The idea behind conversational IVR is simple: a customer speaks naturally to the IVR as they would with a real agent, and the system understands the request and delivers the solution without involving a live person. The result is lower labor costs and happier customers.
Or, at least, that’s the goal.
In reality, do customers actually care about being able to speak naturally to an IVR?
Do Callers Really Want to Speak Freely? It Depends.
A customer’s priority is always to solve their problem or answer their question in the fastest, most trouble-free way possible. Whether callers appreciate the option to speak naturally to a conversational IVR system depends on its effectiveness.
If speaking naturally to the system results in quick and accurate assistance, then yes, customers likely prefer this method over navigating through menus using their keypad or brief, disjointed phrases.
However, conversational IVR systems lose their appeal immediately if they misunderstand the caller’s intention. For instance, if a customer says, “I want to increase my credit limit,” a poorly trained IVR could misinterpret this as a request to discuss credit card charges and route the call to the wrong department.
In cases like these, speaking naturally to the IVR creates delays and frustration. The customer would get faster, more reliable help by using keypad options to choose the correct department themselves.
Beyond convenience and efficiency, another reason customers might prefer speaking freely with IVRs is the enhanced accessibility these systems offer. Conversational IVRs are particularly beneficial for individuals with disabilities, as they simplify interactions and make services more inclusive.
For instance, people with visual impairments may find voice-driven systems more straightforward to use than traditional keypad-based interfaces.
Similarly, conversational IVRs are helpful for those with motor impairments, making it easier for them to use the service without needing to physically handle the device.
Advanced speech recognition that can understand different speech patterns also assists people with speech impairments, ensuring that everyone has equal access to support and services.
How to Make Sure Your Conversational IVR Is Effective
Take Training Your IVR Seriously
If you’re considering a conversational IVR system for your customers, you’ll first need to set it up for success. This starts with training the system to understand and process natural language effectively. With proper training, your IVR system can engage in meaningful conversations, recognize spoken words accurately, and grasp the intent behind customer inquiries.
But there’s more to training a conversational IVR than just feeding it the right phrases.
The system must understand the many different ways customers can ask for the same thing. For example, callers who want to check their account balances could phrase this in vastly different ways. “What’s my current balance?” and “Can you tell me how much money I have in my account?” should prompt the same response from the IVR.
A conversational IVR system must also be able to understand colloquialisms, accents, and the natural rhythm and flow of a conversation. By teaching the IVR to recognize these subtleties, it can better understand what customers are trying to say, even when they phrase things in unexpected ways.
So how do you start training your system to recognize these nuances?
You’ll need someone with technical expertise to tackle your IVR training. Look for a professional skilled in AI, natural language processing, and natural language understanding who is also familiar with the IVR platform’s interface. While good conversational IVR systems offer user-friendly tools for the initial set up, the complexity of AI and language technologies means you’ll want someone who knows what they’re doing running the show.
Once your IVR is up and running, it will improve over time. It will learn from every interaction, so the more it’s used, the better it will become at interpreting customer needs and refining its responses.
Get Customer Feedback
Your callers are the ones your IVR needs to please, and they have the best insight into how well the system is working. This means their feedback is gold.
Gather their feedback by adding a quick IVR survey at the end of each interaction or just before transferring a caller to a live agent—this means the details will still be fresh in their memory.
Many customers are reluctant to spend time on surveys unless there’s something in it for them. To encourage more customers to share their insights, consider offering a small incentive for completing the survey, such as a discount on future services or entry into a prize drawing.
Ask customers to rate their satisfaction on a scale from one to five, with five indicating complete satisfaction. If a customer picks a three or below, introduce an additional question to find out why they weren’t satisfied. Provide options such as difficulty understanding voice prompts or the system not recognizing their speech, which are common issues customers may encounter.
Regularly analyze the feedback to identify common problems and track whether changes to the IVR are improving customer satisfaction.
For example, if feedback indicates that voice prompts are confusing, they can be rewritten and simplified for better clarity. This continuous loop of feedback and improvement helps ensure that your IVR system consistently meets the needs of your customers and adapts to their preferences over time.
Conduct Regular IVR Testing
Regular IVR testing will help keep your conversational system working smoothly and improving over time. To do this effectively, choose an automated testing service that checks every aspect of the system—from how user-friendly it is to how it handles high call volumes and stressful conditions. These services test the system by simulating a wide range of call situations, helping to spot and fix any problems.
Before you start testing, you should understand the different types of IVR tests you can do. Here are five common testing types and what you can learn from each.
Experience Testing
- How it’s done: This test involves real users interacting with the IVR system in controlled conditions. You can follow along and observe how easy it is for users to complete tasks, whether the instructions are clear, and if the voice prompts are understandable.
- What the results tell you: The results can highlight any confusion or difficulties users experience, which parts of the dialogue are unclear, and whether the overall experience feels smooth and intuitive.
- Changes to make: If results show that users are struggling, then simplifying the dialogue, speeding up response times, or providing more direct paths to common requests could improve the user experience.
Load Testing
- How it’s done: This test simulates a high volume of calls to the system to see how well the infrastructure holds up. It tests the limits of server capacity and call management software.
- What the results tell you: Results will indicate how many calls your system can handle simultaneously before its performance suffers.
- Changes to make: If the system cannot handle your expected call volumes, you might need to upgrade your server capacity or optimize call routing to distribute the load better.
Stress Testing
- How it’s done: This is similar to load testing, but it’s done under extreme conditions, such as rapid spikes in call volume. This tests the system’s upper limits to see how it recovers from failures.
- What the results tell you: This test shows the resilience of the IVR system under stressful scenarios and its recovery speed after overloads.
- Changes to make: You can improve your system by adding failover mechanisms, such as redundant servers, and enhance the recovery process by adding automated system checks that trigger restarts or switchovers without human intervention.
Functional Testing
- How it’s done: This involves going through all the features of the IVR to ensure they work as expected under different scenarios.
- What the results tell you: You’ll learn whether all the features are functioning correctly and if there are any bugs or inconsistencies in the system.
- Changes to make: Any malfunction or bug that the test identifies will need to be fixed. This could involve debugging software issues or updating flawed voice prompts.
Regression Testing
- How it’s done: This test is conducted after updates or changes to the system to check if the new changes have caused any problems.
- What the results tell you: This identifies any unintended consequences of updates or changes, ensuring that new code hasn’t disrupted existing features.
- Changes to make: If regression testing uncovers problems, you may need to roll back the problematic updates. Analyze what caused the issues and address the root cause in the system’s design or code. After making adjustments, reapply the updates incrementally, testing each change to ensure that your system is working properly.
