The adoption of AI in the contact center has long been a topic of discussion. With spikes in call volume due to the COVID-19 virus and accompanying global pandemic , businesses are now looking to obtain a cost-efficient and intelligent way to address their customers’ most pressing issues. AI solutions are fueling traditional self-service approaches while also incorporating chat bots and live agent support, all in an effort to create a seamless journey for customers while providing them with the support and agility they need.
AI is redefining the customer experience and organizations are investing in implementations that support deeper uses for AI and NLP to enhance customer service and reduce costs. There are three key factors to consider when planning for AI that will impact your contact center; knowing how to leverage your data, how to best understand your customer’s needs, and how to maximize them together to make the most impact.Read More
Google’s Dialogflow environment is a great place to build natural-language understanding applications that automate both text-based (chatbot) and voice-based interactions. All of the voice-enabled AI environments in wide use today (Google’s Dialogflow, IBM’s Watson Assistant and Amazon’s Lex are the big 3) enable voice communications by going through a 3-step process, where spoken input is first transcribed to text by a speech-to-text engine (STT), then given to a bot for analysis, and finally then sent through a text-to-speech (TTS) engine to produce audio back to the user.Read More
Automating parts of your Contact Center tasks are at the top of the list when considering how to transform your business. AI fueled self-service options help to improve internal productivity, the customer experience and cost efficiency.
A primary issue when integrating multiple channels and services in your Contact Center is creating a seamless, cohesive solution. Utilizing the services of expert, advanced IT partners is strongly suggested as they are able to help you create an extensive, all-in-one infrastructure built from any number of niche solutions.
Contact centers of all sizes are challenged from many different angles today. Customers call in expecting immediate service and engagement for their issues. Contact center agents want support from higher-ups in managing their call queues and getting to critical customer complaints promptly. Incorporating artificial intelligence customer experience solutions can go a long way toward relieving pain points experienced by both groups.
There is no doubt about it – contact centers must streamline their operations to remain competitive in the modern business landscape. Artificial intelligence is able to contribute to this effort in ways that a strictly human team simply cannot. Many contact centers that are falling behind with the technology are also falling behind in performance. Let’s take a look at some of the ways that artificial intelligence can be used in the modern contact center.
Keeping a call-center running smoothly can be challenging for even the largest enterprises. Customers call in expecting immediate service and engagement for their issues. Contact center agents want support from higher-ups in managing their call queues and getting to critical customer complaints promptly. Incorporating artificial intelligence customer experience solutions can go a long way toward relieving pain points experienced by both groups.
Automation has always been part of the contact center world – and it is getting even bigger with the addition of chatbots. While they are in a basic stage now, as is with all things related to AI, chatbots are getting better the more we use them. Machine learning is different than human learning – it’s only as good as the data we feed it. Chatbots lack natural cognition to challenge inputs such as 2+2 = 5. But over time, patterns are established that make chatbots “intelligent” – smart enough to take on more and more complicated tasks.
Despite the fact that Artificial Intelligence (AI) has become a household term over the last few years, studies show that there is still a widespread sense of trepidation around the topic. According to a report published by Forbes last month, when consumers were given a list of popular AI services, 41.5% could not give an example of AI that they could trust. Significantly, in verticals that traditionally have the human touch such as financial planning or healthcare, over half of customers say that they do not trust AI to help them out.