A natural language IVR (Interactive Voice Response) solution is an automated system that allows callers to freely speak to interact with the system, using speech recognition and AI to understand and respond to requests. To take action.
The technology relies on automated speech recognition (ASR) and natural language processing (NLP) to understand what callers need – from there the natural language IVR can provide relevant responses and route calls based on the caller’s intent. . You may have heard it described as a conversational IVR – it’s the same thing.
Unlike traditional IVRs, which rely on rigid menu options and keypad inputs, natural language IVRs enable a more intuitive and flexible user experience. At first people were hesitant to adopt it, but nowadays it has become the new norm in the customer service industry. Call center software providers Features are offered.
In theory, it’s a win-win. On the one hand, customers describe their needs in terms that come naturally to them rather than going through a menu, and on the other, agents don’t need to talk to people who are actually human. No need. help
Let’s take a closer look, as the initial setup and ongoing training is bound to be more expensive than a regular IVR.
Natural language IVR vs a regular IVR
Here’s a simple breakdown of traditional IVR technology, and where a natural language IVR goes further:
Traditional IVR
- Relies on default prompts and menu options.
- Users need to press buttons or speak specific phrases to navigate.
- Users need to follow a fixed set of options.
- Uses scripted responses and basic speech recognition.
Natural Language IVR
- Allows users to speak in natural language.
- Recognizes, interprets and responds to a variety of communication inputs.
- Allows users to engage in more open conversations.
- Adapts to different user responses based on context.
- Prompts users for clarification questions instead of restarting.
Traditional IVR systems are incredibly useful – but no matter how complicated you make them, they’re basically pre-recorded navigation menus. Customers call, hear a series of menu options, and then press the number of their choice.
Natural language IVR allows users to communicate using their natural way of speaking rather than saying a bunch of predefined phrases or punching in a series of numbers. This helps improve user satisfaction – since no one likes to fight with robo-menus – and it gives phone system administrators a lot more freedom. Set up an IVR call flow..
How Natural Language IVR Works (In Detail)
Natural language IVR works by combining complex speech recognition and pattern spotting. When a user says something to the IVR, the IVR recognizes certain words or phrases they said and knows (or guesses) how to respond based on decision parameters that you can set ahead of time. are This process relies on several key technologies, including ASR, NLP, Natural Language Understanding (NLU), and Natural Language Generation (NLG).
First, the system uses ASR to detect the speech and convert it to text.
Next, the NLU component analyzes the transcribed text, identifying the intent behind the words — whether the caller wants to make an appointment, ask a question, or request information. This step is very important, as it involves extracting meaning from the speech and understanding the context of the request.
Finally, NLG is used to generate a human-like response, generating a response that seems natural and relevant to the conversation, based on patterns the system has learned through training data.
Learn more about the method. AI in call centers Natural language is revolutionizing conversational technology like IVR. It is transforming the customer service experience by providing more efficient, intuitive, and personalized interactions.
Example of natural language IVR
Let’s use a simple real-world example of a caller being greeted by an IVR who says, “I (sic) want to make an appointment.”
Natural language IVR uses ASR and NLP to interpret the request. The system recognizes the intent behind the phrase — want to make an appointment — and asks the caller if they are correct. “So you would like to meet, do I have that right?”
After the request is confirmed, the IVR routes the call to the appropriate next step, such as scheduling with an available representative, or offering options for time slots (if your IVR is integrated with your Appointment scheduling software).
This is an improvement for callers, who would normally have to listen to a pre-recorded greeting with basic information and a menu of options.
But what if a caller says something unusual, like, “I left my wallet behind at my last appointment.”
Yes, it is possible that the system may mistakenly redirect the caller to a new appointment scheduler. But typically an IVR is configured to verify that it has understood the caller’s request before routing the call. If the IVR cannot interpret the request, it may trigger agent intervention or direct the caller to a basic touch-tone menu.
As you can see from this example, a natural language IVR is overkill for a small business with relatively few options for callers to navigate. Simple scheduling can be handled by traditional IVR technology.
But consider a contact center for a hospital, where there are hundreds of different options and callers may not know what they need. In this case, natural language IVR can save callers a lot of frustration and route many common calls that would normally take a human to resolve.
