Organisations everywhere are embarking on digital customer experience (CX) initiatives in an effort to build loyalty and increase sales. Yet all too often these initiatives ignore the contact centre, creating expensive silos that damage the customer experience and set your strategy up for failure. A successful digital CX strategy goes beyond what your customers are experiencing online to include what’s happening in your contact centre.
Contact centres require a great deal of investment – from recruiting and training staff to putting the necessary tools in experience for customplace for agents. A chatbot can help you maximise on those investments while creating a positive omnichannel ers.
Chatbots and virtual agents have become an essential tool for providing 24/7 self-service to digital customers. Available on websites, messaging apps like Facebook Messenger and WeChat, WhatsApp and even smart speakers like Amazon’s Alexa and Google Home, chatbots are helping organisations deal with the growing number of customer contact channels. Today’s customers don’t always expect to engage with a live agent for information and support, and these automated solutions are proven to improve the customer experience and customer satisfaction scores.
Yet many organisations make the mistake of only utilising chatbot technology to create a self-service experience for customers, missing out on the added benefits of using these solutions in the contact centre. Chatbots and virtual agents enable organisations to maximise on contact centre investments by instantly providing agents with information to assist callers, reducing average call handling times, and increasing first contact resolution. Training time for live agents is drastically reduced with these tools, and you build confidence with customers by assuring consistent communication from all agents. When agents know they always have the information they need at their fingertips, their focus moves from trying to retain knowledge to building better relationships with customers.
A chatbot in your contact centre works essentially the same way as a chatbot on your website, except the users are your agents instead of your customers. The tool understands questions asked in natural language, as well common abbreviations used by your contact centre, and can guide agents through processes and forms step-by-step as they assist customers. By giving all staff easy access to the same level of knowledge regardless of experience, anyone from support teams to trainers and coaches can step in to answer customer questions with confidence at peak or busy times.
A chatbot also provides your contact centre – and your organisation as a whole – with a better understanding of your customers. When your chatbot is integrated with business intelligence tools, your entire customer experience sees the benefits of having better insights for predictive analytics and next best action initiatives.
Centralise knowledge management control – There are huge benefits to using conversational platforms within the contact centre and for customer self-service, but this requires a solid foundation in knowledge management. Chatbots and virtual agents can only give accurate responses if they are backed by a knowledgebase with accurate content.
Your approach to knowledge management needs an orchestration platform – a tool that brings together all of your organisation’s information sources so that you can centrally control your service experience across contact channels. This platform should allow integration with your existing content sources – other knowledge management systems, customer relationship management tools, information feeds, etc. – so you can easily pull the content you need from those systems, avoiding the unnecessary cost and hassle of recreating everything in another place.
Integrate chatbots and live agents – Offering customers an easy way to self-serve through a chatbot or virtual agent frees up your contact centre to assist customers who need, or want, to speak with a real person. Integrating that self-service tool with human-assisted channels like live chat or callback allows customers to be seamlessly passed from virtual to real agent, with a complete history of their conversation being passed with them. There’s no need for customers to deal with the annoyance of repeating their question or issue, and your live agents can pick up right where the chatbot left off.
In the contact centre, this integration needs to include options for agents to provide real-time feedback and suggestions on chatbot content that is inaccurate, incomplete, or out-of-date. The feedback loop should be linked to the orchestration platform so that the comments and suggestions can be easily reviewed and used to make content updates. This enables contact centre agents to act as knowledge experts and help keep the chatbot content accurate.
The conversational platform should enable you to deliver assistance to agents providing customer care across all the channels your contact centre supports – phone, email, social media, support communities, discussion forms, etc. It should also provide options for agents to use voice and for the tool to be deployed on the IVR (interactive voice response) channel as well for a seamless customer experience.
Combine artificial intelligence and human input – The foundations of successful chatbots lie in the control of the response given. A hybrid approach of machine learning and human curation of content allows the chatbot to continually improve based on the way it is being used while also enabling companies to maintain control over the reliability of responses. Combining human curation with machine learning creates dependable self-service solutions and gives organisations the control they need to comply with industry standards and regulations.
Your contact centre is a rich source of data that can be used to train your chatbot. Analysing live chat and call transcripts is a great starting point for developing your conversational tool. With the use of agent feedback loops, your contact centre team becomes chatbot coaches – the knowledge experts helping to keep the chatbot performing well. It's important for your chatbot to learn from interactions with your agents and customers, but it’s equally important that the solution you choose allows human moderation of the machine learning component. It’s simply not realistic to implement a customer service chatbot – public-facing or in your contact centre – and then expect it to improve and remain reliable all on its own. Bringing together human input, such as agent feedback loops and user surveys, with semantic matching, statistical self learning, and neural networks creates an efficient and predictable solution for your contact centre and your customers. The orchestration platform should allow your organisation to continuously fine-tune the machine learning and human curation components.