On the road to digital transformation, customer service and employee process improvement are a clear objective for any company. Conversational RPA plays an important role in both fields and can provide a clear competitive advantage.
The importance of immediacy
Before the advent of conversational RPA, customer service was the weak point of many businesses. Who hasn’t suffered from long waiting times after a service call?
If human resources are finite and user demand is difficult to forecast, the result is a bottleneck with overburdened employees and dissatisfied customers. The importance of as immediate a response as possible helps to improve customer perception. And not only that, fast handling of incoming and sorting requests also helps employees to improve their efficiency and well-being. But how can this improvement be achieved without a huge investment to increase customer service staff?
The advance of automation technologies, coupled with increasingly competent artificial intelligence, results in a tandem that is hard to beat. Thanks to the implementation of software robots in the early stages (or sometimes even in the entirety) of contact with the user, customer service processes are substantially improved.
The new systems based on conversational RPA make it possible to establish the first gateway for customer service. In this way, for example, it is possible to build a virtual chat system hosted on the company’s website that provides the first answers to the consumer’s questions. In many cases it will even be possible to solve the entire problem without the need for a worker to be involved in the process. In cases where this is not possible, the user will be referred to the attention of a person.
These response systems can be developed in a multi-channel manner. They can also be integrated into tools such as MS Teams or Slack. It is even possible to generate automatic response emails based on the content of the email sent by the customer.
Conversational RPA is the new gateway to customer service. | Photo: Mart production.
Understand the context and nuances of the language.
For the whole conversational RPA system to work properly, it is essential to have tools that understand not only the language, but also the context in which it is being developed. And even more. People are capable of expressing the same idea in very different ways. Nuances, vocabulary and verbal constructions are of vital importance to understand what the user wants to say and respond accordingly.
To carry out all these tasks, we have two allies that are advancing by leaps and bounds. Artificial Intelligence and Machine Learning allow systems to learn from users’ behaviors, language and mode of expression. Thanks to this machine learning, systems become increasingly efficient and achieve better accuracy. In fact, if necessary, they can replace a person without the user noticing the difference.
Thus, it is clear that leveraging the benefits of conversational RPA means substantially improving the way in which we respond to our customers’ queries and needs. A way to streamline, improve and offer solutions that result in an optimization of available resources and greater customer satisfaction.