Jan. 24, 2022
The last decade saw customer expectations for rapid innovation and ease of use force technology teams to move from traditional waterfall development methodology to agile DevOps practices that allow them to respond to customer demands in real time. This change in methodology brought with it a plethora of fancy new tools for engineering teams to optimize their workloads and deliver on the promise of continuous delivery. But, as we all know, software releases are prone to issues. As companies quickly iterated to deliver great new features, enterprise customers were willing to take some of the bad with all of the good.
Now, the consumerization of technology has diminished customer willingness to accept bugs in software to almost zero. More and more people are relying on digital services for all aspects of their daily lives and expect their software to ALWAYS work as intended - in both personal and business settings. Even as software delivery cycles have shrunk from quarterly releases to multiple times per day, customers' reliance and expectations of quality software and digital services have risen to all time highs.
When coupled together, these trends have led support ticket volumes to soar by more than 30% over the past year. Historically, higher ticket volumes have meant hiring more agents. However, with the onslaught of ticket volumes showing no signs of abating, the days of throwing more people at the problem have finally become recognized as an unscalable strategy. While support for engineering and DevOps teams has catapulted into the future, the tools for enabling customer support teams to rise to the challenge of ever increasing ticket volumes have unfortunately lagged behind. How are frontline representatives supposed to combat this issue?
It’s time for Customer Support to have their ‘DevOps’ moment.
Over the years, most companies have made significant investments into technologies to help with this growing problem. Platforms such as Zendesk and Salesforce Service Cloud are brought in to help these companies track customer issues and complaints. Many companies have also provided their customer support teams with knowledge bases to document best practices, recommend workarounds, and troubleshoot known issues. Engineering teams use tools like Jira to track bugs and manage workloads. All of these tools combined are meant to help customer support teams provide their customers with the best possible experience. But how can we tell if they are really succeeding?
Despite these investments, customer support teams are struggling to keep up with the increase in contact volume - in large part due to the manual nature of the ticket lifecycle workflow. The issue boils down to having disparate data silos that live in systems of record, rather than having a unified system of engagement. When a ticket is assigned, the customer support agent must sift through multiple systems and an overwhelming amount of data; they’re missing the context they need to get the right information when they need it most. Has a ticket already been created for this issue or has a similar issue been resolved before? Let me check Zendesk. Do we have a knowledge base article on this topic that has a workaround? Let me check Confluence. Is this a bug that has already been reported? Let me check Jira. Is this a trend happening across multiple customers? Let me check my Google Sheet. Does anyone on my team have information on this issue? I’ll ask in Slack.
Each time an agent needs to toggle from tab to tab, solution to solution, they lose valuable time searching for answers they need at their fingertips. This lack of contextualized information often leads to duplication of effort investigating issues and agent burnout, not to mention the impact it has on customers. Without immediate access to the right information at the right time customers are waiting longer for responses and resolutions leading to otherwise preventable escalations. The impact of long response and resolution times is most evident in customer satisfaction or NPS scores and ultimately increased customer churn.
The data needed to resolve customer support tickets already lives in existing tools and technologies. The problem is that this information isn’t always, or even usually, where the agent needs it most. It’s spread across disparate tools or living in the heads of your top support agents. Great customer experience is a differentiator for organizations but it’s often overlooked that your customer support agents are the ones providing this service. They are the first, and most important, contact point for any issue your customers face. And, because of that, they have a disproportionate impact on the success and reputation of your brand. Because of their importance, customer support agents need to be armed with proactive systems of engagement.
The customer support agent’s job is to quickly assess the nature of an issue and immediately make decisions on how best to engage the customer. To do so well, agents must have immediate access to all of the data in context of the situation they are dealing with. It is no longer acceptable for agents to need to toggle between tabs and tools, going from search bar to search bar to uncover the information they need to take care of your customers. They need immediate access to the contextualized data, within the tool they use most, the ticketing solution.
AptEdge is purpose-built to solve customer support team’s most pressing problems. AptEdge provides a no-code AI for building machine-learning models to automate support workflows. This speeds ticket response and resolution times by automating support workflows and increasing agent efficiency, providing visibility so you can prevent unnecessary escalations, and delivering the contextual information needed where the agents work so they can provide the best customer experience possible. AptEdge further enables organizations with predictive analytics so agents can proactively detect and remediate customer issues to improve customer satisfaction and support leaders to make smarter business decisions.
As one of our customers, Renee Bastine, Sr. Director of Global Customer Support at Everbridge, noted, “With the things AptEdge is doing in the product like auto-linking, auto replies, and searching outside sources like our knowledge base, Confluence, Jira, pulling all of those sources into one tool that I can go to find the information I need, is monumental and huge. I would absolutely recommend AptEdge.”
Are you looking for ways to enable your customer support teams to provide better customer support? See how AptEdge can supercharge your agents with real-time context and predictive analytics, sign up for a free trial today.