What contact centres look like in the age of AI – Part 1, technology

 

The contact centre industry is entering a period of intense disruption and AI software will be instrumental in contact centres reimagining their role. Digital convenience is driving consumers to interact with businesses on a host of channels with much higher customer service expectations.

Meanwhile, the sector is still grappling with longstanding issues that impact profitability and business efficiencies, compliance and regulatory requirements, customer satisfaction and agent retention.

Contrary to Hollywood depictions of AI, contact centres are at the forefront of how AI based solutions can augment humans not replace them. It can be targeted to specific return on investment goals to reduce costs, increase revenue, improve customer experience and reduce risk.

It will harness the 2.5 quintillion bytes of unstructured data created every day (and rising) and help reshape contact centres into whole new customer experience centres. In this two-part series, we look at how.

A seamless, individual customer experience

Digital convenience is a huge motivator for consumers. Companies like Google, Apple, Facebook and Amazon have set the bar in terms of an integrated customer experience that is providing individual customer service across multiple channels. People now expect to be able to move seamlessly between all of them.

While customers’ expectations are high, their brand/company loyalty is not. [24]7’s customer engagement index[2] found that anger at poor service would see 45% of customers take their business to a competitor within one day if they matched on price and product. And 80% would do so within a week.

[24]7 found nine out of 10 consumers will use three channels to resolve an issue during one customer service journey. While customers will cross channels if they can’t complete a task on their first channel of choice, they only want to engage through the channels they want to use.

Understanding the intricacies of individual transactions, as well as the context of customer behaviour over multiple contacts and channels, is paramount. Being cognisant of your customers’ issues, moulding their experiences and creating meaningful engagement creates value for customer and company.

AI will provide immediate feedback, systematically and quantitatively, from every interaction without creating any points of friction or customer effort (like a survey for instance) at an individual customer level or aggregated to the level of your choice. It links all channels to create an individual yet seamless customer experience.

Multiple channels for customer contact is the new norm

Customers are increasingly demanding choice and control while expecting a business to anticipate their needs without invading their privacy. While digital channels are becoming the interaction channel of choice for customers, Dimension Data says around 40% of contact centres don’t have data analysis tools, despite analytics being voted the top factor to change the shape of the industry in the next five years.

Despite customers reporting the phone as the most frustrating contact option, Fifth Quadrant’s 2018 industry study[3] found its dominance has not declined as quickly as expected. But a shift is underway. In 2017, almost half contact centre agents (48%) were using phone and digital channels.

A 2015 industry report[4] by Dimension Data predicted more than 50% of organisations would manage a multichannel contact centre in the immediate future, featuring at least eight different forms of contact methods. Seven of these are digital and the mix is malleable and growing.

Moving from masses of data to meaningful insights

Collecting data is certainly not new to contact centres, with businesses sitting on masses of raw data. Typically, only about 2-4% of recorded calls are monitored for sales information and customer satisfaction, often a long time after they were recorded. Almost none of this data is analysed or used to enhance business performance, customer experience or improve processes.

Dimension Data says 52% of contact centres don’t share customer intelligence outside the contact centre. Around 86% of social media and 79% of web chat operations aren’t automating their planning, tracking, and monitoring adherence. More than half (57.2%) of contact centres managing email still have no workforce management technology solutions in place to help maximise productivity levels.

Companies are making huge investments to monitor for compliance, customer experience and training. But these tools tend to be cumbersome and mechanistic, delivering metrics not meaning.

AI software translates context and meaning, so it captures insights on compliance, employee performance, and customer experience. It allows a contact centre to not just record 100% of calls, social media interaction, video and chat feeds, but allows us to translate, interpret and act on them.

But over and above the ability to transcribe each and every call made between customers and agents, broad and deep levels of information and insight are drawn from every call and placed into a structured data environment. This can then be used by a range of stakeholders in the organisation to guide business decisions.

Augmenting intelligence

While AI can augment human behaviour, there is still a very real bias for humans to want to talk to other humans. Contact centres are still an important competitive point of difference for business, with success gauged on customer experience outcomes. A key challenge is maintaining integration levels across all channels while providing consistent service.

Contact centres are experiencing an offloading of transactional activities into alternate channels. Calls are now more complex and add more value for the customer and the business.

That means AI will move existing analysis techniques of those calls to the next level. It will map word and concept level relationships within conversations and then deduce business specific intelligence and insights

Speech analytics will measure everything from the reason the person called to their mood at any stage of the call or contact. AI can link key words and phrases and carry out semantic matching (which matches phrases on their similarity of meaning).

It will enable contact centres to improve the customer experience, monitor contact centre quality, reduce operational costs and gain critical business insights.

Businesses will be able to trial different call guides to see which one is most effective. AI will identify patterns across multiple calls, giving management a heads up of an issue before it takes hold.

Studies show a dramatic increase (up to 34 points) in net promoter score (NPS) when customers speak with a contact centre agent who’s at a similar life stage and opposite gender. AI will measure education level, clarity, interruptions and talking over each other. It will also measure the sentiment of both the agent and caller in language and time/conversation pauses as well as talking speed.

Critically, it will do this seamlessly from the conversation, not through set questions or a survey. Today’s data, informs tomorrow’s decisions.


[1] Unstructured data is information that doesn’t have a pre-defined data model or isn’t organised in a pre-defined manner.

[2] https://info.247.ai/WS-NA-CE-Index-WS.html

[3] https://www.fifthquadrant.com.au/contact-centre-benchmark-2017

[4] https://www.dimensiondata.com/en/insights

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