The essential preparation for chatbots
We’ve evolved with our clients over the years; as the face of the contact centre has changed, so have we. What was once a call centre is now a multi-channel contact centre, dealing with enquiries via the customer channel of choice: phone, webchat, email and whitemail. Chatbots are a natural next step.
As service communications specialists, we spend our days talking to clients and experiencing their customer service functions, whether that’s across large and often multiple contact centres – or smaller teams. And you can’t deny that artificial intelligence is a hot topic and tells a tempting story: it’ll save you money on overheads and repeat contact, it’ll help you get better information/data on your customers, it’ll be quick and easy for your customers etc. That said, a contact centre or customer service function always needs to strike the balance between operational efficiency and good customer experience.
Implementing chatbots
AI is still in its infancy within contact centres, certainly in the UK. Some companies are already embracing innovation and implementing this new capability but many others are only just starting to evaluate how they could integrate it.
When speaking to clients or listening to specialists talking about the world of AI, virtual assistants or chatbots, the focus tends to be on the functionality and efficiencies that these tools can deliver. There’s no denying the benefits of AI, but I still question, ‘at what cost to the brand and customer experience?’
As with any new approach to customer service e.g. webchat, it’s still vital for companies to be clear from the outset on the customer experience of a bot and how you want to ‘sound’. As we work with more and more clients on exploring what chatbots could mean for them and how we can prepare, we talk about two essential ingredients:
Ingredient 1: Tone of Voice
Speaking to your customers in a clear, consistent tone of voice is no different when you’re thinking about AI. There are constant developments in Natural Language understanding (NLU) – the way machines can process and interpret customers’ interactions and then react accordingly. But, as with any touchpoint, you still need to make sure that as much as the bot is reacting and responding to customer requirements, there’s a reflection of your true brand promise through its ‘voice’ – text, speech, images and video.
It’s important to look at the brand persona and language they use to make sure they still replicate a human, warm and empathetic tone with customers, as well as any other distinguishing features that set a company apart from its competitors.
Our core competency is how companies talk to their customers through service channels. As part of our process, we look not only at what the ‘brand’ or the organisation’s persona is, but we’re also focussed on the customers or end users. Our key aim is to make sure that whatever language we use a) resonates with them and b) delivers the right outcomes for both company and customer.
Ingredient 2: Knowledge Management
One question that came up at the recent ‘AI in Customer Engagement’ forum was:
‘Will there be any circumstances where AI will deliver the opposite i.e. negative outcomes?’
The answer was ‘Yes, if it’s not implemented properly’. For any bot to be effective, it must understand your customers’ needs as well as what help or outcomes are available to them.
This question led me to a realisation of something that’s true of today; Whether it’s training agents directly or giving them the tools to provide the best customer experience possible, you need to have a good way for customer-facing staff (or interfaces) to easily have all the right information ready for the customer. You need well-structured and accessible knowledge management.
As a customer, we all face the metaphorical wall of ‘No’ or ‘I’m afraid you can’t’ or ‘Sorry, I can’t help you’. Sometimes it’s to do with agent capability and sometimes it’s to do with what information is available across an organisation.
We often find, in the work that we do, that there’s a lack of centralised information or data that clearly outlines:
a) what the company can do to help a customer
b) what a customer can do themselves
This applies both to providing the best assistance to a specific enquiry as well as proactively offering ideas or information to offer service above and beyond.
A bot or virtual assistant is only as good as the knowledge and tools that you give it, so the best way to prepare for AI is to consolidate and craft your base of process, knowledge and customer insight. As organisations use knowledge in different ways, there are different systems and approaches to how you can organise your data. Investing in this sort of taxonomy from the outset will mean you’ve mapped out the complexities of your organisation into something AI-digestible.
Our knowledge management projects empower your business to give customers the answers they need, quickly and clearly, leading to higher satisfaction scores. Read more about our results and Knowledge Management approach, or get in touch for a chat about how we can help you get AI-ready.
