What is Conversational IVR?
IVR stands for Interactive Voice Response, an automated phone system that interacts with callers. It uses voice prompts and touch-tone inputs often with keypad navigation. The goal of IVR technology is to route calls to the appropriate recipient. Furthermore, IVRs also gather information from the caller, or provide information to the caller.
The technology works by playing a series of pre-recorded voice prompts that guide the caller through the call. For example, a system might ask the caller to enter their account number or to select an option from a menu. The caller inputs their response by pressing the touch-tone buttons on their phone. Then, the system uses that information to determine the next step in the call.
Businesses program IVR systems to handle a wide range of tasks. For example, they can route calls to specific departments, taking payment information, and providing information on products or services. Businesses use this technology to handle large volumes of calls more efficiently. It allows them to handle many calls at once without the need for live agents.
What is the difference between is Conversational IVR and Traditional IVR?
Conversational IVR (Interactive Voice Response) is a system that interacts with customers through natural language conversations over the phone. It provides a more welcoming experience. In contrast to traditional systems, Conversational IVR relies on pre-recorded voice prompts and menu options.
In conversational IVR, customers can communicate naturally. Then, the system uses artificial intelligence (AI) to understand the customer’s intent and respond with relevant information. This helps answer customers questions quickly and efficiently without having to navigate through multiple menu options.
What is a Modern IVR?
A modern IVR is a cutting-edge technology that serves as a key component of call center automation. It enables businesses to streamline customer interactions and manage high call volumes. Likewise, it provides efficient customer service, all while reducing operational costs.
Contact center automation refers to the implementation of advanced technologies and software that automate tasks and processes. In short, the objective is to ultimately improving customer experience and agent productivity.
Companies can design Modern IVR systems to be user-friendly and intelligent. They use natural language processing and artificial intelligence (AI) to accurately understand and process customer queries. By integrating these cutting-edge technologies, modern IVR systems are capable of automating a range of tasks, such as call routing.
Businesses often design Traditional IVR systems without prioritizing the user experience. Hence, they can be frustrating to use and can lead to negative experiences for customers. This is a result of the fact that companies often design IVR systems to automate tasks and reduce costs. Instead, they should be focusing on creating a positive user experience. Customer experience is essential to any business’s success, and contact centers play a critical role in delivering exceptional service. However, traditional Interactive Voice Response or IVR systems face challenges like poor customer satisfaction and higher labor costs.
There are several reasons why IVR systems may not always provide a great user experience. Customers often find traditional IVR systems to be complicated and frustrating. As a result, contact centers see increased misrouted calls, wait times, pressure on customer service agents and poor customer satisfaction. Moreover, businesses are losing billions of dollars every year due to poor customer experience, according to CustomerThink.
What are the pros and cons of IVR in a Contact Center?
High Transfer Rates
Many customers still want or need to speak to a human agent. IVR’s primary function is to route callers quickly. The objective is to get the user to the most appropriate human agent available. However, misrouting is a very common issue.
Poor call routing leads to customers being transferred multiple times and having to repeat their issue each time. This can be frustrating for both the customer and the agent, who is tasked with resolving the issue. High transfer rates waste valuable agent time and increase customer wait times.
Limited Self-Service Options
IVR systems are designed to handle a limited set of tasks, such as routing calls or providing basic information. However, if a customer has a more complex issue that requires human interaction, IVR can create frustration. In some cases, it can also lead to longer wait times and high abandonment rates. A high abandonment rate is problematic for organizations as it means customers are dropping out of the customer service system. Equally important, low abandonment rates and excellent customer service are crucial for customer loyalty.
Callers tend to zero out or hang up quickly if IVR menus are too complex. This can lead to frustration and confusion, especially for users who are not familiar with the system. Call containment measures the percentage of customers who complete their enquiry using self-serve technologies. A poor call containment rate means the IVR system isn’t fulfilling its function of providing self-serve automation for high-volume enquiries.
