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AI-powered contact centres are game changers.
Truth or Hype? Ravi Saraogi, Co-founder and President of Uniphore APAC shares how Conversational Artificial intelligence (AI) is playing a key role as businesses look to streamline operations while delivering new and transformative experiences Conversational AI helps contact centres in many forms – from powering intelligent virtual assistants (IVAs), analysing calls in real-time to summarising calls for agents. AI-powered contact centres have long been a reality, especially for the financial, telecommunications, business process outsourcing (BPO), and ecommerce industries during the pandemic. While we have seen an extreme acceleration of AI adoption in the past year alone, we will continue to see new and exciting applications being adopted that will truly change the enterprise. AI is part of a much bigger picture; it is meant to “power” the entire front and backend operations and augment agent capabilities for improved productivity and employee experience. Understanding AI-driven capabilities before and after calls
According to key findings from a COVID-era survey, there is still a strong preference from Australian consumers (54.5%) to speak to a live agent when reaching a company’s call centre. Despite this, many may not know how AI-driven capabilities can deliver in-call alerts (real-time insights), guidance and real-time automation of repetitive agent tasks all while the agent is being co-piloted with AI. For example, in the recent “2021 CX Divide” report, 39% of Australian telco customers suffered longer than expected wait times, and 42% had to repeat their issue several times as their call was transferred from one agent to another. AI-driven features can play a pivotal role in improving customer service. For every query, complaint and call that comes in daily, contact centres collect an abundance of
real-world data and live training. This allows AI led tech to learn about customers more intimately, making sense of what a customer prefers, identify patterns, uncover hidden relations, and systematise customer data – before a call even starts. All these go into making the entire customer request comprehensible for human agents to know when to take timely action. AI also drives real-time automation of repetitive agent tasks including after-call work summarisation, call disposition, promises management and more. By leveraging AI and natural language processing (NLP), human agents can reduce time and effort spent on summaries for reporting, and obtain granular insights on calls with increased accuracy. Customer interaction analytics is the new digital oil
Millions of hours of customer conversations are recorded year after year to fulfil quality standards, training demands, and compliance objectives by contact centres. All this data is hardly ever analysed or even drawn upon for humans to take action, which is why many do not realise its powerful potential. If 100% of the data from calls, emails, chat transcripts, social media and other customer interactions were turned into valuable information, imagine the infinite value and customer service proposition that businesses can unleash. Recorded data can be deciphered with the use of customer interaction analytics. By analysing conversational data after every interaction, businesses can discover root causes that lead to
