Do We Need A Chatbot?

By Sameet Gupte, Servion Global Solutions

Ever since mobile messaging applications exploded onto the scene a few years ago, the hype around customer experience automation – using chatbots - has been gaining steady momentum. It has been garnering broader appeal, along with the growing reliance on digital conversations.

Popular messaging platforms such as WhatsApp, Facebook Messenger, Kik, and WeChat have gone way beyond the realm of casual communication. They are becoming a part of an omniscient service ecosystem for leading brands. Furthermore, virtual chat assistants are evolving to realistically and intuitively simulate live agents, right from initiating customer conversations to delivering information and taking actions on their behalf.

This has caused a spur in many forward-thinking businesses wanting to invest in conversational chat engines to offer proactive, personalized and seamless customer experience. In fact, Gartner predicts that “by 2019, 40% of enterprises will be actively using chatbots to facilitate business processes using natural-language interactions”.

Most CX practitioners across domains such as retail, banking and telecom are grappling with the realities of servicing customers in the era of messaging apps. They are ready to invest in people, process and technology to get it done, and to differentiate themselves from the competition.
There is no question as to whether customers of today are ready for the chatbot experience. After all, the top five most frequently used apps in the world are all messaging apps. A top research firm has reported that “Chatbots are expected to be the top consumer application for AI over the next five years”. Customers have become extremely used to the ease and seamlessness of digital conversations. And they are likely to settle for nothing less.

But, here is a question that many businesses fail to address in their quest to stand out.

Are chatbots ready for customers?
If businesses do not have complete clarity as to how customers can leverage new technologies to better engage with their brands, the investment may turn out to be a wild goose chase. Hence, before taking the plunge - it is crucial to pinpoint the type and nature of tasks that chatbots will be expected to perform. Is it more customer-facing compared to agent-facing or vice-versa? Can it help with troubleshooting? Will it help in searching and finding answers to FAQs? Should it be able to perform actions or transactions?

A customer’s journey has many checkpoints, and chatbot interactions are just one of them. For every part of the journey to be unified and seamless, businesses must correlate their chatbot systems to the rest of the service ecosystem. Being unable to smoothly move from one channel to another, without any loss of information or process redundancies, is often a deal-breaker for customers. Gone are the days when human-machine interaction are targeted merely at satiating the 24-7-365 support demands of customers looking for fast responses

Establishing trust has always been a critical part of any customer experience strategy. With the cognitive power of the chatbots, trust is more important than ever. They can unlock new potential for businesses to gain customer mindshare, but only when appropriate goals are set before they are ready to talk to customers.

For the tech-savvy, by the tech-friendly
Another key question is whether freshly-recruited customer care agents will be ready for tech-savvy customers. Even before the influx of these new technologies, no business has fast-tracked the time taken from recruiting agents to putting them into action. Most run through a training and skill enhancement program for them before they are deployed to interact with customers.

So, how can a chatbot be any different? The only difference is that there is no need for retraining - which happens in circumstances such as agent attrition. Bots can continue to be loaded with additional information through Machine Learning and Artificial Intelligence, and they will be able to handle a large variety of customer queries.

Therefore, it is very important to understand what is expected of the chatbot, and how it can be executed.

Making the experience less artificial and more intelligent
A chatbot can only be as good as it is supposed to be. It depends on the quantity and quality of data, and the technology stack, upon which they are built. Prior to deployment, vast amounts of data have to be collated from disparate systems. From reviewing past interactions and analyzing pre-configured queries to addressing domain-specific questions, customer data should be connected to the end experience.

If a 360-degree view of customers is unavailable, automated responses may not be on par with their expectations. Unfortunately, it can lead to a far more damaging experience than with traditional solutions.

The advantage of human-to-machine interaction via natural language processing is that it can drive immediate yet analytical responses rather than waiting for agents to access manual reports. But, the CRM data can only go that far in driving contextualized experience. Access to actionable intelligence such as behavior histories, sentiment analysis, channel preferences and journey patterns is the need of the hour to unleash its true power.

Bot technology is no longer the future. It is a clear and present scenario. As Natural Language Understanding (NLU) capabilities start to acquire more domain knowledge, chatbots and virtual assistants will ultimately reimagine the way conversations happen between brands and customers. Machines will strive to learn how people work, instead of the other way around.

However, amidst the hype and the happenstance, caution must be exercised before hopping on the proverbial bandwagon. Because the future growth of chatbots seems extremely promising. But, in order to grow revenue, reduce operational costs and spearhead long-lasting engagement through them, it is crucial to ask the question – are your chatbots ready for customers?