Get ready, because conversational AI has arrived in the contact center and is changing the way companies engage with their customers.
More and more, conversational AI and artificial intelligence chatbots are serving as the first level of customer support to provide fast, efficient, automated, always-on service that many customers have come to expect. Whether through voice or chatbot, this form of automation allows customers to directly ask a question or present their problem in a natural interaction with the system and receive an answer. When the AI cannot resolve the query, the matter is escalated to a live agent.
This marks a tremendous improvement over the traditional Intelligent Voice Response (IVR), where customers can find themselves trapped in a press-key or voice-response loop. Customers consistently say that a fast response is a competitive differentiator when making a buying decision. And contrary to popular opinion, many customers across all age groups and geographies said that when it comes to basic inquiries, they prefer not to have to interact directly with a person.
The challenge for most businesses is figuring out how to get in the AI game in a way that makes the investment less risky and quickly produces real results. Thanks to the agility of the cloud and the more widespread availability of API libraries that get developers up and running quickly, organizations are finding more agile and efficient ways to build or integrate conversational AI into their sales processes.
Natural language processing (NLP), speech recognition, and machine learning (ML) work together in the contact center to deliver an improved customer experience.
NLP is the technology that allows people to speak or write to a device and enables the device to understand what is being said. It also has improved tremendously with 97% accuracy in the last few years.
The speech recognition module, which is a subset of NLP, processes and rationalizes the spoken word while listening to the human voice. Over the years, it also has become highly accurate with an average of about 95%.
The final part of conversational AI, which is the ML module, identifies how to respond to the verbal input while working alongside the speech recognition module. These technologies are continually learning and improving as their algorithms process more data.
A large percentage of customer interactions involve the exchange of routine information for which responses can be automated (e.g., what are your hours, where is my order, when is payment due, is this in stock). For inquiries like these, speed and accuracy are paramount. Automating repetitive tasks in the contact center with conversational AI and chatbots improves outcomes on multiple levels. To name a few:
And for contact centers staffed by live agents, conversational AI can run in the background to compliment agents with options or solutions they may have missed. This can also automatically gauge agent performance (including call sentiment) and suggest alternate solutions.
Bringing conversational AI and chatbots to the contact center isn’t simple … but Five9 makes the process significantly faster and easier. These solutions are custom built for every customer, with the ability to integrate with existing legacy or current cloud apps, without requiring specialized AI personnel. There is also a library of apps and functions that can be dragged and dropped to develop Intelligent Virtual Agents for use in a contact center environment.
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Ellen DePodesta is a writer, editor, and content creator for Five9, working with the global marketing team to define and elevate the Five9 brand, voice, and content. Ellen has worked as a B2B marketer with agencies and as a contractor in Detroit, Chicago, Cincinnati, and Los Angeles.