Why do organizations deploy customer service chatbots?
First and (hopefully!) foremost, the goal is to offer a convenient, low-effort way for customers to find information. Doing so can help organizations simultaneously take down another important objective: scaling contact center operations and, by extension, controlling costs.
Early as it might still be for chatbots (according to the Gartner Market Guide to Conversational Platforms, only 4% of enterprises have deployed conversational interfaces), the potential upside is considerable. Chatbots Magazine, for instance, estimates that chatbots can save 30% in customer support service costs.
If they work as intended, that is.
According to Gartner, “through 2020, 99% of artificial intelligence (AI) initiatives in IT service management will fail, due to the lack of an established knowledge management (KM) foundation.”
The ties between knowledge management and chatbots
Following a customer-initiated interaction or query, a customer service chatbot typically starts by asking a question—or sequence of questions—to narrow down the user’s intent. To do so, the chatbot uses natural language processing to parse the customer’s query, information it uses to make its own query to a standalone knowledge management solution (or knowledge base) for the right content, answer, or solution.
On the front end, this user experience ought to be a seamless one that makes a call or email to the contact center unnecessary.
To be effective in this capacity, chatbots need to be fed the right content. This makes an organization’s knowledge content and, more generally, its knowledge management strategy, foundational to the efficacy of its customer service chatbots.
Unfortunately, it’s also the knowledge management piece that’s often overlooked by organizations looking to deploy or improve their chatbot experience.
Good KM organizes and structures content
A good knowledge management practice lends well to creating the kind of content that helps chatbots be an effective customer service channel. Think long-form PDFs and static FAQs broken down into discrete, bite-sized pieces.
Sometimes referred to as microcontent, these bite-sized pieces of content cater to the way humans process information—a process chatbots are designed to mimic and respond to. And it’s sound KM that helps organizations prepare knowledge content for these conversational interfaces in this fashion.
Good KM sustains better chatbot experiences
To consistently feed chatbots effective content, there needs to be a system in place to continuously capture, reuse, and extend an organization’s knowledge in a structured and efficient way.
With a knowledge framework like this in place, it is far easier for chatbots to not only match user intent to the exact piece of information and content a user needs, but to continue expanding its capacity to do so as operations ramp up.
Without good KM in place, an organization’s chatbots are at risk of becoming lifeless shells that diminish the customer experience and contribute to the very scalability issues they’re designed to help ameliorate.
At the end of the day, an organization can have all the knowledge content in the world; but without good knowledge management, chatbots might not be able to find it.