Customers like to help themselves. They want to be able to resolve their own customer support issues without having to send an email, wait on hold for hours, or be bounced around from one customer service agent to another.
The good news is that self-service support can help avoid these frustrations. The bad news is that it only works when done properly. In it’s current state, self-service customer support is more frustrating than helpful.
- FAQs only answer questions that have already been asked.
- Knowledge bases rely on customers knowing what the problem is in order to find the right way to solve it.
- Interactive voice responders can’t discern when a customer is angrily hitting their dial pad trying to get the information they need.
Self-help portals aren’t always the most helpful in answering specific questions (Source)
According to a report by ITSM.tools, self-service is failing because 87 percent of customers still prefer the human touch. They miss the understanding and empathy that comes with talking to a live customer support agent (even if they do have to wait for it a little bit longer). Unfortunately for customer service departments, that means more time and money invested in human-led customer support channels.
This leaves customer support departments at a crossroads, trying to find a happy medium between providing support that’s helpful and human without investing thousands in support agents.
Contextual awareness and AI can help bridge that gap.
Customer support departments can use contextual awareness and AI to provide a more accurate and helpful self-service option for customers, saving time and money on human-driven forms of customer support that serve the same purpose.
The state of self-service customer support
Talking to a live support agent can help solve a problem more quickly, but that’s only when self-service isn’t done properly.
Self-service support includes knowledge bases, FAQs, and interactive voice response (IVR) to help customers resolve issues without the assistance of a human support agent. Not only is self-service the default option for customers, but it can also save a company time and money during the support process.
1. Customers want the option to be able to help themselves before they have to reach out to support agents.
- Eighty-one percent of customers will try to solve an issue themselves first, before contacting a support agent.
- Ninety-one percent of customers say that they would use an online knowledge base if it were available and tailored to their needs.
2. Self-service is a way for companies to save time and money, especially for first-tier support issues that don’t require complex issue resolution.
- The cost of a live customer support interaction (whether by phone, email, or chat) is $7 and $13 for B2C and B2B companies, respectively. Costs for self-service is pennies in comparison.
- Self-service support decreases ticket volume to provide more time for agents to spend with customers who need help with more complex issues.
Unfortunately, in its current state, self-service support often leaves a lot to be desired.
3. Companies are still lagging when it comes to providing customers with the self-service experience that they want.
- Thirty-one percent of customers get frustrated when spending as little as five minutes looking for an answer.
- Forty percent of customers say that they still had to call customer support after looking for answers in self-service.
4. Some of the biggest obstacles for self-service success can be solved by AI and contextual awareness.
- Eighty-seven percent of users prefer the human touch as opposed to self service.
- Sixty-two percent say self-service portals are difficult or unintuitive to use.
AI bridges the gap between helpful and human
In a recent article, I talked about how AI is helping to bring some of the humanity back to marketing in the form of a conversation. A similar approach can be used with AI to help make self-service support more useful, with the help of contextual awareness, chatbots, voice assistants and IVR.
Contextual awareness will send signals
Searching through a knowledge base or an FAQ can be a lot like rummaging through the bargain bin: full of stuff—none of which you particularly need. Having a self-help section that’s contextually aware can help sort through some of that noise.
Contextual awareness is when a system can gather data about the environment that a customer is coming from in order to make smarter suggestions for self-help resources. This includes things such as a customer’s location, which device they’re accessing a site from, and even the intent behind their search. It could also know which searches you’ve done before to help make resolution quicker.
For example, if a customer is having trouble on the mobile version of a website and is accessing the FAQs from a mobile device, the system should show resources for mobile device help. Similarly, based on where you are or your preferred language, you can get help showing up for your location or language preference.
Chatbots will leverage previous interactions
Chatbots (known as virtual agents in the customer service space) are the quintessential AI tool being incorporated into areas such as marketing, eCommerce, and customer service. They work to answer questions in a conversational way, using either a rule-based or machine learning approach to help customers find the right answer.
Rule-based bots are more static, preprogrammed to answer common questions with a limited set of answers to choose from.
They could easily answer a question such as:
“How do I change my password?”
But might have trouble answering something like:
“Why isn’t my account information loading?”
If they can’t answer the question, customers will have to resort to another form of support.
Machine learning bots are where self-service could see a bigger bump. Machine learning bots learn from past interactions to help improve responses. Based on your interaction and all interactions before it, it can dynamically answer questions and even ask its own to give better search results to customer queries.
It’s the equivalent of the “Was this helpful?” question in a knowledge base, except it’s using your answers in real-time to help resolve the issue, much like a human would.
Eventually, the idea is that they’ll even be able to recognize emotion and tailor messaging based on customer sentiment.
Voice assistants and IVR will gauge customer sentiment
Similar to chatbots, voice assistants can help bring more empathy to self-service support. As voice search gets better with natural language processing, and people turn to voice assistants like Siri and Cortana more often, voice assistants will be better equipped at understanding and digging up the right answers for user queries.
IVR, also known as interactive voice response, can also benefit from the AI treatment. A more conversational flow and quicker response reaction can help to better match customer intent and solve the problem more quickly.
Conversational IVRs will even be able to gauge customer sentiment and route calls depending on a person’s tone of voice. If they’re angry, they’ll be sent in one direction. If they’re calm, they’ll be sent in another.
Self-service support is as human as you make it
As you’re developing your self-service strategy and trying to incorporate more of a human touch into a fairly cold form of customer support, keep in mind some of these best practices and how AI could make them even better:
|Best practices for self-service support||How AI can make it better|
|Make it intuitive: Make sure that it’s easy for customers to find your self-service section and navigate around once there. Users get frustrated when they can’t easily find what they’re looking for.||Whether using chatbots or voice assistants, AI can help lead customers down the right path by gauging intent and adjusting responses accordingly, doing much of the navigating for a customer.|
|Be consistent: Extend your brand’s voice and your customer service values to your self-service support. Ensure that your tone of voice and user experience is aligned with the rest of your website and customer support channels.||AI and contextual awareness let you be more creative with how you deliver a message by tailoring answers to specific scenarios while still keeping the same tone as your brand.|
|Update it regularly: As your product changes, so too should your customer support. Keep tailoring and improving upon materials to reflect product changes and user feedback about the usefulness of your knowledge base or FAQs sections.||Using data about how users got to a help section, where they got tripped up, or how they reacted during the process (based on what they said) can help improve the usefulness of self-help resources.|
|Have other options: Self-service won’t be able to solve everything. Have other support options like live chat or phone support available to help with more complex issues.||Chatbots and voice assistants can automatically route users to support agents if the problem can’t be readily solved themselves, completely streamlining the support process.|
Self-service is a great way to provide users with the type of support they want while freeing up time for agents to focus on more complex issue resolution. When incorporating AI, this self-support can be more useful and feel much more human than scouring through a static FAQs page or bulky knowledge base.
Self-service will never be able to fully replace real customer service agents when it comes to solving complex problems. It can, however, take care of quick and common issues, and more accurately with the help of AI and contextual awareness. Self-service is a good way to provide customer support at scale, and AI is the only way to be able to scale that human touch.