Does anyone have any recommendation on Data analytics using AI\ML to analyze Support tickets?
Has anyone worked with any vendors to perform advanced analytics on structured or unstructured data?. I am looking to apply machine learning, text analytics, and other advanced data mining technique on support tickets to be able to see any trends in the data. the outcome would be for tickets to be clustered , classified and categorized to provide some deep insight into
1- Problem areas in product, tools or process
2- Highlight KB articles on specific topics
3- Areas in the product that will require more in-depth training for both clients to support agents
4- Any operational/process trends.
5- Opportunities for automation
6- Increase Ticket MTTR
thank you in advance
We have a few partners that may help with this.
You can search for more here. https://www.tsia.com/members/community/partners
Also maybe @SaraJohnson or @DavidBaca have some insight.0
@Kevin Bowers thanks. i am looking for solutions that i can provide Structured and unstructured ticket data i.e subject , description, RCA , Product and the solution will perform NLP , Clustering of the tickets and present them VIA a UI. This will allow for great insight into similar tickets, show trends and areas of concern in the product, areas that need more KB articles, or what needs to be automated.0
Hello @Ibrahim Aqqad - to further @Kevin Bowers' note, I have provided you with this link that provides you with access to some relevant webinars conducted by John Ragsdale, in conjunction with one of TSIA's Technology Partners, TheLoops. Once you've had an opportunity to consume the 3 related webinars with TheLoops, please me know if you'd like a deeper dive and I would be happy to work with John Ragsdale to introduce you to the appropriate TSIA POC within TheLoops to help you better understand if this AI/NLP solution could meet your need to improve how your Support organization is using unstructured support data to help drive product-led improvements that can help improve your customer experience.
Additionally, from a structured support perspective, @SaraJohnson and I conducted a related case management best practices webinar a few months ago that I recommend you and your team review. If you have any follow-up questions from this webinar, please work with your TSIA Member Success Manager (Jennifer) to submit related inquiry questions.
I hope this information is helpful!
cc: @Edly Villanueva1
Here we used Azure Synapse + Power BI to answer those questions, but in this case, you will have to build it from scratch. PBI now has very good AI features, like detecting sentiments on comments (text analytics) and AI-infused charts like the key influencers and decomposition tree that will help you. For unstructured data, we use ElasticSearch, but if your scope is only support tickets, the combination above should be enough for you.
All analytics are done after the tickets, but I think you should also think of an AIOps solution that will answer those questions and improve your operations in real time. I think GrokStream is a great platform and using clustering, predictions/labeling, and automation you will have great results.
My contacts there are [email protected] and [email protected]
If you need further details, don't hesitate to contact me.1