Automate your support with AI
Automation is coming. It is touted as the single biggest threat to jobs in the twenty-first century. But it may be more of a saviour for you and your support team than the boogie man it is made out to be in the media.
A recent Forrester analysis identified customer support trends that show an increase in self-service portal usage to over 81% among responding American adults. In fact, by 2020 more than 80% of customer service will be conducted without engaging humans. Customers have begun to warm up to the idea of dealing with the bots. CX sensitive brands are also exploring options to incorporate any AI that interfaces directly with customers.
While AI is a long way away from replacing customer support entirely, it is still a useful tool for enhancing your support offerings. Ignoring the potential of AI in customer service might allow your competitors to surpass you. AI can give your support a real boost in productivity by automating entire workflows you may need to deal with today.
But What About My Team?
All this may sound great for your company, but what will the impact of AI have on your team. If you make your support more efficient and outsource to robots, are you putting your current team out of a job? In reality, support is a vertical where critical thinking and emotion will always be needed to provide the best possible customer experience. AI can be seen as an enhancement for your support team as it will drastically reduce their workload on monotonous or repetitive tasks where agents can get burned out answering the same repetitive questions.
AI is perfectly suited to repetitive, menial tasks, leaving your support team more time to focus on the meaty stuff which will always exist. Aspect’s 2017 survey on the agent perception of chatbots found that 79% of agents feel that handling more complex customer issues improves their skills and offers more opportunities for career growth.
So let’s look at just a few ways you can harness the power of AI for customer support to enhance your teams’ performance.
As discussed above this is an area of particular relief for agents, removing menial and repetitive tasks from their workload. AI can help in automating responses to common queries like order updates and password reset advice which only needs a simple canned response to answer a customer’s issue. It can also remove unnecessary steps in the support process by asking customers for more information on their issues like order numbers or full addresses before passing it on to a live agent who can properly deal with their issue. This can be implemented into your support workflows in a matter of days and save your team countless hours of monotonous work best left to the robots.
Route Tickets to the Right Agents
Even if your brand is customer experience sensitive and firmly against the idea of AI talking directly to customers, AI can still lend a capable hand behind the scenes. Using natural language processing, AI can “read” a ticket, understand customer intent and direct it to the right team much faster than a human triage system can.
For example, Uber built COTA (Customer Obsessed Ticket Assistant) to help route tickets better and suggest answers to customer support agents. They found that better ticket routing increased efficiency by 10%. Plus, measuring customer satisfaction through surveys, they found that CSAT stayed consistent or improved through the implementation: “By empowering customer support agents to deliver quicker and more accurate solutions, COTA’s powerful ML models make the Uber support experience more enjoyable.”
By not allowing the AI to talk directly to customers, Uber gets all of the benefits of AI but reduces the risk of terrible customer experience. And you don’t need to be Uber to implement AI ticket routing into your support. Out of the box AI solutions like Cx MOMENTS take days to set up and cost a fraction of the budget you would need to build your own AI system.
Prioritize Tickets in Backlog
Based on the huge amount of data that we have analysed from our customers, we have found that the typical customer support team spends 237 working days a year reading the +200,000 tickets they receive every year. That is before they have even begun figuring out a solution and answering the customers’ issue. When tickets flood in it is quite easy for a team to quickly find itself in backlog with a mountain of customer tickets that need to be answered. To prioritize the tickets that need your attention first, you need to read all of them, but you simply don’t have the time to.
AI and machine learning can derive quantitative data from the qualitative much faster than agents can. AI can also find the patterns that your agents didn’t even think to look for. Because each agent is only seeing a small slice of the total number of customer conversations, it’s impossible for them to determine if the questions they are answering are one-offs or symptoms of a much bigger issue.
With AI you get full visibility of why your customers are calling and are able to make decisions based on quantitative data on what customer issues to answer first and where possible causes of the backlog are coming from.
Ultimately, the companies that are able to implement AI earlier will have more breathing room to provide amazing customer service by handing off the more repetitive tasks to machines. AI will also provide them with more insights based on quantitative data, to base their decisions on. It’s the leg up you need to stay on top of your customers’ issues and ahead of your competitors.