Advantages and Disadvantages of Natural Language IVR
Although there are some clear advantages, it is important to weigh both the advantages and potential drawbacks before implementing this technology. Below are some important pros and cons to consider.
Advantages of Natural Language IVR:
- Improved user experience: Natural language IVRs allow users to speak freely, making interactions feel more intuitive and less cumbersome than traditional menu-based systems.
- Performance Enhancement: By understanding diverse speech patterns and intent, natural language IVRs can make calls faster and faster. Reduce excessive call queuing times..
- Better error handling: These systems can handle ambiguous answers by prompting users to clarify, which reduces frustration and reduces call abandonment.
- Continuous improvement: AI and machine learning enable systems to learn from each interaction, gradually improving their ability to understand diverse language input and provide more accurate responses over time.
Disadvantages of Natural Language IVR:
- High Deployment Cost: Advanced technology, such as AI and NLP, makes initial setup more expensive than traditional IVRs.
- Training and Maintenance: Although the system improves over time, it still requires regular updates and retraining to adapt to new speech patterns, slang and regional accents, which can be resource-intensive.
- Chances of Misunderstanding: Despite advances in technology, natural language IVRs can still misinterpret complex or ambiguous inputs, resulting in incorrect responses or the need to escalate to human agents.
- Lack of familiarity: Some users may be more accustomed to traditional menu-driven IVRs and find natural language IVRs confusing or less predictable.
Natural language IVRs come with a higher sticker price and ongoing costs, but they offer significant benefits in terms of user experience and performance. By allowing callers to speak naturally and receive quick, accurate responses, these systems can reduce wait times, improve error handling, and continuously change user behavior. can adopt
Scenarios where a natural language IVR is justified
In environments where quick, intuitive interactions are essential, and call volume justifies the investment, natural language IVRs can be incredibly useful, increasing both customer satisfaction and operational efficiency.
Here are five real-world examples of organizations that can benefit from using natural language IVR:
- Scheduling appointments for health care providers: A healthcare facility can use natural language IVR to allow patients to book, reschedule, or cancel appointments. The system understands phrases like “I need to reschedule my appointment for next Tuesday” and adjusts the calendar accordingly.
- Telecom Customer Support for Billing Enquiries: A telecom company can deploy a natural language IVR to handle common billing queries. Users can say things like, “What’s my current balance?” or “When is my bill due?” And the system retrieves the appropriate information from the account.
- Hotel reservations and changes: A hotel chain can use a natural language IVR to handle room bookings, cancellations and modifications. Users can simply say, “I want to change my booking from next week to next week,” and the system updates the booking in real time.
- Bank Account Management: A bank can use a natural language IVR for customers to check account balances, transaction history, or initiate a money transfer. Users can say things like “transfer $200 to my savings account” and the IVR understands and processes the request.
- Retail Order Tracking and Support: An e-commerce company can use natural language IVR to help customers track orders or initiate returns. A customer might say, “Where’s my order #12345?” And the system pulls tracking details to provide updates.
Natural language IVRs are particularly useful when customer interactions require personalization, phrasing flexibility, or consistent language. They can process diverse inputs, allowing users to express requests in different ways while still providing accurate responses. When tasks involve straightforward, routine language — such as paying an account balance or tracking an order — natural language IVRs can handle requests quickly and efficiently, reducing the need to escalate to human agents. and improve overall service consistency.
For some of these complex inquiries, a Visual IVR can really help callers.. You can use it as an alternative or complement to natural language IVR.
Is Natural Language IVR Right for You?
Natural language IVR can be highly effective for call centers that have routine high-volume, low-complexity inquiries. It excels at automating tasks that would otherwise tie up agents, making them especially valuable in environments where callers need quick, consistent responses or where agents have a variety of skills. There are levels.
At the same time, if you have a call center that deals almost exclusively with complex issues or high-stakes edge cases, having a natural language IVR can do more harm than good. Emergency healthcare or insurance claims services, for example, may not subject people to interactions with robots when they are already under stress.
Similarly, if you have a very low call volume or if your customers have uncomplicated reasons for ever calling, you can get away with it. Following IVR best practices And using a short self-service menu. A natural language IVR, in this case, may be overkill.