In a 2020 Zendesk survey, 72.5 percent of customers said that a fast resolution matters most when they have an issue to resolve with a company. Customer support teams (and leaders) can't ignore this standard, especially in B2B where order sizes are large and client retention is so important. And escalations can go all the way up through the service organization and beyond, even reaching the CEO, with all of it costing more money as it moves through the organization. Escalations can even lead to lost customers, which in turn leads to lost revenue.
The best strategy for escalations is to handle service issues effectively and quickly before they escalate. How can you keep escalation rates low and customer satisfaction high? Here are five practices for service and support teams to use to reduce escalations:
1. Identify pre-escalations early.
Using artificial intelligence (AI)-based tools, systems can now scan customers' comments by voice or text and assign a likely-to-be-escalated prediction. It's often a numerical score—higher numbers signal support tickets that have the highest potential to escalate. Using this information, agents can take the right corrective action earlier by identifying the factors that might drive an issue toward escalation.
Support leaders can also be alerted to potential situations early on in the process, giving them time to make decisions, such as bringing in additional experts or resources or re-assigning the customer to another agent who is better suited to solve the issue. Real-time data allows support professionals to work on problems better and earlier on to keep small issues from turning into large (escalated) ones.
2. Make monitoring part of your team's workflow.
Most support organizations have a tiered system for ticket escalation, though the B2B process can vary depending on who is requesting the escalation. Regardless of the process, regular, frequent monitoring of open tickets is important for prioritizing the issues that are most likely to escalate. Additionally, proactive monitoring helps make sure that in-process issue resolution is proceeding in a way that keeps customers as happy as possible while ensuring the issue gets handled.
3. Eliminate artificial bloat from a giant backlog of cases.
Being able to handle support issues faster and more effectively helps keep the overall number of cases down and prevents a buildup of too many total cases. This is important because a big backlog can lead to slower response times and can overwhelm support teams. Companies can fall into a situation where they can't catch up enough to be effective on a day-to-day basis.
Using AI-based tools allows teams to complement their human talent by giving them better information and insights, which makes them more effective. This speeds response times, solves issues earlier, and reduces the overall number of escalations.
4. Have meaningful conversations with support engineers.
Some of today's tech tools allow support teams to share case details with engineering teams or other departments, such as product development. This type of collaboration across teams allows support teams to take different approaches in the future to improve their approaches and allows engineering and product teams to enhance future versions of products based on customer feedback.
If, for example, a certain version of software is getting a high number of complaints from customers and generating a high volume of support tickets, that data can be analyzed and given to other departments that can then develop a patch to fix the problem or create a new version of the software that fixes the issue.
5. Use agent swarming when issues arise.
Some of today's technology integrates with other communications platforms that companies might already be using (e.g., Slack), making it easy to quickly share information among support teams and with other departments. Through this improved communication, support agents can alert each other of serious customer issues and come together quickly and swarm to work together to solve problems, using the combined experience and talent of the broader team.
Having AI-based tools to identify and alert on the most potentially serious cases can flag high-priority cases faster and start this swarming process more quickly than a human-based approach. Once again, technology identifies key issues earlier, maps them to the best resources quickly, and leads to faster resolution before problems get worse and require escalation.
Having the right support experience could mean the difference between increasing revenue or decreasing revenue, which can affect the long-term viability of the company. Using a combination of modern technology and human talent can deliver a better support experience, which is key to customers having good (overall) customer experiences. This helps customer retention, protects revenue, and helps organizations' reputations, top lines, and bottom lines.
Martin Schneider is chief evangelist and head of solutions marketing at SupportLogic.