email so I'm writing an email to the support address of the streaming company and as you can see I'm using pretty strong language in order to communicate how frustrated I am with their experience I am asking for a refund and I'm asking for somebody to call me ASAP and also for my account to be terminated switching to the agent side of the house as an agent I'm looking at a backlog of cases at any given point of time and having visibility into the current sentiment greatly helps me in prioritizing those cases better in fact I as an agent can also group these cases by current sentiments so that maybe I can start addressing all the negative cases at first because they have the most impact on the business uh because of the churn associated with the negative sentiment customers so let me jump into this uh most recent case that came in from one of our subscribers firstly as you can see on the left hand side of the case form my job is already made easier as AI is predicting and automatically filling up the case form Fields based on the subject and the body of the case that came in from the email all I need to do is quickly glance through them to make sure that they're right and then focus on the resolution this will save up to at least 30 seconds per each case and will enable me to greatly focus on the resolution of the case so focusing on the resolution I see that this email has come in with a pretty strong language talking about account being logged out after after doing my due diligence I decide to respond back to the customer in the same email and let the customer know that their credentials are safe and in fact it's because of an internal system issue that their account was locked out so I'm trying to give the confidence to the end user uh using very positive language and and in order to reduce the churn if possible and I send the email now switching to the End customer side once again I'm pleasantly surprised to see a response from the support agent of the streaming company in less than five minutes with the resolution once I try out the resolution I'm able to log into this app successfully I decide to write back to the support agent thanking for the help in a more neutral tone foreign back to the agent side of the house again I see a response come back from the End customer in a in a much better toll and as a result you can see that the current sentiment is now neutral with sentiment over time improving as well also if I switch to the list view you can clearly see how the sentiment over time has is is been improving while the current sentiment is neutral based on the change in the tone from the customer this is also a great way for managers to step in and avoid escalations for example let's say whenever sentiment over time is declining the managers could pick those cases to step in and provide coaching for agents so that's the sentiment analysis and the case categorization demo thank you