The prospect of offering customers intelligent self service anywhere, anytime, delivered by digital ‘agents’ that do not sleep, take vacation, perform inconsistently and require constant training, will excite any company executive pressurized to reduce costs.
As a result, significant investment and energy is pouring into technologies that aim to deliver a more human-like self service experience. Advancements in deep learning and machine learning capabilities, together with improvements in ‘sensing’ technologies, allow customers to more easily engage with digital agents using standard communication media – voice, movement, sight and touch. Plus, with improvements to natural language programming, virtual agents are getting better at interpreting underlying intent, and handling multiple languages and accents.
So does this then mean the end of assisted service? The answer is no. Here is why.
Much of the digital self service that is being successfully executed by chatbots are limited to level 0 and at best 1 tier call types – those that simply require the execution of an instruction or the provision of a specific answer to a specific question. Few if any businesses have managed to train their chatbots to handle complex query diagnostics in a consistent, compliant way – typically as a result of legacy systems and limited training and/or unstructured data.
And so while call volumes can and will be significantly reduced through the resolution of basic service queries using chat bots, queries that require more complex diagnostics and actions will for the forseeable future still be channeled to skilled contact centre agents. This is not only because clients require more contextual understanding of their problem, but they also tend to seek more human delivered empathy to the resulting stress that their query has created.
The challenge for contact centres globally, is how to deliver this level of query resolution and emotional support using young, typically under-skilled agents? The sheer cost of training agents to the level of expertise required to handle these calls, let alone to then ensure they have the emotional intelligence (EQ) to deal with the customer’s resulting distress, makes the cost of this level of service problematic.
So how then do contact centres overcome this issue? Recruiting more experience, costly agents is not the answer. What is needed is a way to recruit inexpensive resources who specialize in EQ, and then make them capable of handling the complex calls using some form of intelligent ‘expert’ call support. The question is, how?
The limitations of knowledge bases and scripting tools
Most contact centres start by investing in more comprehensive knowledge bases, only to find agents making limited use of the information available. This is because for agents to search, find, read, interpret and articulate the content captured in detailed documents while on a call is difficult – and keeping up with changing content exhausting.
This leads many to try out case base reasoning in the hope that they can offer agents more context-relevant support. And while some experience early success, most end up overwhelmed by the resulting maintenance effort that comes with an exploding information set.
The next step is typically to try capture the ideal call logic or flow into a decision tree scripting tool. And while the initial logic seems helpful, it quickly becomes apparent that no call is the same and more variables need to be considered. This explodes the tree logic, and soon makes it impossible to maintain.
As a result, contact centres either revert back to their original knowledge base, or live with generic scripts that few agents use.
However, with the arrival of data-driven logic, this is about to change!
Intelligence Augmentation. Artificial Intelligence for Agents
While most AI technologies look to replace agents, there is a category of technology called Intelligence Augmentation that looks to empower agents. Think of it as AI for Agents – offering them powerful call navigation that adjusts with the call flow and ensures they consistently ask the right questions, offer the right answers and take the right actions, even if they don’t know the content themselves.
This allows the agent to rather focus their entire energy on the customer experience.
Intelligent Augmentation (IA) technologies are driven off data, not decision tree logic, and therefore act like a GPS, adjusting dynamically to the call flow and guiding staff through all the optimal call routes so they can optimize the call measures while delivering a wow customer experience.
The result is that you can turn specialist agents into Super Agents, capable of answering any call like an expert. Intelligence Augmentation is therefore changing the face of the contact centre industry by allowing contact centres to recruit more cost effective resources with high levels of EQ to answer higher levels of call complexity at the levels of experts. This means, at a lower cost, delievering the following measures:
- Improved FCR
- Improved Customer Satisfaction and NPS
- Improved Quality
- Improved Business Insights
- Reduced Training
- Reduced AHT
Intelligence Augmentation offers contact centres the chance of competing with digital self service by offering clients a differentiated service; one that can cope with high complexity queries and offer a humane, empathetic customer experience.
Without it, agents will struggle to remain relevant in an every increasingly digitised world.