Voice is the most natural way of communication from time immemorial. Callers no longer have to traverse IVRs by tediously listening to menus and punching appropriate digits on their keypads to reach a customer support. Contact Center solutions now have an added feature of Intelligent voicebots that comprehend and react to natural language & transform customers' interactions with your brand. This blog will look at voicebots and how contact centers in various sectors utilize them to improve user experience.
1. What is a voicebot?
2. What is Conversational IVR?
3. What Is the Difference Between Traditional and Conversational IVR?
4. How do voicebots work?
5. How will Voicebots transform Traditional IVR?
6. Why do businesses need Conversational IVRs right now?
A voicebot is an AI-powered software, that comprehends human speech and synthesizes voice to speak with users using natural language understanding (NLU). Instead of battling with many typical IVR choices, voicebots allow clients to have a more open-ended discussion.
Voicebots have been around for some time, but recent advances in AI, machine learning, NLP, and NLU have made them more intelligent. The widespread use of smart voice assistants like Alexa, Google Home, and Siri has prompted companies worldwide to invest in voicebots that provide a brilliant, natural, and intuitive human-machine connection.
Conversational IVR systems employ callers' voice instructions to connect with a self-service model when they approach a contact center for help. These systems are intelligent and intuitive enough to comprehend a conversation's context and substance. It is a massive step to eliminating time-consuming hierarchical menus from communication interactions.
Conversational Interactive Voice Response systems, powered by AI, Natural Language Understanding (NLU), and machine learning, enable callers to drive the dialogue in a conversational manner. It allows the conversation to flow more organically without human involvement. This Interactive Voice Response system can collect the precise words and sentences spoken by callers since it leverages machine learning, providing companies with a wealth of insights about what their callers desire in their self-service path toward problem redressal.
Conversational IVR, as a system, may also improve its performance depending on its inputs. When conversational interactive voice response cannot understand what a caller is saying, an agent may effortlessly take over. The AI system then saves the inputs for causal analysis and optimization so that if a similar inquiry or query is given in the future, it can handle it without human involvement.
As data and expertise accumulate, the Interactive Voice response grows more capable of handling calls independently. Furthermore, the usage of NLU allows IVR systems to become more conversational. It enables the conversation to change from 'this is what I can do for you to 'what can I do for you?'
When combined, these aspects allow callers to control their connection with a support system, enhancing their experience. It leads to smoother call routing operations, more dependence on self-service, and lower internal transfer costs for organizations.
Traditional IVR systems enable users to use DTMF-based inputs in the keypad while conversational IVR allows individuals to use their voice to reach out in a more natural way. Customers can articulate their problems or worries in their own words, and conversational interactive voice response can detect the purpose/intent of the questions and give a more human-like engagement.
Conversations can be used to train a conversational IVR. For example, if a consumer says anything that a conversational interactive voice response doesn't understand, it can direct the customer to a live person. However, such calls are flagged for training the AI model. As a result, the system will need less interaction the next time it meets a similar inquiry and will ultimately be capable of independently doing various tasks.
Like a voicebot, a chatbot is an automated conversational interface driven by artificial intelligence that you can employ to automate and expedite early-stage customer support interactions.
While voicebots can understand spoken voices and answer back in voice, chatbots are text-based messaging systems that read written language and respond in text, allowing a bot-to-user communication that resembles person-to-person messaging exchanges. Because a voicebot communicates by converting voice to text and text to voice, it can utilize the same AI model as your AI chatbot.
Voicebots and chatbots have benefits, and you can use them to give consumers communication channels that suit their preferences.
The following stages comprise the operational flow of an AI-powered voicebot:
ASR (automated speech recognition) allows the bot to interpret human voice inputs, filter out background noise, and convert the voice into text format. ASR can capture voice in the record and play mode or also in streaming mode. ASR software is classified into two types: directed dialogue and natural language dialogues.
A directed conversation is a simplified form of ASR that can answer simple yes/no questions. On the other hand, natural language conversations are more complicated and refined versions of ASR replicating genuine human conversations.
NLU is an ASR component that allows the bot to examine incoming queries to determine what a particular set of words imply and then categorize them into appropriate intents. NLU relies on one of two mechanisms: human tuning or active learning.