Limited feedback and interaction: IVR systems can also feel impersonal, with limited feedback and interaction options. Customers feel like they are talking to a machine rather than a human, which can lead to frustration and dissatisfaction.
IVR technology can provide cost savings for companies by automating tasks and reducing the need for human agents. It can result in a reduction of FTEs and other operational costs. However, an IVR will negatively impact the customer’s experience.
Conversational IVR technology can enhance the cost savings potential by providing a more efficient and personalized customer experience.
Conversational IVR systems can be integrated with existing customer service systems. They can be used to automate routine tasks such as providing account balances or flight information. As a result, it can free up customer service agents to handle more complex issues.
Overall, conversational IVR can provide customers with a more welcoming customer service experience. At the same time, it can help businesses reduce costs and improve customer satisfaction.
Conversational IVR in a call center is a technology that allows customers to interact with a company through voice.
What are the Benefits of Conversational IVR?
Reduced call volume:
Conversational IVR can handle simple queries and free up agents to focus on more complex issues. As a result, this can reduce call volumes. Conversational IVR systems can reduce costs by automating routine interactions and reduce staffing costs.
Improved customer satisfaction
Providing a more human experience, leads to higher customer satisfaction. Conversational IVR is a more natural and intuitive interface for customers, allowing them to interact with a company using voice. By providing faster and more accurate responses, reduce misrouting and wait times as customers do not need to repeat themselves.
Increased call efficiency
Handle multiple requests at once and often resolve issues without transferring the call to a live agent. Conversational AI can help your business save time and improve efficiency.
By automating routine tasks, businesses can direct calls to the right department, and provide information on products and services. With less misrouting contact centers can reduce the need for human agents.
Businesses can integrate Conversational IVR with other technologies, such chatbots, to create a multi-channel customer service experience.
Check out this short video from Swisscom to understand what Conversational IVR made a difference for their call center.
Impact of AI-powered IVR
The impact on businesses and customers can be significant. Businesses can improve their customer service processes and reduce costs. At the same time, customers can get the information they need more quickly and efficiently. Additionally, conversational IVR can help businesses gather valuable customer insights and make data-driven decisions to better meet customer needs.
How to Calculate The ROI of IVR Solutions
Research from ContactBabel cites that the cost of a live service telephone call varies considerably. A call has a mean average of £5.42. In contrast, the average historical cost of a telephony self-service session is estimated to be around 30-70p.
There are a number of studies showing that IVR harms the Telephone Experience. For example, a 2019 survey by Avaya found that 60% of customers felt frustrated with IVR systems. Similarly, 68% said that they had hung up the phone because of a frustrating experience with an IVR system.
The main problem with keypad navigation in IVR systems is that the experience is predetermined. Customers are forced to navigate a pre-determined path, and call center reps are limited in how they can assist customers. This can lead to frustration and poor customer experiences.
Swisscom, for example, has a customer enquiry hotline that uses a voice-controlled system to improve the customer experience. The system assigns customer enquiries quickly and accurately, maximizing the valuable resources of the hotline agents.
Read how one of Europe’s largest telecommunication providers achieved IVR success, here.
Discover Conversational IVR Benefits for Your Business
In today’s fast-paced business world, it’s more important than ever to provide customers with quick and efficient customer service. One way to achieve this is by using conversational IVR. This innovative technology uses AI and natural language to simulate a human conversation. In short, it makes it easier for customers to get the help they need.
Here’s why your business should consider using conversational IVR, based on research from ContactBabel and Teneo.ai.
Increased Customer Satisfaction
Increase customer satisfaction is one of the biggest benefits of using conversational IVR. According to ContactBabel, customers are more satisfied with their telephone experience by speaking to an IVR system instead of navigating a menu. This is because conversational IVR provides a more intuitive and seamless experience.
