The promise of chatbots as an innovative engagement tool has fallen short. They’re easy enough to create, as any adept coder can whip up a bot in a few hours. And, there are plenty to go around — Facebook Messenger alone runs more than 300,000 chatbots.
But, most chatbots have failed to impress, leaving customers underwhelmed and frustrated. Call centers and help desks, which stand to benefit the most from automating processes with chatbots, try to keep up. Lacking automation and rich graphical UIs, human staff are overwhelmed, something the COVID-19 pandemic and the demand it has placed on customer service has recently made even more obvious.
Companies need to offer products that provide customers a contained, automated and seamless journey. That was the dream chatbots were supposed to help bring into reality.
Instead, chatbots became one of the reasons for a real revolution in true customer engagement: AI-based automation and the conversational experiences it enables.
The Problem With Chatbots
Chatbots only solve one part of the actual problem — how to serve customers’ needs best. “Chat” refers to just the text transaction between customers and companies. Chatbots have automated that part; text goes in and text comes out. But, that fails to account for the complexity of customer journeys and the need for personalization.
Customers engaging with a brand want a seamless experience delivered right to them. Pictures and videos, file uploads, maps to locations, and document signings are all pieces of the digital experience customers want. Sometimes, when customer text goes in, they need non-text responses to complete their interactions. This is messaging, not chat. To help understand the difference between chat and messaging, think about a typical interaction with Uber. This interaction is a series of requests going back and forth between you and Uber. This is a perfect example of a conversation and it is enabled using messaging protocols. Uber was brilliant in using rich images (pins, maps, buttons, etc.) to make the conversation immersive and, therefore, welcoming. Now, by contrast, imagine if you were hailing an Uber by having a text-only interaction back and forth with Uber’s systems. Get the difference?
Chatbots are the lazy man’s automation and have severely hindered the improvement of customer experiences. Brands need a solution that provides the entire digital experience – a quasi app experience – and this is why messaging is so powerful.
Create The Business Case for Automation
Originally, chatbots were supposed to support human customer service agents — with an eventual goal to replace human assistance with AI-powered help. But, without a clear definition of how they could help customers and support companies’ bottom lines, chatbots failed.
Like any technology, if you don’t incorporate it into your business to solve a specific problem, then you’re wasting the technology’s potential. Chatbots have lived in this limbo since CIOs and CMOs first brought the concept to their board rooms. Everybody built a chatbot without grasping how that feature would improve their business.
While companies are no longer creating chatbots just to have them, they did stimulate the emergence of better CX through enabling AI-based automation and creating conversational experiences for customers. To get there, however, companies have to build a business case for the technology.
The first step is to identify use cases and success criteria. Where would technology improve customer experience? What’s the target ROI? Do improvements in metrics like net promoter score factor into the discussion?
These details define the new technology’s business purpose, which then leads to the details of automation. Where can the company replace or redefine the human element in the backend? Good design arises from answers to these questions.
Automation Enables Conversational Experiences
Businesses need to offer a Conversational Interface which is the ‘canvas’ on which the messaging experience takes place with a customer. This Conversational Interface maps to the backend processes while smart automation decides what rich front end experience should be presented to the user in order to have a successful session. A Natural Language Understanding (NLU) engine is an absolute necessity in rounding off the messaging solution as it is imperative that the solution understand what customers want and what they need.
We all say ‘things’ in different ways and while I may want to ‘drop a pin’ to show my destination, my cousin may want to scroll through a carousel to denote hers. Really robust NLU also understands tone, emoji and sentiment, so when someone responds with a sad emoji, the system knows they’re not a happy customer. This advancement in NLU enables a smooth customer experience because of the ability for users to be interacted with on a personalized level and in real time.
True AI-based automation solutions provide unlimited functionality as they can reach into every backend process your business runs. Many solutions feed into your ability to provide a conversational experience with your customers, and automation can help all of them. Again, it comes down to defining how your business wants to use new technologies and creating a solid business case.
Moving forward, conversational experiences, not automated text transactions, need to be the priority for brands. Companies using CI and other automation will provide the seamless experiences customers expect and create true engagement using AI.
This article was originally published in insidBIGDATA.