The knowledge base has been considered a crucial component of providing self-service for years.
It’s often touted as indispensable for helping customers and upskilling support agents. And now knowledge bases as we’ve always known them are dead. That might seem like an exaggeration, but it’s not.
Customer demands are changing and customer service technology is improving. These two factors mean that providing on-demand and contextual support is now a trend you need to consider. If your customers aren’t asking for contextual support yet, they will be soon.
Zoom out for a moment.
Whether you know it or not, you’ve probably recently read a news article that was written by artificial intelligence (AI). We’ve all seen the expansion of chatbots. If you’ve been paying attention, you’ve noticed that in-product support is becoming standard.
The traditional knowledge base is fading
- Your knowledge assets (as in your written down information)
- Your knowledge storage (where the knowledge is indexed and stored)
- Your knowledge portal (where it can be found by your users)
All three of these ingredients have to evolve as the traditional knowledge base becomes less relevant. Millard’s vision for the future is the need to “bring all of these into the product and leveraging technology to expose it easily and in context to the user.”
The ‘traditional’ model of going to a knowledge base and using keywords to search for an answer is becoming outdated. If you have a help center filled with knowledge articles, over the next few years it will become obsolete. Users are growing to prefer in-product knowledge and help, delivered instantaneously by chatbots, guides, or other means.
Emil Hajric, founder and CEO of Knowledge Base tool HelpJuice, says this: “As far as the way knowledge articles are used—whether through in-app chat, a suggested popup, or the user going straight to the knowledge base center, the goal is to help the user find the answer faster with less browsing or searches.”
Exactly. Going to a help center and searching for a topic is useful. It’s worked for years. But it’s no longer required.
This trend is happening across all technology. For example, all major web browsers now allow you to search directly from the address bar. Voice search is on the rise. Interactive onboarding guides are now the norm when you sign up for a new SaaS product. Each of these shifts are responses to the shift in how knowledge is now being consumed.
The (Potential) AI Disruption
Can AI write a knowledge base article? And if so, should they?
That trend has not gone unnoticed by Hajric: “I know we’re all tired of the word ‘AI’ being thrown around, but creating content can be tedious work. My prediction on the future of knowledge management is that we’ll be able to have a knowledge base that is 100% auto-updating by itself.”
Creating or updating articles isn’t the only place in your knowledge management strategy where AI can play a part. Hajric highlights another function for AI: “Something that we have is what we call ‘Contextual Awareness’ which grabs the paths of successful searches and tries to predict the appropriate answer based on other successful paths.” Features like this are already a reality.
“Support agents rely on knowledge articles to drive constant learning,” says Somya Kapoor, co-founder and CEO of TheLoops. “But this is still a very reactive approach for modern support. SaaS companies need to complement it with product context which is already available in the organizations.”
The implication is that AI can highlight the right articles to your support agents at the right times. This brings two advantages: reduced training costs for your agents and less friction for your customers.
Combining Hajric’s vision of AI predicting answers for customers and Kapoor’s observation that AI can help agents in real-time creates meaningful possibilities for support teams.
You’ll be able to drive positive customer experiences through sharing your knowledge in more creative ways. As Kapoor puts it: “This is where you can move the needle from being reactive to preventive.”
Smarter Support Operations
The knowledge-sharing evolution is not just about product data and knowledge articles. It also includes all of the other pieces of metadata you have about an account, customer, or product use case.
This data exists in many different systems: data warehouses, bug trackers, CRMs, customer success management tools, and more. Kapoor believes that connecting these data sets together is the solution.
“Knowledge bases are static and an incredible amount of time is spent creating and searching them; both agent and customer time. If every customer interaction could be enhanced with real-time, contextualized insights such as customer data, sentiment, usage metrics, alerts, you will shave hours off every agent engagement and can provide insights to organizations too.”
Smarter support operations mean combining your tech stack in intelligent ways so you can deliver better guidance to your agents and customers. Like revenue ops or sales ops, support ops can give your support organization a boost through holistic tool oversight, data analytics, and identifying areas to improve customer experiences.
Knowledge Remains Critical to Success
Let’s be clear: knowledge sharing is not going away.
Humans have transmitted knowledge for our entire existence. Whether that is carving in stone, scripting in ink, generating air waves, or connecting wires, humans have always wanted and invented ways to share and access knowledge.
The key for today’s support leaders is to stop thinking in terms of a knowledge base and start thinking about the best way to share contextual knowledge. How can you give customers the perfect knowledge at the perfect time?
The options are virtually endless, but the only way to make these possibilities a reality—and to set your customer experience apart—is to rethink your knowledge management strategy.
Knowledge isn’t dying. But the traditional knowledge base is.
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