Read this Fireside Chat recap to learn how KOHO went from 1% of their support interactions QA’d to 100%, improved their CSAT and overhauled agent efficiency by auto-tagging tickets and uncovering topics with TheLoops AI Intercom integration.

Quality assurance has always been a priority when it comes to Customer Support. For the majority of Support leaders, this particular function has also come with its own limitations and constraints.

• Only a small percentage of interactions can ever be assessed for quality assurance purposes
• Be it 1%, 3% or 7%, this sample size of customer interactions isn’t thorough or varied enough to spotlight all issues
• Gaps persist reinforcing the issue of lower performing agents lacking timely, relevant coaching and course correction to help them improve where they fall short
• Customer frustration or delight may not be captured consistently and is likely missed due to low response from CSAT surveys

With the rise of GenAI adoption and functionality specific to CX, automated quality assurance for customer support is quickly replacing traditional QA programs with good reason.

Monika Aufdermauer, VP of User Success at KOHO, sat down with TheLoops to share her team’s personal success story and how the rollout of TheLoops Platform, complete with Auto QA, helped her resolve 3 persistent gaps within her support organization leading to $400k in cost savings, data-driven collaboration with her product team and a decrease in ticket volume from 15% down to 11%. 

As more Support, Success and Customer facing leaders evaluate their AI options, Monika’s takeaways offer key things to consider, touching on how the AI of yesteryear is nowhere near the same as the AI of today. Let’s dig into the specifics she shared to help you and your team.

Takeaway 1: There’s tangible, measurable, immediate impact from Auto QA

KOHO, like many support teams, was working hard to ensure customers were met with quality that matched or exceeded their standards and expectations. However, working hard wasn’t necessarily the same as working smart.

With only 1% of interactions under evaluation and monitoring, gaps that were especially prevalent in their chat bot interactions went undetected, leaving customers frustrated and dissatisfied. As an AI pioneer and early adopter, Monika quickly realized she had put the cart before the horse.

If I had to go back and do it all over again, granted the technology and AI for CX ops did not exist at the time, but if it had, I would’ve focused on fixing the operational issues first and improving agent efficiency versus ‘experimenting’ with the customer facing AI, relying on so much manual work (tagging and routing) and having things fall short of our standards.

After Monika met TheLoops CEO+Co-Founder Somya at an AI event, she soon understood TheLoops capabilities and was able to discern that her CX ops and quality assurance were ripe for an overhaul. In less than 90 days of implementing TheLoops, the team at KOHO went from 1% of tickets QA’d to 100% but that wasn’t all. CSAT also jumped up from 4.1% to 4.6%.

“100% automated quality assurance from TheLoops helped us really truly see where training could be provided–and we could dig further into specifics and gaps much quicker at scale.” As an added bonus, Monika also emphasized just how easy and fast this specific form of AI was to deploy.

This ease of use and immediate adoption across CX soon found its way to breaking down another blocker: alignment with the product team. That leads us to takeaway number two from the fireside chat.

Takeaway 2: Automated Quality Assurance And AI Helps Build A Bridge of Alignment with Product Teams

The disconnect between support and product teams is a classic CX conundrum. Manual work, perceptions of reliance on “gut hunches” and competing priorities often trump attention and collaboration, leading to misaligned roadmaps and frustrated customers. KOHO knew this playbook all too well.

“We knew what our challenges and issues were–we had it all there qualitatively. But it wasn’t until we were able to show the product team, in real-time, the correlation between issues, bugs, and feature requests that our data was validated and we were taken seriously.”

Real-time data in the form of topics, subtopics and sentiment on every customer interaction became a shared language. “What changed was what you reported on. It was not just doing the same old, same old top order metrics that you would spend hours on, TheLoops AI helped you get down to the next level of metrics really speaking to business outcomes”, Somya added.

With this newfound clarity, TheLoops’ insights led KOHO to complete an overhaul of their transaction feed, eliminating a major pain point for users. Real-time sentiment analysis became their early warning system, allowing KOHO to identify at-risk customers and intervene before they even reached out with an issue. “Why wait for someone to be upset?” Monika cautions.

“With TheLoops, we now predict CSAT as well. From product to the front line, we’re ensuring visibility and that our customers are always delighted.” Which leads us to takeaway number 3.

Takeaway 3: The Initial Culprit Was Manual Work and Processes: Automation and AI Improved Everything

Change is always an uphill battle but it shouldn’t be especially in CX where you can improve your team’s productivity, uncover $400k in savings and prevent mistakes and errors from happening in the first place. Due to limitations within ticketing solutions, particularly when it came to understanding case drivers and auto-classifying and routing tickets, KOHO’s efficiency killers were like a domino.

Agents were overwhelmed and multi-tasking (and tagging), customers were growing more impatient, and frustration was building. As a result, the numbers were fluctuating until the KOHO team made a startling discovery. Thanks to TheLoops topic modeling, they were quickly able to see that some customers were filing duplicate tickets.

“We couldn’t believe it when we uncovered it, but as soon as saw the duplicates and fixed them, we went from 15% to 11% and reduced overall conversations,” Monika revealed. “TheLoops identified these hidden inefficiencies, allowing us to route queries faster and free up our agents to focus on what they do best – delivering exceptional customer experiences. We were sold and wanted more capabilities right then and there.”

This reinforced one of the final points Monika really wanted to drive home. Consolidating technology is the way to go, particularly when you embrace a predictive AI platform that can handle multiple CX use cases and needs.

“AI isn’t here to steal jobs; it’s here to make them more impactful. This technology is about augmenting human capabilities, not replacing them.”

If you and your team are ready for a similar success story to KOHO’s, we’d be happy to chat with you and show you a demo of TheLoops today.

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