Improved Call Efficiency
Improved call efficiency is another benefit of Conversational IVR. Research from Teneo.ai has shown that conversational IVR can reduce average handle time (AHT). Furthermore, it can improve average speed to answer (ASA). This is because a solution with open questions can handle multiple requests at once. It also can often resolve issues without transferring the call to a live agent. This save businesses time and money, while also providing customers with a more efficient experience.
More Accurate Data Collection
Conversational IVR can also collect more accurate data on customer interactions. Businesses can use this data to improve the system and make better business decisions. For example, businesses can use this data to identify areas where they can improve their customer service processes. It allows managers to make changes to better meet customer needs.
Conversational IVR integrates with other technologies, such as chatbots, to create a seamless, multi-channel customer service experience. This makes it easier for customers to get the help they need, regardless of their preferred method of communication. This increased accessibility can lead to higher customer satisfaction and improved call efficiency.
Conversational IVR is a cutting-edge technology that offers numerous benefits for businesses, including increased customer satisfaction and improved call efficiency. Based on research from ContactBabel and Teneo.ai, it’s clear that conversational IVR is a valuable investment for any business. Especially those looking to provide top-notch customer service.
How to improve CX with Conversational IVR?
How to improve customer experience (CX) with Conversational IVR:
Conversational IVR can improve the customer experience by providing more natural, intuitive, and efficient interactions in several ways:
Personalized customer interactions
With Conversational IVR, organizations can offer personalized customer interactions like human conversations. Language technology allows conversational IVRs to understand and respond to customer inquiries in a human manner. It reduces frustration and make the interaction more welcoming. This can help to build trust and increase customer satisfaction.
Quick and easy issue resolution
It can help customers quickly and easily resolve their issues. This means that customers don’t have to wait in lengthy queues or navigate through complex IVR menus. This minimizes frustration.
By providing real-time support by routing customers to live agents when needed, customers can receive the help they need quickly and efficiently.
Integration with other channels
Integrating the conversational IVR with other customer service channels, such as live chat and social media, can provide a seamless experience for customers.
Reduced costs and increased efficiency
Conversational IVR can handle repetitive tasks, allowing agents to focus on conversations that add more value to the customer relationship. This can help to reduce costs and increase efficiency.
Richer and insightful data
Conversational IVR can provide organizations with valuable insights into what customers contact them for most often, what goods or services they’re requesting, and what issues recur frequently. These insights can help organizations improve automation, personnel management, digital deflection, and customer engagement.
By implementing a better Telephone Experience, businesses can improve the customer experience by providing more natural, intuitive, and efficient interactions. This leads to increased customer satisfaction and loyalty, as well as reduced customer frustration and call volume. Contact center automation at scale is the only viable solution to a myriad of problems, and OpenQuestion is the key for achieving success in this area.
How to implement Conversational IVR?
Implementing a conversational IVR to achieve contact center automation involves several steps, including:
Determine business goals: Identify the business goals for the conversational IVR. For example, these can be reducing call volume, improving call resolution rates, decrease mis-routing and enhancing customer satisfaction.
Choose a platform: Choose a conversational IVR platform that fits the needs of your organization. Equally important, consider factors such as ease of use, fast deployment, scalability, integrations with existing systems, and the level of languages and customization available.
Define customer journeys: Define the customer journeys that the conversational IVR will support, such as account balance inquiries, payment processing, and product information.
Design the conversational flow: Design the conversational flow with the goal to provide excellent customer service.
Integrate with existing systems: Integrate the conversational IVR with existing systems. For example, customer relationship management (CRM) and telephony systems.
Test and refine: Test the conversational IVR to ensure that it is functioning as expected and making the customer experience as positive as possible. Then, refine the IVR as needed based on feedback and testing results.
Launch and monitor: Launch the conversational IVR and monitor its performance over time. Use metrics such as customer satisfaction, call resolution rate, and cost savings to assess the success of the IVR and make any necessary adjustments.
Companies can achieve Contact center automation by following these steps. Businesses can effectively implement a conversational IVR that meets their business goals and enhances the customer experience.