Human tuning is a manual technique that involves adding frequently used terms to conversation records. It improves voice comprehension so that the bot can comprehend new inquiries without difficulty.
On the other hand, active learning is a more sophisticated kind of NLU that self-learns and grows its vocabulary from prior discussions. This software can comprehend user intent and behavior to provide a more tailored response.
This module, often known as a knowledge base, focuses on matching the user's query with millions of bits of underlying information. When the voicebot discovers information that is most relevant to the inquiry, it uses text to voice to compose an appropriate answer.
Knowledge bases allow the voice assistant to create personalized replies. For example, asking your Google Assistant to call your buddy John will search your contact list for the name John and call him. The assistant's knowledge base grows with time and becomes more intelligent.
voicebots can respond to client queries using pre-recorded audio files or Text-to-Speech (TTS) technology. It is a computer-generated replica of the human voice, also known as voice synthesis, that employs deep learning algorithms to provide responses that sound natural.
Customers can find the touch-tone technique, in which callers must press specific numbers to be connected to the appropriate department or representative, unpleasant and time-consuming.
Conversational IVR, on the other hand, provides a more fluid style of communication, effortlessly linking callers to the appropriate person or department and offering the information they want.
You can ensure the same response on every channel since you can use the same database and dialogues as your other Conversational AI solutions. The answer will be the same whether a consumer asks your chatbot, searches it up on your dynamic FAQ website, or asks the voicebot. If you modify a response, such as opening hours, you need to do it once, and all of your bots will be updated.
Customers hate having to wait. However, your contact center support agents are not always accessible. Whether large call volumes overburden your agents or clients call after hours, your agents' availability and customer demands cannot always coincide.
Fortunately, conversational IVR can provide clients with quick, round-the-clock self-service help. This is not possible with traditional IVR. The IVR containment rate can be as high as 60% to 80%. Clients can obtain responses to their customer concerns and problems 24 hours a day, seven days a week, without having to wait on hold for hours.
Consumers who can make their own decisions are satisfied customers. You can utilize conversational interactive voice response to assist clients in gathering information and making adjustments, such as replacing an outdated password or terminating a service subscription. Customers will feel more powerful and self-sufficient and avoid time-consuming talks with customer support staff.
Furthermore, voicebots can decrease the strain on customer support staff, reduce stress, and boost employee happiness. By answering many consumer inquiries, conversational IVR relieves the stress and pressure on your customer care agents. It allows your contact center agents to concentrate on more complex and less time-consuming parts of client support.
It is costly to hire and train many contact center representatives and to guarantee that there are enough individuals on duty to respond to consumer inquiries around the clock. Furthermore, voicebots aid in call reduction by resolving consumer inquiries and problems, minimizing the amount of protracted and expensive interactions between customers and agents.
Conversational interactive voice response is a cloud-based software and is easy to scale with your business. Also, the ability to run multilingual Conversational IVR lets you address different customer segments and geography.
Conversational IVR provides a more flexible experience for clients since they are not restricted to a single scripted sequence. These sophisticated IVRs are easier to use and better at directing clients toward self-service options rather than requiring the participation of a live representative. Not only does this increase employee productivity and save companies money by lowering customer turnover, improving brand image, lowering personnel expenses, and increasing client retention, but it also makes consumers happy.
Conversational IVRs can cut live agent call traffic in half while improving call routing accuracy and customer satisfaction - Navigating extensive menus and waiting in long lines is not an experience that any client desires. On the contrary, millennial clients demand faster service and easy encounters.
Customers seek more flexible, quicker, and faster methods to handle problems, and traditional IVR systems are increasingly critical to improving and modernizing customer service. Many firms will install Conversational IVR systems in the following years to reduce costs, boost agent efficiency, and enhance customer experience.
The transition from classic menu-driven interactive voice response to conversational interactive voice response improves the client experience. It provides a continuous chance to enhance call routing and customer happiness while increasing contact center efficiency. In summary, conversational IVR can meet callers' basic needs, respect their time, understand them, and engage them with the aid of AI.
To understand the implementation of Conversational IVR and how C-Zentrix can assist you in improving customer experience in contact centers, connect with us.
Author Bio: Akshay