Your customer success team is only as good as the knowledge base they rely on, and most internal knowledge management systems range from barely adequate to laughably awful. Fortunately, artificial intelligence tools have advanced to make knowledge bases - and customer success teams - better than ever before.
Your customer success team has one of the most daunting jobs in your organization, one which requires them to be experts on the technical, practical, and financial aspects of all your products and services. Customer success teams not only implement a customer on a solution, they also are charged with avoiding customer churn. In fact, good customer success teams create negative churn by getting customers to use more of your products and services over time.
To do this, customer success teams must be almost inhumanely expert on everything your products and services can do for every possible customer in every possible situation. This job description often seems to require the equivalent of 20 years' experience using a one-year-old product. To square this seemingly impossible circle, customer success teams rely on exhaustive documentation and reference materials about your current solutions and their past implementations, which means that developing, managing, and maintaining a sufficient internal knowledge base can make or break your customer success efforts.
Unfortunately, developing a good internal knowledge base is one of the most under-resourced and underappreciated jobs in nearly every company. Very few organizations have a documentation team accountable for maintaining your knowledge base, even in large corporations.
That's where new artificial intelligence tools come in. AI can make your knowledge management system more effective than ever before by automating and enhancing your documentation process.
Your average knowledge base suffers from three problems:
- Your knowledge base is hard to populate
- Your knowledge base is hard to navigate
- Your knowledge base is hard to update
All three issues can seriously undermine your customer success team, because all three prevent the team from finding a needed answer in your knowledge base.
With an AI-enhanced knowledge manage system, a virtual software agent can observe your customer success team's communications when new implementation tactics are employed and new problems are solved, prompting the creation of new entries in your knowledge base (either by your team or, in some cases, by the AI itself). For example, if someone uses a new Chrome extension, or a new SQL script, to solve a customer implementation problem, the AI agent can mark that for inclusion in a knowledge base article.
When existing knowledge base entries are relevant to new incoming inquiries, AI can update those entries’ annotation to indicate that the content is relevant to new problems. For example, if someone realizes your new floor wax can also serve as a dessert topping, the AI can tag the entry for that product with both keywords (and also mark down which customers employed the solution for which use case).
And, if your customer success team has to constantly adjust information in your knowledge base – like identifying out-of-date screenshots or correcting mentions of non-current software versions – an AI agent can flag those articles for update.
In addition to annotating and creating relevant content, AI grooms your knowledge base to keep it current so your customer success team can focus on customer success, rather than compensating for wiki-rot.
Keep up with the most innovative teams who are adopting AI; try Talla for Knowledge Management today.