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Conversational IVR is the evolution, or even revolution of telephonic customer service. Forget button-pressing, and simply let customers tell your Conversational AI what they need and want.
Conversational Interactive Voice Response (IVR), is a telephonic customer service system powered by AI. Unlike traditional IVR with its button-pressing menus, Conversational IVR uses natural language processing (NLP) to understand a customer's spoken request.
This allows customers to talk to a smart assistant on the phone. The IVR analyzes the customer's intent and responds either with relevant information or by routing them to the right human agent. This frees up agents for complex issues, shortens wait times and offers customers a more natural and efficient experience for simple inquiries.
The roots of IVR go back to the early phone days, when operators manually connected calls using switchboards. In the 1960s, the first Touch-Tone telephones with buttons paved the way for Dual-Tone Multi-Frequency (DTMF) IVR. These early systems used recorded prompts with menus of options you selected by pressing buttons. Think "Press 1 for Sales, 2 for Support..." While efficient for basic routing, they lacked flexibility and offered a frustrating experience.
The 1970s saw the rise of Voice Recognition (VR) IVR, where callers spoke their choices. However, VR technology was limited, often requiring specific keywords and struggling with accents or background noise.
The late 20th century brought Menu-Driven IVR with more complex decision trees and pre-recorded responses. This offered some improvement, but it remained rigid and unable to handle nuanced requests.
A big step forward was the rise of Natural Language Processing (NLP) in the early 21st century. Conversational IVR, powered by NLP, understands the meaning behind spoken sentences, not just keywords. This allows for more natural conversation with the system.
The latest advancement comes with Large Language Models (LLMs). These AI models enable even more sophisticated interaction. LLM-powered Conversational IVR can hold more complex dialogues, understand context better, and adapt to different communication styles. This makes the future of IVR bright, promising a truly natural and efficient way for companies to interact with their customers..
Here are 5 key components that make Conversational IVR systems work:
This component converts the caller's spoken words into digital text, allowing the system to understand what's being said.
This AI technology analyzes the text from ASR to grasp the meaning and intent behind the caller's words. Essentially, it figures out what the caller wants.
This component manages the flow of the conversation. It uses the information from NLU to determine the next step, whether it's providing information, routing the caller to an agent, or asking clarifying questions.
Once the system knows how to respond, TTS converts the chosen response back into natural-sounding speech for the caller.
Conversational IVR can access and utilize information from a company's knowledge base, allowing it to answer frequently asked questions or provide specific details directly.
Conversational IVR interactions follow a typical path, with the goal of either answering your query or routing you to an appropriate human agent.
Imagine you call a company. A friendly voice greets you (pre-recorded audio). Automatic Speech Recognition (ASR) then kicks in, converting your spoken response into text.
Natural Language Understanding (NLU) then analyzes the text to understand what you want. Did you say "billing" or "technical support"? Based on this (intent recognition or prompting), the system uses Dialog Management to choose the next step.
If your request matches a pre-designed response, or the system has enough knowledge to generate a relevant answer, then it plays that as a Text-to-Speech (TTS) prompt. For more complex requests, the system might ask clarifying questions ("Can you tell me more about the technical issue?").
Throughout, the system might access a Knowledge Base to answer FAQs or retrieve relevant information. Finally, depending on your selection or the conversation's direction, the system might:
Route you to the appropriate department using Automatic Call Distribution (ACD).
Offer self-service options like account management through voice commands.
Connect you to a live agent for complex issues.
This conversational flow offers a natural and efficient way to navigate the IVR system, getting you the help you need faster..
Speech recognition is a huge upgrade compared to traditional button press IVR. Let’s look at how they are different.
Traditional DTMF IVR relies on button presses for interaction. Imagine a robot voice saying "Press 1 for Sales, 2 for Support..." You respond by pressing the corresponding button on your phone's keypad. This is limited, inflexible, and offers a frustrating experience if you forget the options or your desired choice isn't listed.
Speech recognition, conversational IVR ditches the buttons. You speak your request naturally, like "Connect me to sales." Advanced speech recognition technology understands your spoken words and translates them to text. The system then uses Natural Language Processing (NLP) to grasp the meaning behind your words and route you accordingly. This allows for a more natural conversation and handles a wider range of requests compared to the button-pressing days of DTMF IVR.
24/7 availability: IVR systems operate round-the-clock, providing customers with support and information anytime they need it.
Quick resolutions: Automated responses and self-service options help customers resolve their issues quickly without waiting for a human agent.
Reduced operational costs: Automating routine inquiries reduces the need for a large customer support team, saving on labor costs.
Scalability: IVR systems can handle a high volume of calls simultaneously without additional costs, unlike human agents.
Call routing: Efficiently directs callers to the appropriate department or agent, minimizing transfer times and improving first-call resolution rates.
Handling peak times: Manages high call volumes during peak times effectively, reducing wait times and customer frustration.
Customer insights: IVR systems can collect and record customer interactions, providing valuable data for improving services and products.
Personalization data collected can be used to personalize future interactions, enhancing customer satisfaction.
Standardized responses: Ensures consistent and accurate information is provided to all customers, reducing the risk of human error.
Compliance: Helps in maintaining compliance with regulatory requirements by ensuring that all interactions follow predefined scripts and protocols.
Customizable menus: IVR systems can be tailored to fit the specific needs of a business, offering customized options and messages.
Integration with other systems: Can be integrated with CRM, ERP, and other business systems for seamless operations and data flow.
