As a customer, resolving issues over the phone can be a painful and laborious process, and that’s if you manage to speak to someone in the first instance. This could be the reason why so many of us are turning to digital self-service channels to look for answers, and why the proportion of traffic going through ‘non-voice’ digital channels is growing exponentially.
Businesses undoubtedly value self-service as part of their care-mix. Online tools such as virtual agents, help guides, forums and even social channels such as Twitter, reduce demand on their more expensive contact centres. However, many self-service technologies simply aren’t the silver bullet that many perceive them to be, at least not until businesses start to realise that their care operations can’t live in silos.
What many don’t realise is that a large percentage of customers find self-service tools frustrating. In fact, having tried and failed to resolve an issue through a self-service tool, many customers find themselves having to call the contact centre. This is known as "fall-back" traffic. It can account for up to 20 per cent of call volume coming into a contact centre and up to 10 per cent of the total care budget. Factor in the poor customer experience and the return on investment for many self-service deployments starts to fall away fast.
That’s why the industry needs to evolve.
Digital self-service channels, as well as tools that automate care operations, are undoubtedly the future; but as businesses frantically look to explore more and more inventive ways of supporting their customers, many are forgetting the need for consistency.
There are some very simple explanations why so many of today’s self-service offerings, despite their good intentions, fail to deliver on their promise:
– Poor discoverability – effective and accurate help content is often too hard for customers to find, hidden away in labyrinths of digital menus and gateways.
– Information gap – while the industry likes to talk about omni-channel, the reality is that most web-based channels don’t have access to the same knowledge bases as contact centre agents. Often the answer to a question just doesn’t exist online.
– Digital channels are deemed impersonal – simply put, customers miss the two-way nature of a conversation. While an agent has more leeway to move ‘off-script’ and affect an upgrade or rebate, online care is often a pre-scripted process that will end only one way.
– Immediacy – the immediate nature of online communications means that online interactions are subject to much higher customer expectations. If there is a delay in the resolution process, the customer will look to resolve the issue elsewhere.
Fortunately these issues are all correctable and by using the one thing that the customer care industry isn’t short of – data.
Customer care is data rich, but information poor. The data is noisy, unstructured and difficult to make sense of. But making sense of this data is exactly what businesses need to do in order to realise the potential of their self-service investments.
Self-service gets smart
What if this data could be better used? What if care channels (from the contact centre to online tools) actively used each other’s data to learn from one another in a way that ensured a consistent experience?
Over the last two years several key technologies have matured, making it possible to achieve this and deliver a self-service experience that’s as reliable, and pleasurable, as talking to a human agent.
Where web-based self-service tools were historically just knowledge repositories, research into machine learning, sentiment analysis and natural language processing is reinventing the market for self-service.
For example, this year we will see the emergence of a new generation of virtual agent; one that actively learns from live agents and the terabytes of data that pass through today’s contact centres. Rather than sitting in a silo away from the contact centre, the next generation of self-service technology actively benefits from it to provide contextual, relevant responses instantly and with the same accuracy as a live agent.
Like a human agent, this next generation of virtual agent learns through experience. Monitoring how live agents in the contact centre are diagnosing and solving customer problems, it uses machine learning to grow in confidence and understand the best way to manage customer interactions online.
We’re already building this next generation of technology; tomorrow’s digital self-service experience won’t be impersonal or inaccurate. Tomorrow’s virtual agent will have the knowledge of thousands of live agents and be able to make decisions based on experience and data in a fraction of a second. At this point the true promise of self-service, meeting cost efficiencies without damaging the customer experience, will finally be realised.
