McKay Borbon | Content Marketing Manager
"KPIs help CX leaders tell a story, not only for their team but for their brand."
- Katie Scruggs, Senior Customer Service Manager.
Resolve more tickets in less time.
Scale support with a reduced headcount.
Cut customer wait times during peak season.
If you’re a CX leader, you’re likely no stranger to the expectation of having to do more with less. Not only does the strain impact you and your agents on a day-to-day basis, but the pressure of hitting your KPIs is always looming overhead.
While clear goals, skilled agents, effective processes, and customer-centric strategies are essential for attaining key performance metrics, it is not always enough. And when spikes in ticket volume, seasonal rushes, and rapid growth strike, even the most productive service organizations and highest-performing agents are faced with the challenges of scaling.
The reality is that there is only so much an agent, support team, and contact center can handle at a time before wait times increase, a backlog builds, resolution rates drop, and customer satisfaction declines. It’s a domino effect that is difficult to bounce back from.
To improve efficiency, streamline operations, and alleviate the pressure their agents are under, many CX leaders are augmenting their service organization with AI-powered customer support automation.
Since AI does not have a ticket capacity, it can easily handle high ticket volumes and respond to customers within seconds. With the ability to accurately resolve more tickets at a greater speed, support teams that leverage AI automation tools are better equipped to hit (and even surpass!) their KPIs.
Thankful spoke with CX leaders from some of the top ecommerce brands about their most important customer service metrics and how AI automation helped them achieve their performance goals.
Here are the KPIs CX leaders are crushing with AI. 👇
The longer a customer has to wait to be connected to and get a response from an agent, the more dissatisfied they are likely to be. In many ways, the initial response sets the tone for the entire service experience. That’s why TTFR is a critical customer service metric for many CX leaders - including the VP of Customer Happiness at Bombas, an in-demand mission-driven apparel brand.
Considering the CX team is referred to as the Customer Happiness Team, it is not surprising that Bombas really values customer happiness. So much so that they have a really great Happiness Guarantee policy that covers free returns with no time limits. The customer-centric policy has one downside; it was inundating the Customer Happiness Team with time-consuming return and exchange tickets which negatively impacted wait times.
To streamline the return and exchange process for agents and customers, the VP of Customer Happiness implemented AI Agent, Thankful’s AI automation solution. With AI Agent handling returns, exchanges, and other transactional tickets, the Customer Happiness Team’s overall TTFR dropped by 81%. 
The Head of CX for a popular men’s skincare brand also saw a significant reduction in her support team’s TTFR thanks to AI automation. Even during hypergrowth and spikes in ticket volume, the team was able to decrease the first response time by nearly 17 hours; 16 hours and 54 minutes to be exact.
CX leaders can rest easy knowing that customers, especially those with time-sensitive inquiries, are able to get the help they need when they need it.
Many CX leaders agree that one of the most important KPIs is average handle time (also known as “time to resolution”); the measurement of how long it takes for an agent to handle a query from start to resolution. The quicker customers are able to have their problems solved, the happier they will be - and the sooner the next customer can be helped.
Not only does AI automation reduce wait times by providing customers with fast responses, but the most advanced solutions actually have the ability to quickly and accurately resolve tier-one ticket types with no human involvement. And thanks to its unmatched speed and scaling capabilities, AI makes it possible for CX leaders to achieve a solid AHT even when there are influxes in ticket volume.
In addition to reducing Bomba’s Customer Happiness Team’s TTFR by 81%, leveraging AI automation helped decrease the team’s AHT by 35%. “The technology saves our agents time and gives us the ability to manage spikes in ticket volume really well,” Bomba’s VP of Customer Happiness says.
The Customer Success Manager for Pura Vida, a wildly popular and charitable accessories brand also had success leveraging AI automation to reduce wait times amidst momentous hypergrowth. At the time the CSM partnered with Thankful, Pura Vida’s ticket volumes were up 147%. Fully resolving 30% of track order requests and over 50% of missing package requests among other common customer issues, AI Agent helped the team keep up with the high demand. The result? A 55% reduction in customer wait times! That’s something a support team, upper management, and customers will all be happy about.
Ticket resolution rate is perhaps the strongest indicator of the efficiency of a service organization and the effectiveness of the support that is being provided. It is also commonly used when determining if a brand’s Service Level Agreement (SLA) is being met or not. Needless to say, it is a highly important metric that CX leaders are held accountable for. This is why AI automation is most commonly sought out by service organizations that do not have the bandwidth the handle the number of incoming tickets.
The amount of tickets AI automation can take on varies based on how CX leaders’ goals and how they choose to optimize the technology. Here are some examples of AI Agent’s resolution rates that have contributed to the improvement of overall resolution rates across different support teams.
One of the best benefits of AI automation, especially in regard to resolution rate, is that it scales alongside brands. This makes resolution rate goals more attainable even during the busiest and most difficult of times.
When a large merchandise brand was hit with brutal external delays that coincided with peak season, their already high ticket volume increased by 265%. Fortunately, an AI Agent was already onboard and was able to scale its own resolution rate by 400%. It made the months leading up to and following busy season more manageable, alleviated some of the pressure human agents were under, and helped keep the team’s performance metrics on track.
Your support team is hitting your target TTFR, AHT, and resolution rates - but are your customers satisfied with the service they are receiving? No customer is going to object to quicker responses and faster accurate resolutions - in fact, that’s a must-have by today’s customers’ standards. But if you’re questioning automation’s ability to achieve high CSAT scores, rest assured that human-presenting AI technology like an AI Agent has a great track record when it comes to delivering service that meets customer expectations. We’re talking 99% CSAT scores!
Rather than telling you about the quality of support AI Agent delivers, we’ll let real customers tell you.👇
This article opened with some of the initiatives CX leaders have likely had placed upon them at some point in their careers. Are these expectations excessive? Of course. Frustrating? Absolutely. Possible? Yes - with the right technology.
Let’s recap. With AI automation you can...
✅ Resolve more tickets in less time
✅ Scale support with a reduced headcount
✅ Cut customer wait times during peak season
And don’t forget…
✅ Crush your KPIs
To learn how generative AI automation can help you achieve your specific goals,
McKay Borbon | Content Marketing Manager
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