How to transition from a traditional IVR system to a Conversational IVR?
Many businesses have invested significant resources into their existing IVR infrastructure and may be hesitant to completely replace it.
In terms of technology and resources, a conversational IVR implementation requires access to a platform, a development environment, and tools such as APIs and SDKs.
The deployment may also require telephony systems, databases, and other resources, depending on the organization’s requirements. It is also important to have a team with the necessary technical skills and experience to implement and deploy the solution effectively.
The process typically involves a few easy steps:
- A transition to Conversational IVR should allow for businesses to enhance the customer experience while leveraging their existing infrastructure.
- The architecture is easily integrated with existing Contact Center platforms.
- An implementation guide for a 10-week project, including a blue-print solution, demo access, and packaged documentation.
- A Customer Success Manager to ensure a smooth transition.
Begin your journey with business and technical checklists and a ready-to-use implementation plan. It should not take more than 60-days, which you can read about here.
Learn more about Telefónica’s journey, here.
Boost Your Contact Center’s Efficiency with OpenQuestion: Save €3.2 Million Annually
Discover how OpenQuestion, a cutting-edge Teneo.ai solution, can transform your call center’s performance and save millions on our e-book. Compare the cost and efficiency of a contact center before and after implementing open questions. The e-book examines a call center that managed 10 million inbound calls at a cost of €50 million, with 7 million calls correctly routed, 1 million misrouted, and 2 million requiring redialing.
ROI Breakdown: OpenQuestion’s €3.2 Million Annual Savings for Call Centers
By introducing OpenQuestion, the call center experienced a decrease in call volume (9.96 million). Furthermore, the total expense decreased down to €46.8 million. The implementation of OpenQuestion resulted in 40,000 fewer calls attended by agents and a net savings of €3.2 million, highlighting its effectiveness in enhancing call center performance and reducing costs. Learn more by accessing our in-depth information here.
In conclusion, OpenQuestion is revolutionizing the customer experience and enabling a typical call center to save €3.2 million annually. Boost your contact center’s efficiency with this innovative solution.
What is the future of IVR and Conversational IVR?
The future of conversational IVR, or Interactive Voice Response, is likely to see a number of new developments and trends. Here are some of the most significant changes that we might see in the coming years:
Increased Use of AI and Natural Language technologies
With advancements in artificial intelligence and natural language, such as ChatGPT, Conversational IVR systems are becoming more sophisticated and can understand and respond to a wider range of human speech patterns. This will result in more welcoming interactions, improving the customer experience.
With High Inflation Business are searching for Faster Deployments
Many businesses use AI technologies to augment humans and streamline operations, but the common approach is to apply AI in a way that might not always be effective, due to limitations in the technology platforms. The challenge with many Conversational IVR systems is that they often require extensive programming to be effective, and even then, they may not always be able to understand customer queries accurately.
A Conversational AI solution should be able to connect to all commonly used voice-, or AI-services, from Microsoft, Amazon, Google, OpenAI, and Genesys, among other enterprises.
Improved Speech Recognition
Speech recognition technology will continue to improve, reducing errors and making it easier for customers to interact with IVR systems. This will also make it easier for customers with disabilities or those who have trouble typing to access information and complete tasks.
Overall, the future of conversational IVR is expected to be characterized by increased use of AI, leading to a more seamless and efficient customer experience.
ACD (Automatic Call Distributor): A system that automatically routes incoming calls to the next available agent in a call center.
AI-powered IVR: A system that uses artificial intelligence to understand and respond to customer requests, making the interaction more natural and intuitive.
Automated call routing: The process of automatically directing incoming calls to the appropriate customer service representative based on the caller’s needs or information provided.
Average Handle Time (AHT): The average amount of time an agent spends handling a call, including the time spent on hold, after-call work, and call transfers.
Call Center: A facility that provides customer support services through various communication channels, including phone, email, chat, and social media.
