True Word Cloud based on Ticket Body
I've tried using Ticket Subject with the word cloud, but the subject has to be the exact same as another one to be counted together. That's not a true word cloud, as it should be able to pick the most common single words out of all the ticket subjects.
Are there plans to expand this to Ticket Body? I'm trying to generate a word cloud for each team so they can see the most commonly used words in their tickets. Tags and Subjects don't suffice.
Thanks!
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I agree with this feedback as well. In order to spot any trends in tickets, such as ticket body/ description, it would be helpful for the Word cloud visualization to parse out common words or phrases in tickets. I understand that there is a feature similar to this in Content Cues; however, in Explore we're looking to refine this data more by filters (ticket group, type, etc.).
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This feature would definitely be a great way to identify new trending issues raised by customers when experiencing high volume
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You have my vote! As it is, I can't a word cloud report to work in Explore.
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Adding a vote here for improving the word cloud feature.
Currently ticket subjects need to match exactly in order to be counted, which is not helpful when our many agents have varied ways of documenting the same topic (e.g. "COVID-19 question" vs "COVID-19 request").
Expanding this to the ticket body would also be very nice. We have a use case for identifying common words in the first comment of a ticket, or the second comment, third, etc.
Please consider adding this to your roadmap. Thank you!
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+1 on this - it would be great to perform this type of analysis on data.
I am also thinking that this may be beneficial in scenarios where legacy data was not categorised properly and cannot be updated due to the restrictions on editting closed ticket data. It may help to give some degree of understanding on what previous tickets were related to, even if the relevant fields / forms were not setup correctly.
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is there any progress on this question? maybe another option to do a trend analysis on ticket types without the need to categorize each ticket on entry.
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