Feb. 10, 2022
In the world of customer support there are 2 distinct types of escalations; those initiated by the customer and those initiated by an internal support agent. In either scenario, we know escalations can negatively impact the customer experience. Customers expect fast, intelligent responses and resolution times when they have an issue. As a customer support ticket escalates from one tier to the next it is handled by different people each of whom must research the issue to uncover the best path forward. Each tier has its own standardized guidelines that the support agents must follow. This process takes time. Time that your customer is not always willing to give you.
This is not to say that every escalation is bad. There are times when the complexity of the issue demands a higher level of technical expertise than a typical tier 1 support agent might possess. Agents regularly have to balance the knowledge that escalations can lead to elongated resolution times and reduced customer experience while understanding that some issues require escalation…how are we to reconcile these divergent paths to provide the best customer experience possible?
This is where automation and predictive analytics must come into play.
In order to reduce the number of escalations, you need to ensure your agents have immediate access to the information they need to resolve tickets. Sounds simple enough. But when you consider the effort that goes into ensuring you have the right knowledge base articles, ensure they are in a single source of truth, and enable your agents to have immediate access to search those articles within the context of the ticket they are working on, this simple idea explodes in complexity. Let’s break this problem down.
How can we ensure our support agents have the knowledge they need to resolve a ticket, when we can’t possibly know every issue a customer might face? The first step in preventing repetitive escalations is predicting when they’ll happen.
Effective prediction requires rethinking the purpose of analytics. While it is important for customer support executives to be able to see how an agent is performing, how many support tickets are created for each area of the product offering, or how long on average it takes to respond to customer support tickets, this information is reactive in nature and only serves as a lagging indicator.
Customer Support teams need to move beyond reactive analytics to real-time, predictive analytics. In doing so, support executives can pay attention to emerging trends, quickly identify repeating escalations, and strategize ways to prevent them in the future. With real-time, proactive monitoring your team will have the data they need to create the necessary knowledge base articles required for your teams to resolve customer issues. You will also have the data you need to prevent repeat tickets from happening in the first place.
You might be thinking, how can we have a single source of truth in customer support when there are so many disparate systems of knowledge we access for each ticket? It doesn’t make sense to move all of your knowledge base articles to your ticketing system, or all of your tickets into your knowledge base, and it’s unlikely you’re going to get your engineering teams to move off of Jira and into a platform like Zendesk.
The solution isn’t to bring all of the resources in your company into one platform; you simply need to give your agents a singular place to search all of your data silos in the place where they already work: the ticketing platform. Most frontline support agents spend the majority of their time in their customer support system like Zendesk or Salesforce Service Cloud, but they are asked to repeatedly context switch in order to search disparate knowledge sources when an issue arises.
To get a single source of truth, agents should be able to search all of those knowledge sources without ever leaving their service desk. Providing your support agents with access to all knowledge sources, ticket information, bug tracking, and current trends within the system they already use - allows them a single place to find all of the context they need to quickly and efficiently resolve customer issues before they escalate, all without disrupting the workflows of other teams.
Are you looking for an escalation management strategy? See how you can provide your frontline support agents with the contextual information they need, in the systems they already use. AptEdge supercharges your agents with real-time context and predictive analytics to reduce customer escalations and elongated resolution times. Sign up for a free trial today.