Mar. 14, 2022
In a world where customer expectations are at an all-time high, it has never been more important to resolve customer issues as quickly as possible. In fact, in response to a Zendesk survey question about the most frustrating aspects of a bad customer service experience, nearly 60% of respondents stated that long wait times while interacting with an agent are the most frustrating. While 30% thought that the agent not having sufficient information on file was the most frustrating.
What do these two frustrating situations have in common? They both come down to the customer being upset with the amount of time it takes the agent to resolve their issue. Whether it is waiting too long to have an agent respond to a customer support ticket, having an agent respond with the wrong information, or the agent not having the required information and needing to escalate the issue the result is a bad experience for the customer.
This problem within customer support directly impacts revenue. According to a Zendesk customer experience trends report, 50% of consumers will switch to a competitor after a single bad experience and that number jumps to 80% after more than one bad experience. If support teams aren’t continuously improving their response and resolution rates businesses run the risk of high customer churn.
The good news is that there are solutions to help customer support resolve customer issues more efficiently. The need for these solutions will continue to increase as customer support is becoming a revenue driver for many companies. Bain & Company has noted that a mere 5% increase in customer retention produces more than a 25% increase in profits.
Here are three key areas to focus on to improve the efficiency of your customer support operations.
In order to resolve customer issues more efficiently, you must automate as many of the time-consuming manual tasks as you can across all of your customer support operations. Agents are often overburdened by the number of tickets they receive and often have difficulty categorizing and grouping them based on similarity. With the use of AI and ML, incoming tickets should be analyzed, automatically grouped, and sometimes even deflected entirely prior to reaching a live support agent.
By automating processes, deflecting recurring tickets, and automatically grouping similar tickets, support agents are able to better prioritize which tickets to tackle first. This will have a big impact on the overall customer experience helping to prevent churn and create upsell opportunities.
When a support agent receives a new ticket they must research where the ticket is coming from, whether a similar ticket has been resolved in the past, if there is an open bug, whether there is a parent ticket associated, or if there are any knowledge base articles on the topic. Unfortunately, all of this information resides within different systems. That means support agents are often spending much of their time going from tab to tab typing the same search query into several different search bars. And this is happening while the customer sits idly waiting for a response.
The work-life of a support agent, as well as your customer, would be greatly improved if they had immediate access to the contextualized knowledge they need to respond and resolve incoming tickets. Support agents should have a single place, within the ticketing system they are already using, to search across all of the disparate support tools and knowledge bases they use. This will allow them to uncover the insights they need to resolve customer issues from related tickets, knowledge articles, and emerging trends so they can quickly respond to and resolve the issues of your customers.
Taking this a step further, agents should also be presented with recommended knowledge base articles, similar tickets, and open bugs so they don’t need to type into a search bar at all.
And finally, analytics needs to be thought of as more than just a way to see agent and team performance, resolution times, escalations, etc. Analytics needs to be used as a proactive tool that you and your support teams can use to predict and prevent escalations. Customer support does not have the luxury to wait and use reactive data to incrementally improve processes over time. They need their analytics to provide actionable information to handle the tickets they are currently receiving. Analytics should be able to help your agents quickly identify emerging trends across your product areas, customer base, or ticket themes so they can get ahead of trouble areas.
By understanding what trends are emerging, you can proactively update gaps in knowledge base articles and prioritize which tickets to respond to first. And yes, you should also be able to see response rates, resolution times, which agents escalate the most tickets, and the revenue impact of support cases so you can proactively prevent customer satisfaction issues and customer churn.
Whether you’re looking for help automating your customer support ticket lifecycle, providing contextual knowledge to your agents within their current systems, or if you need to turn your reactive data into actionable insights AptEdge has your covered. Get started with AptEdge today, free.