boost.ai’s Head of Voice lays out why voice tech sucks and how to fix it
At this year’s Voice22 summit in Arlington, Virginia, I had the pleasure of holding a keynote presentation on how to unlock true customer value with voice technology. I’d like to share some of my thoughts from that presentation and summarize the key steps that can be taken to ensure a successful voice project.
But first, let me start with a fairly controversial statement (followed by a quick qualifier)...
Voice tech sucks… if we don’t implement it properly, don’t have the right teams in place, and don’t educate enterprises on best practices around implementation.
Here’s the good news: it doesn’t have to be this way. Voice technology can be implemented to transform the customer experience, making every customer—and every agent—feel like a VIP.
Right now, however, that VIP experience is far from reality in customer service. Poor service remains the leading cause of customer churn, with dissatisfied customers costing businesses over $500 trillion annually—a staggering loss, more than double the global real estate market’s total value, all due to subpar customer interactions.
Over-the-phone service, a cornerstone of enterprise service strategies, is a prime example. Long wait times, frequent call drop-offs, and frustrating experiences for both customers and agents highlight the urgent need for reinvention in this outdated channel.
By implementing voice tech correctly, we can bring value to contact centers, both through voice bots and analytics. We can make products and services more easily available and drive up adoption rates.
There are many strategies to achieve this, with artificial intelligence – and specifically conversational AI – being the driving force and helping to solve key service challenges like,
- How do we ensure that customers don’t keep getting handed over between agents?
- If a customer has a simple question, how can we automate to ensure they get their answer with minimal friction?
- How can we take the user's information and find out more about them?
- How do we augment call center agents with information and tools to provide a better customer experience?
One of the areas where conversational AI can really help is in voice-based telephony. The elements for successful voice experiences in this channel include,
- Speech flexibility - allowing organizations to use the speech services that they prefer and avoiding a “crap in, crap out” scenario
- Strong NLU - means the ability to actually understand user intent. We’ve all experienced a bad chatbot, and adding voice on top of it will not make things any better
- User friendliness - aka the organization of data and information and content design
In developing a successful voice project there are several key areas that need to be considered.
Prepare for success
Before deploying a voice bot you need to ensure you’re starting with the right technology and that you understand what use cases you are attempting to solve.
Ensure that all stakeholders are aligned and then work together on scoping sessions so they understand what is expected and what the goals of the project are.
FAQs are often seen as poor targets for a conversational voice bot, but if well-structured, they can be a great starting point. A voice bot can offer a soft launch, showcasing possibilities and aligning decision-makers on the technology's potential.
Optimization is crucial
As soon as a project is underway, we must begin the process of optimization. You should never consider deployment before training the model and understanding (and hopefully gathering) data on the end users.
If you are deploying both voice and chat, you need to optimize for each channel specifically. The content can (and should) differ, whether you have a narrow set of use cases or a broad scope that covers varied support scenarios.
It’s through optimization and thorough testing that we elevate the end user to the VIP status that I mentioned earlier.
Going live doesn’t mean going home
We see the same scenario often - companies invest time and resources in building a voice or chatbot, push it live and then let it languish. This is the wrong approach.
Once a bot is live, there’s an incredible opportunity to gather real-world data from users and use it to optimize even further. Pre-deployment, the data gathered often presents an incomplete picture of how a voice bot can help serve customers. It’s only after the channel is live that you can start filling in the gaps as users ask for things you may not have scoped for and as their expectations increase now that they are interacting with the channel.
Educate, educate, educate
From project start to finish, education is crucial and often overlooked. Whether you’re working with AI trainers, engineers, the contact center, or marketing, everyone needs to be up-to-speed and aligned on how the project functions and fits within the organization.
Do business decision-makers get educated enough as well? More often than not, that isn’t the case but it is just as important as other facets of the business.
Test for the unexpected
I briefly mentioned testing earlier, but it deserves special focus. Before launching an AI voice bot, thorough testing is essential to ensure it works smoothly and avoid any unexpected issues. Don’t just test the happy path—test deep, broad, and even those scenarios you think users won't ask, because they will.
Keep in mind that testing for voice differs from chat; prompts must be adjusted for how they sound, and omit elements like gifs or emojis that don’t translate from chat. By following these guidelines, we can create AI voice bot experiences that make every customer feel like a VIP.