Conversational AI: Conversational AI refers to the use of natural language processing and machine learning to create intelligent virtual assistants that can communicate and engage in human-like conversations with users.
Conversational IVR: An IVR system that uses natural language and artificial intelligence to understand and respond to customer requests in a conversational manner.
Contact Center: A type of call center that provides support and information to customers through multiple channels, including phone, email, chat, and social media.
Customer Experience (CX): This is the overall perception of a customer about a company and its products or services.
Customer Self-Service: A service provided by a company that allows customers to handle their own inquiries, purchases, or support needs without the assistance of a customer service representative.
First Call Resolution (FCR): The percentage of calls resolved on the first call, without the need for a follow-up call.
GPT-3: GPT-3 is a language model developed by OpenAI. It uses deep learning to generate human-like text. It can perform various natural language processing tasks, including language translation, question-answering, and text summarization.
GPT-4: Generative Pre-trained Transformer 4 is a multimodal large language model created by OpenAI and the fourth in its GPT series.
Intent Recognition: The ability of a virtual assistant to understand the purpose or goal of a customer’s request.
IVR chatbots: An IVR system that uses chatbot technology. It interactswith customers and provide information or support.
IVR self-service solutions: Self-service options provided by an IVR system. For example, options offered could be account balance inquiries or bill payments.
IVR System: A type of technology that uses automated voice and touch-tone input. It interacts with customers and provide information or support.
IVR technology: A type of technology that uses automated voice and touch-tone input. It interacts with customers and provide information or support.
IVR virtual agent: An IVR system that uses a virtual assistant to interact with customers. It provides information or support to them.
IVR Voice interaction design: The process of designing the voice and touch-tone interactions between customers and an IVR system to ensure a positive customer experience.
Multi-Channel Support: The ability to provide customer support through multiple channels, including phone, email, chat, and social media.
Natural language IVR: A system that uses natural language to understand and respond to customer requests in a conversational manner.
Natural Language Processing (NLP): A branch of artificial intelligence that focuses on enabling computers to understand and respond to human language.
Open-ended questions: Open ended questions relate to the verbal communication between a human caller and a contact center. The technology asks the user what they would like support with in a human-like way.
OpenQuestion: It’s a Teneo-based product that listens to users requests when they call a business for support. In short, OpenQuestion captures the request and routes the user to the correct agent, without the need for a caller to use the keypad to navigate through a menu.
Personalization: The ability of a virtual assistant to tailor its responses to an individual customer based on their previous interactions and preferences.
Service Level Agreement (SLA): A contract between a company and its customers that defines the level of service to be provided, including response time and resolution time.
Skills-Based Routing: Skills-Based Routing: It is the process of routing incoming calls to the agent who is best equipped to handle the call based on their skills and expertise.
Speech-enabled IVR: A system that uses speech recognition technology to understand and respond to customer requests. This contrast with traditional systems that use touch-tone input.
Virtual Agent: A type of virtual assistant that uses AI and NLP to communicate with customers. It provides support and information.
Virtual assistant IVR: An IVR system that uses a virtual assistant to interact with customers. It provides support and information.
Virtual Assistant: A software program that provides support, information, and assistance to users through natural language interactions.
Voice-activated IVR: An IVR system triggered by a customer’s voice. This contrast with traditional systems that are triggered by touch-tone input.
Voice-activated Virtual Assistant: A virtual assistant controlled using voice commands.
Voice Biometrics: The process of using voice recognition technology to identify an individual, It uses the person’s unique voiceprint to authenthicate him.
Voice biometrics IVR: An IVR system that uses voice biometrics to verify the identity of the customer. It provides personalized service.
Voice Recognition: The ability of a virtual assistant to understand and respond to spoken language.
Voice User Interface (VUI): The interface through which customers interact with a virtual assistant using voice commands.
Workforce Management (WFM): The process of managing the staffing and scheduling of agents in a call center to ensure adequate coverage and efficient use of resources.