Customer Service Messaging: An Ideal Channel for Automating using a Chatbot
Customer Service Messaging Channels: Opening a Path for Automation
Considering most of us use messaging to communicate with our friends and family on a daily basis, it shouldn’t be a surprise that messaging has been appointed as the new preferred channel of engagement for resolving customer service issues. Businesses that wish to remain competitive and offer exceptional service experiences will be forced to offer messaging in their suite of tools made available for customers to use when in need of service.
Over the last 5 years, we have witnessed phenomenal growth in the rise of messaging apps – driven in no small part by millennials and the soaring popularity of chat apps like WhatsApp, Facebook Messenger, and other well-known chat apps. Research shows that mobile messaging apps have overtaken social networks to become the dominant platforms on phones. This phenomenon is being driven in no small part because these apps have become mini-ecosystems in themselves that include browsing, shopping, and ordering all available within the messaging app itself.
Ted Livingston of Kik predicts,
“Chat apps will come to be thought of as the new browsers; bots will be the new websites. This is the beginning of a new Internet.”
To take it one step further, a recent Forbes article author equated Chat on mobile devices to what email has been to the computer – the primary way we communicate. Put another way, messaging apps are the killer app on mobile in the same way that email was the killer app on the desktop.
Besides the popularity of messaging apps and the widespread adoption of them as a convenient way to engage, an essential advantage of message-based engagement is that it lends itself to automation via conversational AI. So for customer service organizations, shifting customers to message- or text-based channels opens the door to more self-service and digital assistant models. Compared with traditional customer support engagement channels like the phone, email, and contact forms, text-based messaging is more easily automated using digital assistants, thereby alleviating costly agent time on responding to routine requests.
A recent piece of research we conducted revealed just how hard it is for customer support to respond to incoming emails or contact form queries, with almost half of the companies we surveyed not responding at all. But what if these customers were shifted to a digital messaging channel? Then a digital assistant can automate a good portion of inquiries while handing off to live agents to tackle the more unique or complex queries.
Why Customer Service Messaging is Important
Given its popularity, it’s no wonder that messaging has become the #1 way in which millennials want to communicate with customer service. A survey by OpenMarket found that texting is the #1 preferred channel for notifications from businesses and that 83% of millennials would prefer to text than to call a 1-800 number. Here are some recent data on the popularity of messaging apps like Facebook messenger and WhatsApp that make these channels important for customer-facing businesses as they review their digital engagement strategy.
Messaging channels are core to today’s AI customer service automation driven by conversational AI. They can bring a big win for businesses both on the cost and satisfaction front – changing how they staff for peak times and facilitates the elimination of long wait times and queues altogether.
Because customer service messaging works across all modern digital channels, it is the ideal medium through which to bring these channels together for a frictionless customer service experience. Messaging works on web (webchat), mobile, social media, and on digital voice assistants like Siri and Cortana. It can be made to work with older technologies like email (which is a form of messaging but more cluttered!) or on newer technologies like home voice-activated devices (Amazon Echo and Google Home) that convert voice commands to messages.
These technologies can even be used in your car. For example, you can start a conversation in the morning on your Amazon Echo device, check-in later on web chat and follow up that night with a message in your mobile app (in-app message). In this scenario, your history follows you from channel to channel, creating a seamless experience for you and more intel for the businesses solving your problems.
Check out this post on customer service chatbot use cases as well.
The Customer & Business Benefits of Using a Digital Assistant with Messaging Channels
We have taken this concept of messaging as a channel as a critical way for enterprises to provide better support for customers, when they want it and in a manner and pace that fits their lifestyle. Customers can look forward to a world with no more queueing, transferring, dropped calls (or dropped live chat sessions) and without continually having to repeat themselves.
But besides the clear benefits of messaging as a customer channel of communication, the business can benefit hugely by adopting messaging for customer support. Why? Because interacting with a customer on a messaging channel lends itself to automation using AI. It is easier for a digital assistant to understand natural language and a customer’s intent and extract the entities in short text messages than in long emails or phone messages. So the digital assistant gets to the nub of the customer inquiry easily and can be trained to respond, (this customer support case study highlights the business advantages when AI is used).
Think of some common customer service queries such as “where’s my order?”, “can I check my account”, “can you send me the instruction docs”, “I want to renew my policy”, etc. A chatbot, powered by AI, can be trained to respond to many of these types of text-based requests and respond immediately and out of hours, and a customer retention bot can be trained to keep customers from stopping services. This is instrumental in taking pressure off busy contact centers so that human workers can deal with more complex customer issues or with issues that are escalated to them from the chatbot. This is what we refer to as an automation-first approach to handling inbound customer service queries.
Of course, the problem with messaging apps and one that is getting increasing attention is around privacy and security. Thankfully there are ways to ensure that sensitive customer data is handled by an ai bot in a secure manner so that the data is not exposed in an open messaging session.