Alorica + CallMiner Case Study

When a top wireless company was struggling with inconsistent customer experiences, they turned to Alorica and CallMiner for help. Using AI to analyze conversations, every customer call became more genuine and effective.

When you’re running a nationwide wireless network, customer conversations happen around the clock. For this top American wireless network operator, those conversations weren’t going as well as they should.

The numbers told the story: both customer and agent sentiment were inconsistent across contact centers. Some agents could flip an angry customer calling about surprise fees into a positive experience. Others handling the exact same situation? Well, not so much.

“We had agents dealing with payment arrangements and insurance protection calls all day,” says the wireless company’s operations team. “These are our most common call types, but they were becoming sources of frustration instead of opportunities to build loyalty.”

As a long-standing client of Alorica’s, the wireless company turned to them to help with data-driven insights, but this time it was more complicated – agent satisfaction scores were both lower than expected and strangely inconsistent.

Without understanding why scores varied so much, Alorica couldn’t target their coaching for their quality assurance (QA) program effectively. What were some agents doing to turn negative calls into positive ones? And why were certain interactions going wrong?

“We were giving broad feedback that has traditionally worked in the past, but this needed a more targeted approach,” the Alorica team explains. “We needed to get specific.”

Listening to every conversation

Alorica analyzed 100% of customer interactions using CallMiner’s AI-powered conversation intelligence platform to help diagnose the root cause of inconsistencies. The team used AI classifiers within CallMiner, which leverage large language models (LLMs), to automatically label the context of customer interactions.

“We needed to understand the difference between a good call and a bad call,” says the CallMiner team. “Not just overall – it was important to know exactly what words, what tone, what approach made customers happy or upset. The ability to know that would be indispensable.”

Once the low performing interactions were effectively categorized, the team used CallMiner’s semantic search capabilities to find what was causing low and inconsistent scores. Using generative AI, analysts could ask questions in natural language and get the full context from millions of conversations instead of hunting for keywords.

AI accelerated Alorica’s ability to discover these root causes. What used to take weeks of manual analysis now happened in real time, giving them immediate insights to improve agent performance. The first major discovery? Unexpected fees were driving most negative experiences. But here’s what surprised everyone: it wasn’t the fees themselves that upset customers.

“We found that two agents could handle the exact same billing issue,” explains the Alorica team. “But one would leave the customer feeling satisfied and the other came up short. It was the same situation, but the big difference – was empathy.”

Agents who simply acknowledged their frustration first and said things like, “I understand how unexpected fees can be frustrating,” consistently scored higher, even when the charges were justified. But agents who jumped straight into explanations scored lower every time.

Small changes, big results

The insights kept coming. CallMiner’s AI identified specific language patterns that either helped or hurt an agent-customer relationship. The real magic happened when Alorica provided contact center teams with empathetic coaching tools. Instead of generic feedback, they could point to exact moments in high-performing calls with CallMiner.

“We’d show agents things like, ‘Listen to how Sarah handled this billing question,’” explains a supervisor. “What really stuck out to me was watching agents actually start to enjoy the tough calls,” says the supervisor.

“You could see it – they’d hang up after turning around an angry customer and just light up. That feeling of making someone’s day better? That’s what this was all about.”

“Notice how she acknowledged the customer’s frustration before explaining the policy? That’s what made the difference.”

The results were immediate. In less than one month, eNPS scores jumped from 60 to 80 as teams embraced empathy-focused coaching. But the most rewarding outcome was personal: 4.7% of agents in Q4 2024 moved into being top performers – just a few months later in Q1 2025.

“What really stuck out to me was watching agents actually start to enjoy the tough calls,” says the supervisor. “You could see it – they’d hang up after turning around an angry customer and just light up. That feeling of making someone’s day better? That’s what this was all about.”

Making every conversation count

Today, the wireless company uses Alorica’s data insights expanded with CallMiner AI to continuously refine customer experiences. With AI classifiers and semantic search, supervisors can spot coaching opportunities with data in real time and can quickly identify other sources for potential customer dissatisfaction.

“It’s changed how we think about customer service,” says the operations team. “We’re not just reacting to problems anymore – we’re preventing them. Every conversation is a chance to build loyalty.”

The partnership between the wireless provider and Alorica expanded, with plans to take CallMiner’s AI insights to the next level. Imagine every single agent interaction automatically tagged with specific coaching tips, or highperforming agents getting instant recognition for great work.

“AI has fundamentally changed our approach to coaching,” says the Alorica team. “We can now identify what works in real time and turn those insights into immediate action. It’s not just about fixing problems; it’s about celebrating success and replicating it across the entire team.”

Today, Alorica ranks #1 for performance with the wireless provider. For their team, the whole experience shows what happens when you combine AI with real customer experience expertise. But it’s not just about understanding data in conversations, it’s about making an impact.

When you can take someone who’s struggling and help them become a top performer in three months? That’s when you know you’re onto something big.