Artificial Intelligence | AI





Until recently “artificial intelligence” (AI) was still considered “science fiction.” With the integration of “artificial intelligence” (AI) in the everyday work of small and medium-sized enterprises, however, it is no longer considered unusual.

For example, intelligent machine interaction in telephony is already being used on many hot lines in interactive voice response (IVR) to evaluate customer requests so that these calls can be “pre-sorted” for subsequent human editing.
The advanced, completely machine-based self-service structure is already used in customer communications.

The largest role still played by AI in this area is the ability to ensure quick customer service.

With the integration of AI, quality assurance may also be supported.

The use of AI in customer communications enables the immediate handling of all ad-hoc queries and the efficient distribution to live agents while simultaneously maintaining effective quality standards.

  • CALL
  • CHAT
  • WhatsApp
  • APP
  • WEB

The purpose

Resumed in a few words, the main purpose for the use of AI in the Service Center branch is to be able to provide “an excellent customer service experience”.

Non-stop service provision
Inbound call automation
Fully automated self-service
Optimizing waiting times

When looked at in detail though, the use of AI with all its options can mean the taking over of the entire 1st level.

In consequence the live agent – in charge of 2nd level and beyond – becomes more important, as he’ll be enable to provide a far more efficient assistance to the customer, considerably contributing to increasing the allover customer satisfaction and therefore service quality.

You can’t really see how this should be possible?

Then keep on reading!


The approach

Here, efficiently using AI starts with the quality management. An interface for AI is added to the already existing processes and procedure, so that in a first step the automated auditing can be performed on customer communication (calls, chats, etc.).

In the meantime, a bot-based automation of the processes takes place in the background. These bots will be performing a pre-qualification – just like in a simple IVR – with the goal of optimizing the allover process management and the routing to the agents.

As part of your QM, the AI will follow-up on all inbound activities and monitor workflows, routings and the distribution of the customer requests. The system will control if procedures are correctly followed and analyze the content of the dialogues, but it will also perform call analysis for tone of voice.

The results are delivered in a transcript and will give you a precious set of information for efficient coaching of your AI, essential for the further learning process.





The human interface

Imagine your AI as a new member of the team. A person that does not have any specific professional experience in this area, but is a very fast learner, capable of real multi-tasking and definitely willing to continuously keep learning and apply the new, assimilated content to its work practice.

In the beginning, this new co-worker will have to be trained. Someone needs to provide him with the knowledge and input necessary for him to successfully manage the tasks he’s been assigned with, and he’ll have to assimilate the implemented workflows as well as the do’s and don’ts.

The human interface – the coach of your AI – will be responsible for this and will be feeding the system. Subsequently it’ll be in charge of continuously correcting and adjusting until the stage of not more than a little fine-tuning is reached. If necessary at all.


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