When it comes to customer communication automation, chatbots are among the first things that pop up in mind – probably because they are at the peak of popularity these days. However, there’s also a more sophisticated solution that can bring even more benefits and a higher payoff if applied properly. This refers to virtual agents (VAs) which use such technologies as natural language processing and machine learning to interact with customers.
There are certain similarities between virtual agents and chatbots (they are both used to automate the communication process), but the main difference lies in their capabilities. This article discusses the three ways how VAs can be more beneficial to your business than chatbots.
VAs are more human-like
Chatbots are usually designed to handle basic tasks, such as providing information at request, placing orders, or sending status updates. They use scripted decision trees to respond to customer requests with pre-approved answers. Customers are usually aware they are talking to a chatbot and might feel undertreated, especially when it comes to more complex requests which require more consideration than just following the script.
Virtual agents can provide customers with a more profound experience. They are capable of recognizing customer intent and giving personalized, accurate answers while engaging in a conversation in a human-like manner. Moreover, VAs pay attention to such things as tone of voice, modality and customer’s emotions and respond in an appropriate way.
They can even imitate different intonations and make pauses. For example, voice agents by Neuro.net can hardly be distinguished from a real person – only 1% of customers were able to do that.
VAs are more autonomous
Automating doesn’t make much sense unless it fully frees humans from routine tasks. If managers have to constantly check and oversee work done by a chatbot, it might bring more problems than benefits. Of course, there are also well-designed chatbots that are extremely good at automating specific procedures. Still, they usually have a more narrow focus than virtual agents. For example, chatbots can effectively provide answers to a predefined range of questions; however, they cannot hold a conversation if it slightly diverts from the script they have been programmed to follow.
Virtual agents are far more autonomous. Since they are pre-trained on real-life data, they are able to handle multiple situations and engage in a natural flow of conversation. Even if they fail to get to the point at the initial request, they can ask additional questions to clarify the issue and get more details. VAs can connect to different databases, CRMs, knowledge bases, etc., to retrieve the information they need to solve the customer’s problem.
VAs are constantly learning
Chatbots rely on a pre-defined knowledge base and cannot act out of their program unless you manually add some extra functionality. A chatbot recognizes certain keywords from the user’s input, and if they are on the list, it retrieves the corresponding response and puts it out to the customer.
Unlike chatbots, virtual agents are constantly improving their performance since they continue to learn from each interaction even after the initial training is complete.
VAs use custom NLP and machine learning algorithms that enable them to sound like a human. However, it’s important to bear in mind that the quality of a VA’s work largely depends on the quality of the dataset it’s been trained on.
Final thoughts
Although chatbots look like a quick and easy-to-deploy automation solution, their performance is limited by a number of factors. Virtual agents, on the other hand, require a bit more effort at the implementation stage. Still, in the long run, they can fully overtake human routine operations while enhancing the speed and quality of service since they never get tired and are always in a good mood. In fact, adopting a conversational AI solution like Neuro.net can help you increase productivity dramatically, resulting in a higher return on investment rate.
