The importance of classifying tickets thanks to Artificial Intelligence: the vtenext case
Vtenext is an “All in one” CRM software with more than 80 partners worldwide. The natively integrated Business Process Management engine (BPM) allows the customer to manage all marketing activities, sales, after-sales and customer service. The strength of vtenext is to be able to manage within a single platform and in a simple way all the business processes involving the customer, allowing you to maximize the Customer Experience and consumer satisfaction.
The integration of Klondike and its Machine Learning algorithms has allowed vtenext to track those “unconscious” processes within the organization, classify existing tickets and make predictions about the possibility of occurrence of certain events.
We interviewed Denis, Customer Service Manager at vtenext.
How was the ticket support management in vtenext before implementing Klondike?
Before integrating Klondike’s Machine Learning algorithms into our system, vtenext support ticket management was fairly repetitive and mechanical. The process basically followed this process: the partner, the retailer or the customer opened a ticket on our support portal to the occurrence of a given problem; someone read all the requests that arrived and these were sorted and catalogued manually, one by one.
That someone was me (Denis): I read all the incoming tickets, whether it was a person asking for a copy of an invoice, someone asking for directions on how to configure the mailbox, or simply requests for general information or reports of malfunctions. After having read all the requests received, I had to sort them out to the various departments, to whom of competence.
Then you introduced Klondike and started automating tickets: what has changed?
After the insertion of the Klondike ticket classifier, tasks are completed in a semi-automatic way. Thanks to the classifier, a category-field is created based on the text of the request. It’s created based on what the ticket is related to (i.e. configuration, development, etc). After a short period in which the machine acquires data, with which it improves its forecasts, all this happens in an automatic way.
The main advantage is that I no longer worry about checking which category tickets are assigned to. The machine is precise and accurate, and the cases in which the ticket is poorly categorized and must be sorted again are very rare and isolated.
HOW KLONDIKE WORKS
Thanks to Klondike’s algorithms, superpowers are given to CRM. Machine Learning features are integrated, optimized and interact directly with the present database allowing you:
– to automate and optimize the processes carried out within the CRM of Customer Service, sales, administration or marketing;
– to save time by having the machine perform mechanical and repetitive tasks, while improving the customer experience.
What are the advantages and benefits of ticket automation?
One of the biggest advantages concerns the ticket classification and assignment process. Before, this was extremely repetitive (and a bit boring) and was done by one person. And if that person was busy, the tickets had to wait to be sorted.
Now everything is automated and is carried by a machine, and the benefits are so many. Above all, the processes are much faster and the customer response time has significantly decreased. Having eliminated those dead times in which a ticket was read and subsequently sorted, the report remains on the waiting list for one hour at most before being cataloged. And customers are very happy with this speed in responding to their problems.
Benefits not only for customers, but also for companies…
Indeed! The technical support team opens an average of 30 tickets per day, about 1000 tickets per month. When this was done manually, it took me between an hour and two, of the 8 working hours to sort and assign tickets. Now it is the machine that carries out these mechanical processes for me: that time is saved, which is optimized on other tasks, increasing the efficiency and productivity of the company. An hour and a half saved every day that can be used to perform other tasks, respond to customers and coordinate the team: it’s really a big hand!
Would you like to find out how to automate processes like vtenext?
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