The future of contact centres – showing business how it’s done with AI
More than ever, businesses need to understand the complexities of individual transactions and customer behaviour over multiple contacts and channels. By pioneering AI software technology, contact centres have the opportunity to stand as industry leaders and reimagine every aspect of their business.
The data mining of old has been replaced with scope to look at every single customer and personalise your brand’s interaction with each of them. Harnessing the massive rise in unstructured data – around 2.5 quintillion bytes of data a day and rising – through AI will play a central role in helping reshape contact centres into customer experience centres.
It will offer contact centres levels of insight into customer needs which would drive increased profitability and efficiencies, greater customer satisfaction and create more valued and meaningful work.
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. 7’s customer engagement index 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.
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 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 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.
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.
AI will be a value add to human endeavour
If contact centres are going to capitalise on increasingly savvy and demanding customers, they need to adapt their structures and training pathways to help staff gain the necessary skills and navigate this new landscape.
Dimension Data found 75% of companies recognise customer service as a competitive differentiator. More than half relate improved customer experience to revenue growth. Three quarters view their contact centre as a key differentiator. For the future of contact centres, well-trained and engaged staff will be more important than ever.
AI has the potential to complete routine, mundane and predictable tasks, freeing up contact centre staff for the kind of meaningful, satisfying and valuable work to which humans are suited and aspire. Being an AI pioneer will allow contact centres to showcase AI’s capacity as a job disrupter not destroyer.
Jobs that traditionally rely on rules, repetition or data are more efficiently handled by AI algorithms. That is what AI products and machines do best – perform repetitive tasks, analyse huge data sets and handle routine cases. They will add enormous value by uncovering and acting on patterns which make customer and business predictions far more frequent and accurate.
In turn, this frees up time for humans to do what they do best – resolve ambiguous people issues, exercise judgment and instinct, and deal with dissatisfied customers.
This emerging symbiosis between humans and machines is unlocking the next wave of business transformation. Contact centres require both capabilities and provide a perfect case study for how an industry can reinvent itself using AI. If the benefits are to be realised, now is the time to reimagine processes to be more flexible, faster and adaptable to the behaviours, preferences and needs of customers and its workforce at any given time.
For contact centres the mindset is shifting from who is the cheapest to the smartest and most efficient. With only 9% of Australian businesses pioneering AI technology, this sector is in the enviable position of showcasing how an industry can embrace new technology and transform itself into a customer service centre.
As the use of digital channels increases along with customer expectations of an omnichannel experience, contact centres need to employ and retain motivated, engaged and skilled people.
Customer support roles will be reimagined as AI capabilities take over the transactional, repetitive and unfulfilling components of contact centre work. Instead, contact centre staff will become resolution experts and relationship builders.
The capacity of AI to draw extensive and comprehensive insights into customers will be matched by its scope to offer staff ongoing professional development, performance review and recognition.
Contact centres will be well equipped to address and upgrade performance in the areas of training, best practice, sales and service performance. The data enables every conversation to be heard, every day so agent training and performance issues can be spotted and solved in real time.
Expect change across the whole business
The impact of insights unlocked by AI will be immense. Contact centre workforce management (WFM) systems will integrate with others across the organisation to ensure customers’ needs are met.
Dimension Data says 75% of companies recognise service as a competitive differentiator and 57% relate improving customer experience levels to revenue growth. Three quarters of organisations view their contact centre as a key differentiator, meaning insights uncovered by AI will be invaluable to a company’s success.
Combined WFM systems and a centralised function to track and analyse the impact of different departments and processes could see a transactional contact centre reimagined as a customer experience centre that drives brand advocacy.
Contact centres, particularly those in regulated industries, are facing increasing regulatory complexity as well as enormous pressure to abide by industry standards and regulatory requirements.
From a compliance perspective, AI software will enable the contact centre to monitor and assess call guide adherence and compliance for every call.
For conduct risk, various measures will be built through phrase features, statistical measures and higher order calculations to identify potential issues. For example, it will be possible to identify an agent that is angry or offensive to customers from phrases they have used, or agents that are putting conversations on extended hold.
These observational insights will be extended into predictive solutions to address conduct risk issues. AI will act as an early warning system, allowing quicker intervention before an issue becomes systemic.
The “uberisation” of contact centres
The uptake of cloud and hybrid IT solutions will continue to increase as contact centres refine how they operate to meet changing customer needs.
Stemming from the move to cloud, there will be an increase in remote or offsite work solutions. It will be more common for people to log in from home than to work from a physical call centre.
This will see the “uberisation” of the workforce – a large pool of people available to work and a variable pricing structure. From there, if a contact centre has a dramatic increase in traffic, additional staff, working remotely, can be mobilised in a matter of minutes. The scope is there to increase charges to the customer or the salary for remote home-based call centre workers. It will mean the erlang model of call centre demand will be capable of being controlled in ways it never has before.
The rise of the small – or micro – call centre is also underway. Even for a small contact centre, globalisation means customers expect 24/7 support. Having two or three people spread around the world will become the norm. The advent of cloud-based call centre infrastructure also creates the potential to build a call centre quickly and without significant investment.
The road ahead
There is no denying that contact centres are entering a period of intense disruption. The rise of cloud-based infrastructure will see new forces enter the market and force existing operators to become more flexible.
For large established businesses, offering a frictionless multi-channel offering will not be something new but something expected by customers. So much so, customers won’t think about dealing with different channels within a company but simply with the company. Accurate, consistent and personalised interactions with customers will be essential.
AI software will be instrumental in helping contact centres reimagine their role from contact to resolution. It will free staff to work on meaningful, more complex and intuitive scenarios with customers as AI performs transactional and predictable tasks. The elevation of work in a contact centre has the potential to create a more stable workforce with improved corporate culture.
Ultimately, people still want to interact with other people. A contact centre is a fine example of that. Utilising AI will allow contact centres to focus less on mundane, transactional activities and more on its interactions with its customers. It will see far more opportunity for meaningful human interaction beneficial to customer and company.
 Unstructured data is information that doesn’t have a pre-defined data model or isn’t organised in a pre-defined manner.
 2017 Study into Artificial Intelligence by Australian Business, Daisee, 2018
 An erlang is a unit of telecommunications traffic measurement. It is used to describe the total traffic volume of one hour.