Companies and their customers share a love-hate relationship with Interactive Voice Response (IVR) systems at the heart of most customer contact centres.
The phone-based support technology allows companies to collect, virtually queue and deposit callers into categories depending on their issues.
But, as the pandemic starkly revealed, when people shifted their lives online, IVR platforms were exposed as making life easier for the companies using them rather than their customers. Call centres were jammed with interminable wait times and dissatisfied customers, who inevitably voted with their feet and sought alternatives.
IVRs herd customers into pens by having the customer self-categorise their issue, which places them into a queue waiting for human agents to solve problems rather than dealing with the problems directly in real-time. In most cases, more modern IVRs only offer limited integrations for data collection or back-end execution so must still route complex issues to humans.
The problem has been exacerbated by contact centre employees having limited bandwidth, especially during high-volume periods, meaning the higher the call backlog, the more likely a customer is placed on hold. As contact centre agents are inundated with active customer requests, there isn’t time for them to quickly react to changes in procedures, policies and compliance requirements, or to master information on new products or how to troubleshoot. The net result is churn as frazzled employees seek greener pastures.
The Australian Customer Experience Professionals Association (ACXPA) said the average attrition for a call centre staff in Australia is 26% and only 69% of frontline agents are still in post after 12 months. Companies end up spending valuable resources finding, hiring and training employees, knowing full well that most will never be around long enough to fully master their systems, policies or products.
Building an intelligent contact centre
Forward-thinking companies are now adopting Conversational artificial intelligence (AI)-powered virtual agents to provide first-line resolution and support for customers, and to augment human employees through AI and back-end automation. Gartner says that by 2026, Conversational AI deployments within contact centres will reduce agent labour costs by US$80 billion, globally. It projects that by the same year, one in ten agent interactions will be automated, an increase from an estimated 1.6% of interactions today that are automated using AI.
Using open conversations with dynamic information extraction, customers can work directly with a Conversational AI system to find answers to even the most complex problems in real-time – which would defeat IVRs. Conversational AI can learn and master a company’s business processes in a variety of tasks before even fielding its first customer query. It can also contextually comprehend the actual meaning of a query and use that understanding to prepare its response.
Unlike IVR systems, it can use neural network algorithms to detect intent. For example, if a bank customer called to say they wanted to go paperless but had lost their credit card in Sydney and were worried about fraudulent transactions, Conversational AI would triage and determine that fraudulent transactions was the most important element of the conversation, reissuing a new card the second-most important element and going paperless is the least important element.
Utilising a Conversational AI front end in call centres can resolve anywhere from 30-60% of the incoming calls immediately compared to how calls are handled by IVRs.
Creating the human-AI contact centre team
There’s a critical business reason for building Conversational AI solutions that work alongside, rather than replace, humans: AI is no substitute for human ingenuity. Conversational AI supports agents in three ways: by providing real-time AI-powered recommendations during escalated calls; assisting agents with the right information; and enhancing analytics with suggested transaction improvements. AI also helps new agents become more proficient.
Enterprises that have adopted Conversational AI are already creating new team roles. Similar to how the advent of social media resulted in new marketing roles, the intelligent contact centre will necessitate several new roles that don’t exist today.
We’ll see team members, who understand customer journeys, working with business analysts who look after the virtual agent application interfaces. Supervisors will also be needed to manage virtual agent performance and handle agent-to-human escalations. Other team members may be prioritising new use cases.
As the number of use cases grows, the business case to deploy Conversational AI in contact centres just gets stronger. And if competitors are already utilising Conversational AI in their own call centres, ignoring this trend could see a company losing customers and agents seeking better experiences.
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