Practically speaking, increased ticket volume can be bittersweet. A ticket influx means your company is growing its client base, which is great news. But on the other hand, an increase in customer inquiries is almost guaranteed to cause customer support bottlenecks. Most support teams lack the resources to scale accordingly.
When overwhelmed by tickets, your knee-jerk reaction might be to hire more agents, but throwing extra bodies at the problem is not a sustainable solution to the ongoing issue of scalability. In reality, the solution is far simpler and it begins by employing one of the first pillars in intelligent automation: ticket triage.
Automated ticket triage is already helping many progressive companies prevent “fire drills” that waste resources, compromise customer satisfaction, and tarnish your team’s reputation. Now, automation can determine which tickets are best handled by humans or by AI. You can optimize responses to an influx of redundant tickets alongside a handful of escalated issues. Leave those redundant tickets to AI to automate while your team performs due diligence on more complex service priorities.
The tangible ROI of triage is immediately apparent to any team under a resource crunch. Traditionally, routing necessitates a high-level agent effort. Without proper triage protocols, tickets are cherry-picked, difficult cases are skipped, tickets are lost in the shuffle, and spam inquiries infiltrate your queue.
Coordinators, dedicated solely to triage, ensure tickets are assigned to the right queues, have the correct severity level, and receive the right service level agreements. Agent triage efforts ensure that not only are customer commitments honored, but also that your system is capturing the appropriate data from every interaction.
But as you’ve probably discovered by now, this is unsustainable. Needless to say, manual triage is time-consuming; not to mention as repetitive as it is prone to human error. Herein lies one of the greatest problems plaguing the customer support industry today: current triage practices are unsustainable when up against increased ticket frequency.
“How can my company improve triage?”
A simple question that doesn’t have a simple answer. In order to improve CXM efficiency, consider the Four Steps to Successful Triage:
1. Establish Your Case Categorization Structure
2. Define Severity and Service Level Commitments
3. Establish Agent Specializations
4. Implement Workflows
Let’s explore each of these steps in greater detail to better understand how to improve triage and streamline day-to-day support team processes.
Establish Your Case Categorization Structure
There is no one-size-fits-all rule to triage ordering — that’s what makes it so tricky. Ticket categorization depends entirely on the specific needs of your organization. And yet, despite the significant variability of this step, it remains one of the most important elements of an efficient CXM.
Common categorizations include:
1. Severity — Prioritize important tickets over less pressing ones. The definition of severity can vary, so it’s important to establish a concrete rating system to make severity levels clear and actionable (more on this in the next section).
2. Customer Size/Revenue — Large customers are prioritized over smaller ones. This is especially applicable for B2B organizations.
3. Service Level Agreements — SLAs define terms between customers and support. These details can inform ticket priority.
4. Ticket Type — If your team is organized by specialty, the inquiry type would determine priority.
5. Channel — Teams that don’t train agents on multi-channel support will want to prioritize tickets according to channel (phone, email, chat, social media, etc.)
6. Product — If your organization offers multiple products it can be useful to categorize accordingly.
7. Skills-based Routing — Route tickets to specialists within the organization.
In general, top-level tickets tend to fall into these categories but almost always include sub-categories to catch all related issues:
* Product FAQs
* Account Related Matters
* Ops/Tech Support
Keep these ticket categorization considerations in mind, and identify those that are most applicable to your organization. Through this process, a support team can establish their categorization and sub-categorization structure to directly align with the customer experience.
Define Severity and Service Level Commitments
As noted above, not all support issues have the same impact on your business. Some tickets influence revenue, while others are general questions or feature requests. For this reason, it’s crucial to create a severity model tied to revenue impact and risk to inform categorization.
One of the most fundamental severity level mistakes, which is far more prevalent than you might expect, is overbroad or vague definitions. For example, if customers rate tickets according to the popular 1 – 5 scale, chances are that most customers will always classify their inquiry as a 5. After all, their question will seem most pressing to them — this model is too subjective.
Assign concrete characteristics to severity levels: “business cannot operate” is far more descriptive for the customer and agent than an abstract, subjective number.
Keep in mind, severity levels are directly correlated to SLA. Predetermined agreement terms such as response time must be honored and reflected in your severity level model. To avoid costly lapses, organizations can create notification triggers, which inform senior management when SLAs have been missed or when severity level thresholds have been crossed.
Establish Agent Specializations
In the busy day-to-day of a support center, agents have to wear many hats. While agent versatility might seem like a good thing, team productivity can actually suffer if employees are spread too thin.
Agent specializations deliver higher quality responses — agents keyed into specific expertise can better cater resolutions to customer needs. Plus, this keeps agents more engaged since they can focus on more challenging tasks and overcome redundant, repetitive tickets.
Expert agents unfettered by attrition can only lead to one thing: a better, more accurate support experience for you customers. But how do you find the time to train agent specialties?
It all goes back to quality triage — proper ticket routing is the foundation for any effective CXM. Effective triage enables agents to best utilize their skill-based routing toolkits in CXMs.
The final, and possibly most important, step toward effective triage is to establish agent workflows.
After completing the previous steps, you can piece everything together to create agent workflows, training materials, and guidelines. These processes will act as the foundation for all support interactions going forward. And, with all of the preceding groundwork established, you can rest assured that productivity improvements compounded into a more sustainable, more efficient CXM.
Agent workflows are the culmination of your efforts thus far and essential to solving customers’ most pressing issues.
How AI Improves CXM Triage
Given all the steps outlined above, you probably have more questions.
The key to effective CXM triage is simple: machine learning technology. Triage is one of the first AI features a customer support team can implement. It is easy for AI to learn ticket intent and route to the correct agent thanks to Natural Language Processing (NLP) technology.
NLP is used to understand customer intent by interpreting words as if the computer were a human. The right support system can read between the lines and extrapolate meaning from colloquialisms, slang, and language nuances–it can even detect 16 different languages and route to the appropriate specialist.
Triage powered by NLP is well-equipped in detecting spam and understanding query content to ensure the right ticket gets to the right agent.
AI for customer support sets your team up for success throughout the entire customer journey. Other benefits to automatic triage include:
* Sentiment analysis on every incoming ticket, which improves routing accuracy and is core to delivering severity and emotional matching – the “human elements.”
* Language detection – up to 16 languages
* Triage based on standard and custom fields
* Insightful data analysis tools such as confusion matrices. This helps your team identify which categories have poor coverage, better understand the customer journey, and eliminate redundancies.
Triage removes the possibility of human error and relieves agents from the redundancy of manual ticket categorization. This frees up agents to do what they do best: provide customers with useful, memorable support.