The best possible experience for customers should be almost unnoticeable. It should feel natural, intuitive and effortless. It also needs to be easy, proactive and not drag. From the customer’s point of view, it should be targeted and customised, so that it feels personalised just for them. All this must be consistently replicated so that the customer knows what to expect no matter what touchpoint they use. Of course, this must also all apply if the customer wants to reverse their original transaction by returning the item or requesting a refund.
To achieve all this, an interaction needs to be intelligent, well informed and relevant, based not only on the context of everything that surrounds it, but particularly in the moment that matters most to the customer. One of the biggest challenges in delivering this is being able to collect, collate, analyse, and interpret the myriad data these interactions generate in real time so that it can be used meaningfully.
This is where AI comes in. When AI is used to infuse knowledge and insights throughout every customer journey, it helps ensure intelligent decisions and inform next best actions. This not only benefits customers, but also the employees serving those customers by supporting and augmenting the work they do. With the increase in online and digital interactions, the only human interaction a customer may have with an organisation may be through their contact centre, making each agent an ambassador for the brand – so the agents need to be enabled to do their job well.
This can be achieved in a number of ways. Firstly, AI behavioural pairing can match customers and employees in a way that plays to their strengths and personalities, making the most of what they’re good at. Secondly, by providing employees with digital co-workers, the agents can focus on the customer, on the relationship and the interpersonal elements. Because customers most definitely notice when agents are distracted – even slightly – by some other pending action. So, while agents are focused on the customer, their digital assistant can do things like analyse the interaction, surface hidden or unseen issues, suggest next best actions and take real-time corrective actions. In addition, virtual assistants can handle a lot of the manual, time consuming activities agents undertake with every interaction, such as automatically inserting transcriptions into CRM systems, saving employees up to 65% in after-contact work activities.
Thirdly, AI can support work-from-home agents in numerous ways. It can help determine how distracted an agent is getting and provide feedback whilst affecting agent selection. It can detect a volume change in background noise – for example when the kids return from school - and automatically switch the agent over to non-audio work if necessary, or it can change the mode of the agent to digital if the agent’s broadband is not performing well.
And of course, after the interaction, AI and machine learning can be used to mine all interactions for critical business intelligence that can improve operations internally and externally for both customers and employees alike, helping ensure a continuous improvement cycle.
When customers are connected with likeminded employees, and when those employees are focused on customers and everything that matters to them, more successful interactions are driven. If you want measurable increases in enterprise productivity and profitability, and long-lasting value, there’s an AI for that.