Free up human agents: By handling routine tasks, IVR systems allow human agents to focus on more complex and high-value interactions.
Efficient workflows: Streamlines workflows by automating repetitive tasks, leading to increased overall productivity.
Uninterrupted service: IVR systems can continue to provide service during power outages, natural disasters, or other disruptions, ensuring business continuity.
Adaptability: Easily scalable to accommodate the growing needs of a business without significant additional investment.
Future-proof: Can be updated with new features and integrations as technology evolves, ensuring long-term utility.
Secure data handling: IVR systems can be designed to handle sensitive information securely, complying with data protection regulations.
Authentication and verification: Can include features for secure customer authentication and verification, enhancing the security of transactions and interactions.
System stability metrics, such as uptime and latency
Question recognition metrics, such as true positive rate
Customer experience metrics, such as customer satisfaction %
Containment metrics, such as First Call Resolution
Activation metrics, such as signup %
Which ones are most relevant for your business depend on your goals with the IVR. However, it can’t be stressed enough that - whatever else - the key metrics are those that measure how well and how fast the IVR system can recognise customer queries correctly!
Conversational IVR systems are often used in customers service for all manner of high traffic queries and requests, for example in retail business:
Order status inquiries
Returns
Warranty claims
What’s in stock inquiries
Reservations/cancellations
In most cases, high traffic calls can be resolved right away, or the call can be used for information gathering leading to more efficient handover to a human agent (or ticketing system).
In banking and finance, advances in user identification mean that customers can make inquiries about:
What’s my balance
Making transfers
Opening, closing altering accounts
Reporting fraud or fishing
Many more use cases are on the board, once again more complicated inquiries can be handed off to human agents.
Due to the sensitive nature of healthcare, conversational AI is mainly a useful tool for the practical side of healthcare customer interactions:
Appointment (re)scheduling
Patient information
Reminders
Insurance details
Prescription renewals
Reporting measurements and data points
Implementing a conversational IVR involves several steps, starting with defining your business goals. During the implementation process it’s always good to keep those goals in sight.
Identify business goals and the customer issues you want to address. Analyze call data to understand common inquiries and areas for improvement. Define what your main value driver will be, for example reducing peak times, average caller wait times, percentage of calls automated, etc.
Select a platform that fits your needs and budget. Consider factors like cost, scalability, integration capabilities, and ease of use.
Using the proven CDI method, map out the dialogue between callers and the system. Consider customer prompts, system responses, and potential decision points based on user input.
Prepare the system with relevant data like customer queries (and perhaps knowledge base entries). Train the NLU engine to understand your target audience's language patterns.
Rigorously test the system for accuracy, naturalness, and call flow efficiency. Gather user feedback and use it to refine the system for optimal performance.
Remember, successful implementation hinges on considering your business objectives. Align your IVR with the level of self-service you want to offer. Usually it’s a healthy ambition to ensure it complements, not replaces, your live agents.
Technology selection:
Choosing the right Conversational IVR technology and platform involves analyzing your business needs and aligning them with platform features. Here's a breakdown to help you select the best fit:
Identify customer needs: What issues do callers typically face? Can an IVR address them effectively?
Self-service goals: How much self-service functionality do you want to offer (e.g., FAQs, account management)?
Agent workload: Can an IVR reduce call volume and streamline routing, freeing agents for complex issues?
Natural Language Processing (NLP) capabilities: Assess the platform's accuracy in understanding natural speech and intent.
Scalability and integrations: Can the platform handle future growth and integrate with your existing CRM or knowledge base systems?
Security and compliance: Does the platform meet your data security and regulatory compliance requirements?
Ease of use and administration: Consider the platform's user-friendliness for building and managing conversation flows.
Industry reputation: Look for providers with experience in your specific industry and a track record of success.
Pricing models: Compare pricing structures (subscription, per-minute) and ensure it aligns with your call volume.
Free trials and demos: Take advantage of trial periods and demos to test the platform's functionality and user interface.
Customization: Consider the platform's ability to tailor the user experience (e.g., greetings, branding).
Reporting and analytics: Does the platform offer insights into call flow performance and user behavior?
Customer support: Ensure the provider offers adequate technical support and resources for ongoing assistance.
By carefully analyzing your needs and evaluating platform features, you can choose the IVR technology and platform that empowers you to deliver an exceptional customer experience - and realize your business goals.
Integration with existing systems:
It can add great value to make your IVR more transactional and/or allow it to have more context. Integrating a conversational IVR (Interactive Voice Response) with CRM, databases, and other systems involves creating a communication hub. Here's a simplified approach:
Choose your tools: Pick a Conversational IVR platform that offers API (Application Programming Interface) access. Many CRMs and databases also offer APIs.
Map the conversation flow: Design the questions and responses your IVR will use. Identify where information needs to be retrieved from (CRM, database) and where updates might be needed (CRM).
API Connections: Developers will build connections between the IVR platform and your CRM/databases using APIs. This allows data exchange during conversations. Imagine the IVR acting like a waiter, taking your order (user request) and fetching information/updating systems (kitchen/databases) based on your needs.
Security: Ensure proper authentication and authorization protocols are in place when connecting systems. You don't want just anyone accessing sensitive data.
Remember, this is a simplified explanation. It's best to consult with CDI for a successful integration.
As a globally recognised Conversational AI company, we’ve helped brands to deliver Conversational AI systems that deliver great service to their audience whilst improving their bottom line.
If you’d like help understanding how you can find the best IVR system for your business case, don’t hesitate to get in touch.
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