Artificial intelligence, or AI, has been a hot topic within the customer support community recently and there are many good reasons for that. By using AI intelligently (no pun intended) support teams can be more efficient and effective, and create a better experience for customers, all without sacrificing quality.
It’s important to note that when we talk about using AI in customer support, we mean using it to empower the support team, not replace them. Humans will always need to be a part of the customer support experience, as AI will never be as smart as humans. AI can enable support agents to do their jobs better and therefore deliver better customer experience.
You can think of AI in support like calculators are to accountants. With a calculator, accountants can… account faster, with fewer errors, and spend more time on bigger tasks. With AI, support teams can get answers to customer questions faster, with fewer errors, and spend more time on bigger problems.
Let’s look at these few ways you can use AI to improve the customer support experience by unleashing customer support superpowers!
Using AI for Tagging & Data Analysis
Customer support organizations generate a wealth of data, and there is a huge opportunity to use that data to evolve the product and grow the business. There are ways humans can pull information out of customer engagements, such as tagging and other data entry processes, but let’s be honest, it takes time, it’s not easy, and if you don’t have the right system down, the data is only minimally useful and sometimes not useful at all.
In most cases, manually tagging tickets doesn’t provide the level of granularity we need. Product teams value customer support data when it can tell a story and provide true insights, but the data we get from manually tagging doesn’t always accomplish that. AI can fill in the gaps and supply a more holistic picture from customer support data. This type of rich customer support data can help shape your product into something your customers can’t live without.
What if you never had to tag a ticket ever again? With AI and machine learning, that’s very possible. Tools like Idiomatic and MonkeyLearn enable software teams to make sense of their customer support data at scale. By using automatic ticket tagging, support teams are able to focus more on customer interaction and leave data capturing up to the machines. This not only helps the support team by saving time, but it also helps the product team by providing customer insights from support tickets faster, more accurately, and more consistently.
Customers benefit in a number of ways. They get quicker responses to their requests, and they get a product that better suits their needs, as the product team has richer data on what customers are asking for and the pain they’re experiencing with the product.
AI introduces a systematic, scalable way of consuming mass amounts of customer engagement data.
Using AI for Sentiment Analysis
AI can also be useful in analyzing data for customer sentiment. Customer sentiment is the overall emotion of customer engagement, and this data can become useful over time as the product changes. For example, if your product team made a change and the overall sentiment in support tickets during that time decreased, it’s possible you may have missed the mark.
Taking this even further, sentiment data can also be used to trigger other actions, like routing tickets. If a customer writes in and the AI tags the ticket as having an extremely negative sentiment, it could be prioritized accordingly. Or if a customer writes in and the AI tags the ticket as having an extremely positive sentiment, it could be tracked as a potential opportunity for a customer case study or testimonial.
Using AI for Automatic Routing and Triaging
Many large support organizations have different tiers of support, or different teams responsible for certain types of support requests. Getting those requests to the right team or person is important and can mean the difference between a good customer support experience and a bad customer support experience. The faster that support tickets can get to the right person, the faster the customer will get a response.
AI can help route tickets quickly and accurately by looking at the content and data of the ticket, conducting analysis, and sending the ticket on it’s way all in a matter of seconds. This means support teams can focus on getting the best response to the customer, instead of spending time assigning tickets back and forth until it gets to the necessary person.
Have an angry customer writing in? Make sure they’re handled with extra care by escalating them to a senior team member, or someone who can certainly handle the issue. AI can be used to do all of this behind the scenes (using sentiment analysis we mentioned above) so that support agents can do what they do best; serve the customer.
Using AI for Suggested Answers
AI can play a big role in suggesting answers based on the information in a support request or information a customer begins to provide before submitting a support request. There are two main use cases related to suggesting answers. Answers can be suggested on the agent side, and answers can be suggested directly to the customer before a ticket is ever submitted. Let’s look at both scenarios.
On the agent side, when a ticket comes in, the agent can be presented suggested answers directly within their help desk tool. This saves the agent time by not having to browse for the documentation themselves, and they’re able to save time by not writing up an entire answer from scratch. They can simply select the correct answer, add some personality into their response, and send it off. In this scenario, AI is working for the agent.
On the customer side, answers can be suggested before the customer even creates a ticket. In other words, AI can deflect support tickets. When a customer is in the process of submitting a support request, answers can be suggested to them based on the information they’re providing in the ticket or search form.
AI really shines here, because in most cases, customers don’t want to have to contact support, they want to be able to solve their own problems. AI lets them do that! When suggesting answers on the customer side, support teams often see a significant reduction in many of the simpler support tickets they’re used to seeing.
Tools like DigitalGenius, AnswerIQ, and Solvvy can all help support teams by automatically suggesting answers.
Embrace AI with a Watchful Eye
AI is here, and it’s not going away. The good news is neither are our jobs. In fact, AI needs humans to make sure things aren’t getting too out of hand or heading in the wrong direction. Humans will always be more quality focused than AI, so it’s important to keep a watchful eye over the AI technology you introduce. For example, if AI keeps suggesting an incorrect answer to customers, but the customer never speaks up, humans need to be there to catch that.
AI is an additional tool we can use to do our jobs better, and it is playing a big role in improving the customer support experience. AI helps clean up the small tasks, the repeat requests, and the low hanging fruit. It makes us more productive, accurate, and effective and even helps us build better products!