Conversational AI is emerging as a critical component of most modern contact center operations. Rapidly evolving algorithms are offering companies a range of ways to improve customer experiences, boost efficiency, cut costs, and even access more valuable data.
The AI revolution isn’t just driving the creation of higher quality chatbots (with generative AI). There’s also an incredible opportunity for businesses to leverage AI across a range of channels, including in the voice landscape.
Contact center Voice AI allows organizations to design voice bots that can streamline the IVR experience, and enhance customer conversations. After all, studies show that 73% of all contact center interactions involve voice.
Unfortunately, deploying contact center Voice AI solutions can be challenging. Here’s where most businesses go wrong with their strategies, and how you can boost your chances of success.
The Main Challenges with Contact Center Voice AI
Voice AI and automation can optimize contact centers in a variety of ways, delivering unique advantages to both employees and customers alike. But leveraging the power of voice AI in your contact center requires meticulous planning, the right strategy, and support from the right vendor.
Here are the biggest challenges businesses face when implementing Voice AI initiatives, and how you can sidestep them with your initiative.
1. Using the Same Framework Everywhere
Building effective voice bots and voice AI solutions can be complex. Voice bots aren’t exactly the same as chatbots. They rely more heavily on algorithms for natural language processing (NLP), text to speech (TTS), and speech to text (STT). Plus, it’s often more complex for bots to understand spoken language than written text, thanks to varying dialects, speech clarity, and other factors.
The complexity of implementing a voicebot into your system may prompt you to use the same framework for every region, country and target audience. However, this can be a dangerous approach. Some platforms are stronger at understanding certain languages and weaker at dealing with others. Additionally, the framework used to process data can lead to compliance issues, as the regulatory environments of different countries can vary.
For an outstanding solution, you’ll need to find a solution that can adapt and change to handle different languages, voice channels, call flows, and requirements simultaneously. You should be able to create multiple versions of your voice solution, to suit various needs.
2. Not Prioritizing Integration
Most companies investing in contact center voice AI know their solution needs to integrate seamlessly with their contact center solutions, phone systems, and any other platform they might use to manage voice. However, they often fail to recognize the importance of comprehensive integration.
Your AI systems shouldn’t just work seamlessly with your contact center, they should also integrate with a range of back-end systems and processes, from your Customer Relationship Management (CRM) tools to your analytical resources, databases, and more.
To unlock the full benefits of voice AI for automating crucial processes, whether it’s customer self-service, note-taking, or customer journey analysis, you need a flexible ecosystem. Look for a solution that can easily integrate with all voice engagement channels, recording tools, biometric systems, and anything else your business might use.
3. Failing to Consider all Use Cases
Often, one of the most common ways companies implement voice AI into their contact center, is by creating a conversational IVR solution. Adding voice AI to your IVR technology is an excellent way to improve the customer experience. It can enable more intuitive self-service experience via voice channels, and reduce the number of customers routed to human agents for common queries.