Like all businesses, contact centers are under increasing pressure to do more with less. There is a need to reduce costs and possibly headcount, while at the same time contact volumes are increasing, customers’ problems are becoming ever more complex, and their expectations in terms of service are higher than ever.
Technology, in the form of AI, has long been thought to offer a solution to these challenges. The market for this technology is expected to grow from $4 billion to $15 billion by 2024.
In this article we are going to look at the capabilities of conversational AI, the new possibilities it opens up for CX, and the operational and business problems it helps solve.
Many possibilities of conversational AI
Conversational AI is a core contact center automation technology powered by recent advances in Natural Language Processing and associated technologies such as speech-to-text and text-to-speech. Cloud computing and storage enable huge amounts of data to be processed to perform functions like sentiment and intent analysis.
Therefore, it is possible to develop artificial agents that can understand natural language, interpret intentions, and respond in much the same way a human would – only faster, more accurately, and for a much lower cost per interaction.
Insights into customer behavior
With access to the company’s CRM and other databases, including customer histories, a Conversational AI system can instantly tease out much more insight into likely customer behavior, even at the level of individual customers, than a human agent can.
Personalized customer service
Deployed as chatbots, voice bots, or intelligent self-help systems, and using the full range of contact center channels including voice, messaging, chat, push notifications, and SMS, a Conversational AI can take personalized customer service to new levels.
Operational challenges Artificial Intelligence helps to solve
When it comes to customer service and the customer experience, conversational AI is being used in three different ways.
Generally in the guise of a chatbot or voice bot, the AI system interprets customer queries and tries to respond in the same way a human agent would. If it cannot, there is generally an option to failover to a live agent. This solves several operational challenges that help contact centers to meet their KPIs and ROI targets.
It provides 24/7 cover far more cheaply than rotating shifts of live agents ever could. It also enables high volumes of interactions, including peaks, to be managed consistently with every customer being answered almost immediately.
By efficiently managing the most common and simple customer interactions only the more complex ones make it through to the live agent teams. This means they can take more time to provide detailed, personalized responses to those customers that are having real difficulties.
The advantage is increased satisfaction from those customers as the company went out of its way to help them.
The second main use of conversational AI in the contact center is to support live agents by providing a more natural user interface to the tools, systems, and information that agents need to conduct customer interactions.
Gartner estimates that already 40% of users are primarily interacting with new applications via so-called conversational user interfaces. These work by monitoring the conversations – whether by voice or chat – the agent is having with a customer and intervening at appropriate times with relevant information, screens, or prompts.
This context-sensitive help means agents do not need to spend lots of time looking up the information themselves. It also vastly reduces hold time and the need to transfer customers from one agent to another because of a knowledge gap.
It also allows agents to find answers much more quickly which reduces the length of interactions and increases first contact resolution rates. These are all known to be huge indicators of customer satisfaction.
Most organizations these days store an incredible amount of customer data, including information on transactions, past interactions, and even transcripts of calls and chat sessions.
Only an AI is capable of interrogating such a data store to cross-reference and find links between pieces of information that give new insight into customer behavior. A conversational AI can do this by listening in on agent interactions – and using sentiment and keyword analysis to understand how a customer is reacting, or predict what a customer wants.
Results of deploying conversational AI
Companies that have deployed one or other of the technologies discussed above have reported impressive results. The use of AI to manage the more routine interactions – balance queries, password resets, and so on – has also been shown to cut costs by up to 30%.
Employee experience is also improved which leads to lower attrition rates. Training costs are slashed when human agents are assisted by Conversational AI.
The task of a contact center is ultimately to provide customers with information or resolutions to problems in a timely and effective manner. Whether that response comes via a chatbot, voice bot, some other self-service system, or an AI-assisted human agent does not matter so much to customers. The trick is to enable the agent – whether human or AI – to find the right data to answer the customer as quickly as possible. That is where the power of Conversational AI lies.