Delivering a fantastic customer experience today is a lot more complicated than it used to be. Consumers expect their favourite companies to deliver personalised and relevant experiences on all of their preferred channels. Your clients don’t have the patience to wait for you to answer their questions, and if you can’t make them feel special in every conversation, you risk losing their loyalty.
Artificial Intelligence has emerged as a popular solution to a variety of customer engagement problems. Around 83% of teams say that AI is one of the main tools they’re using to deliver better CX to customers. However, there’s more than one form of AI.
Conversational AI, which promises more immersive experiences for customers through personalised messaging, virtual assistants, and chatbots, promises to be a valuable opportunity for the teams that know how to leverage it correctly. Virtual assistants could deliver results to customers faster, while providing agents with more contextual information on a call. We spoke to leaders from Agara Labs, AudioCodes, and Inference Solutions to get their insights into this landscape.
Regarding the Modern Contact Centre and Conversational AI, What are the Biggest Challenges Faced Today?
Today’s contact centres are under more pressure than ever to deliver meaningful experiences in an environment where more consumers are embracing the digital world. Clients are searching for innovation from the brands they buy from, with 57% of consumers saying that “change” is crucial for better customer experience.
We asked our experts, in relation to the conversational AI and contact centre landscape, what are the biggest challenges currently faced?
Abhimanyu Singh, Co-Founder and CEO of Agara Labs:
Co-Founder and CEO for Agara Labs, Abhimanyu Singh told us that contact centres need to cater to customer expectations quickly today, while adhering to guidelines for public safety, and protecting employees. Since the pandemic, contact centres across various verticals are taking on a huge selection of new challenges.
Singh told us that the biggest challenges include: “A surge in call volumes, anxious customers searching for quick resolutions and reassurance, and repetitive queries, often resulting in extended wait-times and customer churn.”
At the same time, companies are also contending with a reduced workforce, lower operational efficiency, and dropping customer satisfaction levels as they struggle to handle an avalanche of requests. Business leaders are struggling to deal with staff requirements during the peaks of business demand too.
Andy Elliot, VP of Marketing and BD EMEA for AudioCodes:
The VP of Marketing and BD for EMEA at AudioCodes, Andy Elliot said that the biggest challenge for many contact centres right now, is adapting to the increasingly competitive modern world.
“This has two sides. Firstly, competition to recruit and retain skilled resources. By offloading transactional tasks to voice bots / voice AI technology, skilled agents can spend more time doing work that they value with customers. Secondly, contact centres are competing to provide ever higher service levels.”
Elliot told us that today’s consumers are more demanding, and less patient. Voice AI and conversational tools can accelerate a range of customer service tasks through automation, and deliver the speed that companies need. However, companies are still facing challenges in adopting the right technology. Issues with input quality, language understanding, accents, and cultural communication differences are common.
“Spoken language is a complicated area, so companies have to find voice AI solution providers that can connect their very specific use case with the right AI technology and work closely with them to get it right.”
Callan Schebella, CEO of Inference Solutions, which was recently acquired by Five9:
Callan Schebella said that the biggest barriers keeping many mid-sized and smaller organisations from deploying virtual agents and conversational AI in the contact centre are cost and complexity.
“Custom applications were needed for such tasks as natural language processing and text-to-speech, requiring big upfront spending along with ongoing maintenance. You needed to hire or contract with some serious technical expertise to get the job done, and that added greatly to the cost as well as the time commitment.”
Schebella told us that the perceived complexity means that many contact centres are still using outdated technology to provide self-service opportunities today, which creates a frustrating customer experience. Cost, and reliance on professional services were some of the top barriers to automation mentioned in a survey of IT decision makers recently.
What Needs to be Done to Address These Challenges?
While embracing new technology in the contact centre can be a challenge in itself, there’s a lot of opportunity out there for companies that are willing to evolve. The right conversational AI solutions could be the key to delivering a high quality of customer experience to end users. They could also be essential components in creating a more “differentiated” brand.
We asked our experts what they believed companies needed to do to address the current challenges they face with contact centre performance, and conversational AI.
[caption id="" align="alignright" width="204"] Abhimanyu Singh[/caption]
Abhimanyu Singh told us that as conversational AI continues to evolve at incredible speeds, it’s likely that consumers and businesses alike will benefit from this self-service over voice solution. Businesses need to drive adoption of conversational AI opportunities, increasing the potential quality of interactions between brands and customers.
“Voice AI has the capability to personalize customer interactions and provide zero wait time instant responses 24/7” according to Singh. However, organisations need to understand baselines and get clearer pictures of issues that might lead to poor experience over voice. Companies also need to identify high-velocity use cases which are suitable for automation, and map out conversational journeys, with insights into possible points of failure.




