Offering a self-serve support channel for your customers seems like an obvious deflector of support issues, but sometimes they get ignored, particularly if a customer feels as though their issue is unique enough that it won’t be captured within the realm of the most frequent of frequently asked questions. Whatever the reason, handling high volumes of FAQs from customers is a sure way to make your support desk overly costly and increase overall issue resolution times. Here, we will discuss some strategies to consider when trying to reduce the load of FAQs that are unresolved via customer self-serve support channels.
Design a more effective FAQ page
First, start with the FAQ data. Your most common customer questions probably feel like they’re within reach, but now is a great time to check with your knowledge base analytics to ensure that you list the most common challenges encountered by your customers. Maybe you store this data in a wiki, Google Drive, Confluence or somewhere else – whatever the case may be, its time to go look there now. Once you’ve got that data, its time to build your best FAQ page EVER (tips via Semrush).
- Create a clearly defined and logical structure.
- Answer questions clearly and concisely. If it needs to be more detailed or expert-level, you can link to a more in-depth guide elsewhere on your site.
- Update your questions and answers regularly, based on new information or developments.
- Categorize your questions.
- Display your most common questions on the landing page.
- Answers should be short and allow users to search.
- Link to related questions or resources that can lead the user down the conversion funnel.
Just a cautionary note, FAQ pages are rarely static. That means you’ll need to regularly audit your FAQ page for the most relevant content and ensure that it is available to your customers and prospects.
Implement an AI-powered web widget
Sometimes users can be incentivized to interact with a Q&A chatbot via a website widget if its presented as a convenient support option. According to IBM research, businesses spend $1.3 trillion on 265 billion customer service calls each year. The same study estimates that chatbots can successfully answer up to 80% of routine questions. When they don’t feel like they are simply there to collect your email address, chatbots can be an efficient way to offer a self-serve channel that is aimed at providing fast resolution.
The calls keep coming in… so what now?
So you have optimized your FAQ page, but the calls continue to come in from customers. It’s good news in a way, but the volume may become unmanageable particularly if your company is growing quickly and you are onboarding new customer support agents regularly. When customers avoid external self-serve support channels and instead want to speak to an agent, its time to make sure that your support team’s tools, knowledge and strategy are up to snuff.
Create an internal FAQ database that is optimized for fast search, access and sharing amongst agents
When your customer agents are being forced to deal with common issues that should be resolvable with an external FAQ page, they need to be able to deal with the issues efficiently so that a backlog doesn’t build up. A backlog can arise if simple issues are taking too long to resolve, which can impact SLA times negatively. Typically, this problem arises as a result of a few common root causes:
- Poor quality internal support documentation
- Disparate knowledge silos that cause confusion as to where the correct answer is documented
- Poor search tools that return insufficient results when queried
- Support agents ignoring self-serve support protocols and reverting to shoulder-taps and interruptions of senior
Much of this can be solved with a workflow-centric knowledge management solution. We emphasize the workflow-centric part because its absolutely critical for success that a knowledge management solution, for data to be searchable, capturable and shareable from within existing workflows. For example, if your customer support team spends an abundance of time in Slack in their workday, then they should be able to search, capture and share knowledge fluidly in that place. This can be challenging depending on the depth of your existing knowledge stores integration with that platform, but nonetheless, this should be addressed to solve the problem.
Improving documentation quality
There are a number of ways to improve documentation quality, including generally making it easier to capture and update knowledge on the fly, but there is one key strategy that makes big difference to the overall quality: content verification. This might be a feature of your existing knowledge base, but ensuring that knowledge is verified creates confidence and trust. So conveying the quality of knowledge and prompting users when it may have expired and needs to be updated, should be a regular part of knowledge maintenance
Searching across knowledge silos
When knowledge is dispersed among multiple silos or repositories, it creates a bevy of problems. First there is confusion as to where to check for knowledge. “Is the answer stored in Confluence? Maybe Zendesk Guide? Or maybe somewhere else entirely? Who knows.”
Second, it delays issue resolution, because the support seeker has to check in multiple places for a single answer. There is a compounding effect on resolution times and there is a high probability that the agent will just give up and opt to shoulder-tap another agent for support.
Solving silo problems can be resolved by providing a reliable single source of truth. This tool might be powered by federated search technology, which will eliminate the need to execute multiple search queries.
Poor search results
Many wikis or repositories have poor search algorithms and return inadequate results. This could be improved with a feedback loop (upvote/downvote answers), but many solutions don’t have a learning component embedded in their search algorithms. By enabling a simple feedback loop, support agents can be confident that their queries will be answered with the most accurate information possible.
Ending Shoulder-Taps in Customer Support Teams
Shoulder-taps have a compounding effect on productivity losses in an organization, particularly when those shoulder-taps are “crowdsourced” in an open communication platform like Slack. Not only does a shoulder-tap reduce the support seeker’s forward momentum, but it takes away from one or more other support agents current workload to divert resources to a single blockage in the network. Ultimately, these behaviors occur because the agents do not have trust or confidence in the existing self-serve support channels, or worse yet, they feel as though its easier or faster to simply ask a question in Slack than to ask the wiki/knowledge base. When you combine all of these things, the problem that requires focus is workflow related. By optimizing search, access and sharing of knowledge from within existing workflows, your chances of self-serve support success are high.
In conclusion, there are a number of strategies that customer support leaders can implement to increase the efficiency and effectiveness of your team when confronted with excessive low-quality support requests. To reiterate, they are:
- Improve your FAQ page
- Explore customer facing chatbots as a solution
- Choose a wiki that is optimized for FAQs
- Improve documentation quality
- Enable multi-silo search tools
- Train search algorithms to improve results
- Focus on optimizing for existing workflows that your customer support agents are comfortable with