The Solve and Evolve loop as an entire process does much more than just dealing with customer service and content. While customer service and content are the focus of this article, I’d like to point out that the Solve & Evolve loop is inherently a demand and usage-driven feedback mechanism meant to optimize your customer service and provide feedback for product improvement. I’ve written another blog post about using customer contacts to improve both service and product.
But, I digress. Continuing with the focus of this post, let’s go through each of the first four steps:
Step 1: Gather knowledge
Knowledge always starts with the customer. After all, what they’re experiencing is vital to your business. When a customer asks a question, a support article is created to answer that customer. Your agents write articles based on the customer’s context and are at the same time making that knowledge relevant and searchable.
Step 2: Structure knowledge
The best way to write a support article is from the customer’s perspective. To do this properly, it’s often easiest to start from a template. This also ensures that the agent provides the required information and that knowledge articles are uniform and easy to read.
Step 3: Reuse knowledge
When a customer asks a question, the agent has to search the knowledge base. Each time a support article is reused, you’re providing consistent service, which is so essential to a great customer experience.
Step 4: Improve knowledge
The next step is to improve your collective knowledge. Make sure your agents know this and take part in it; ownership of it is vital to the success of KCS. It’s not just to help them – it benefits their colleagues, your business, and your customers.
So, Just How Effective Is Knowledge Centered Service, Really?
One of our customers, a gaming company with a popular online multiplayer game, had documented only 29% of their processes before they implemented KCS. This lack of a single source of truth for knowledge meant that agents searched in internal knowledge bases and external sites like Google and Stackoverflow for answers to players’ questions. It also meant agents were sending solutions out that might work for the player. After implementing KCS, they had 85% of their processes documented in just two months – that’s right, they went from 29% to 85% in two months! Agents were now sending solutions they knew worked, and players were no longer dependent on the searching skills of the agent handling their issue. When you receive hundreds of thousands of contacts a week, this makes a massive difference in agent satisfaction, player satisfaction, and efficiency.
And, it’s not uncommon for companies to keep their knowledge spread out in different folders and drives, with no formal structure or knowledge base. In fact, in a survey conducted by Dixa late last year, 47% of customer service agents, out of a cohort of 1500 across the US and UK, said that they have no formal knowledge base, with more than 29% responding that they often turned to Google to try and find answers. Read the full report here.
Empowered Agents and Consistent Answers
When agents can find answers to customer inquiries in an internal knowledge base, they feel empowered to solve issues because they know the information they’re providing to customers has been verified and is coming from a trusted source.
When no article exists to solve an issue, agents have the power to create a new article right away and know that it will benefit not only their team members but also potentially themselves at a later point in time. If a solution is incorrect or things have changed since the article was published, they can flag the article and provide the correct information so the article can be updated. From the customers’ side, they will experience consistent answers across both agents and channels because the information is coming from the same source.
Closing the Loop
When you’re using a knowledge base that’s built-in to your customer service software, after a conversation has been resolved, agents then mark what article was used to solve the issue. This information is then added to the conversation as an internal note, which, if the customer reaches out again, ensures the next agent won’t try that same solution again. Instead, the agent will either use a different article or flag the used article to consider updating it to shed light on this new situation.
Part of Knowledge Centered Service involves keeping an eye on your knowledge base’ analytics: which agents are creating the articles used the most to solve customer issues? Usage of which articles results in a high CSAT? Or, conversely, a low CSAT? There is a wealth of knowledge to be gained by analyzing the quality and health of the articles in the knowledge base.
Get Started with Knowledge Centered Service Today
I hope this guide has proven useful and made the prospect of introducing Knowledge Centered Service to your support organization seem both exciting and possible.
If I can add one final word of advice, it’s to start today. You’ll see immediate benefits, and, as for the results, well, I’ll let them speak for themselves.
Download the eBook version here, and access it for offline reading anytime, anywhere.
If you’d like to hear more about KCS and Dixa’s knowledge base – book a demo with us today.