How AI-powered Contact Centres Change the Game

How AI-powered contact centres are changing the game

More than Hype: How AI-powered Contact Centres Change the Game

Digital transformation – or DX – has been a buzzword for nearly a decade with Conversational artificial intelligence (AI) playing a key role as businesses look to achieve streamlined 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 e-commerce 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 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 due to being 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 customer dissatisfaction.

With sentiment analysis, the programme is able to determine key phrases, trending topics and even emotional states based on the conversations the customer has with the agent.

Customer interaction analytics can also highlight any issues that require immediate attention.

It can pre-emptively discover ways to reduce customer churn, failed sales efforts, and repeat contact rates and ensure first contact resolution.

All this can directly influence enhancing the customer experience – and agent experience – which will ultimately improve overall satisfaction.

Employees are indeed a company’s greatest asset

Businesses will have to increasingly examine the entire customer experience (CX) journey from a holistic perspective.

AI should aim to empower customer journeys, marketing efforts, and employee training.

While new technologies can power contact centres, businesses must ensure that there is still a human presence on the backend to ensure solutions are being implemented to meet customers’ end goals.

This includes empowering agents to foster real-time customer care through empathy and authenticity.

According to Nate Brown, Chief Experience Officer at Officium Labs, building relationships with customers can only be achieved through mission-driven CX.

During his session on Conversations That Matters, a podcast for contact centre professionals, he said that business leaders have to “show and demonstrate an organisation’s values through CX and its employees, to communicate a brand identity authentically.

One cannot separate brand proposition, culture, employee experience, or customer experience – it’s a journey that should be continuously forming.”

 

 

The idea of achieving a fully AI-powered contact centre should not be thought of as the end goal.

Business leaders should see AI as a powerful tool to help them achieve exceptional CX on the front-end and superior DX on the backend.

Technology can reach its optimum potential when a human agent can act on the actionable insights it draws. It is only beneficial if it improves agent productivity and wellbeing, and it is simply only needed if it makes humans’ lives better.

More businesses need to see the process as a holistic one and combine all their efforts and investments to achieve an improved experience for all.

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About Ravi Saraogi 2 Articles
Ravi is the Co-founder & President-APAC, leads Sales, Delivery and Customer Success for Uniphore. He has vast experience in directing technology teams in initiatives spanning mobile theft security, wireless network development, and mobile learning applications. He’s known for his excellent analytic skills, dexterity in problem resolution, and proclivity for driving operational excellence.

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