Playing defense, not offense
Malik, a longtime Chargers fan in Los Angeles, had been eyeing a new jersey all season. After a few solid wins and a birthday coming up, he finally went for it, ordering one of his favorite players' jerseys with expedited shipping so he could wear it to a Sunday watch party.
But just days after it shipped, news broke that the player had been traded. The jersey still arrived, still crisp, still wrapped, but suddenly outdated. Malik called Fanatics hoping for a quick return and maybe a chance to reorder. Instead, he found himself stuck in a voice system that didn’t understand him. He said “return.” Then “wrong jersey.” Then tried pressing zero. By the time he reached an agent, he was already frustrated and wondering if he should’ve just ordered from somewhere else.
Malik’s experience wasn’t unusual. Despite years of investment in a homegrown voice bot, Fanatics struggled to contain calls and meet expectations, especially during high-pressure moments. Their agents, proudly called “athletes,” worked across nine global regions in eight languages. But seasonal spikes often pushed headcount from 300 to over 1,200, and delivering a consistent experience at scale became nearly impossible.
When the company’s CEO had a similar call fail, the mandate was clear. Fix the experience fast. And don’t build. Buy.
Turning the game aroundÂ
Nigel Ponds, Fanatics’ Global Director of Workforce Management, launched an RFP and selected Replicant’s AI agents as the foundation for a more modern self-service experience. The goals were clear: reduce friction for fans, ease the burden on athletes, and drive meaningful improvements in satisfaction and efficiency.
Within months, the team saw a significant increase in containment and more than doubled their customer satisfaction scores. The results came faster than expected, prompting leadership to raise the bar even higher.
But Fanatics didn’t just implement Replicant’s platform. They helped build it.
During a candid conversation with Replicant CEO Gadi Shamia, Nigel shared that their quality management tool was falling behind. It was slow to update, expensive, and unable to flag issues like background noise or unclear speech. Within a week, the Replicant team responded with an early version of what would become Conversation Intelligence.
“We muted the phone because we couldn’t believe it,” said Nigel. “We ran real calls through the tool and it caught everything - mumbling, background noise, heavy accents. It was exactly what we needed.”
That feedback loop helped shape the product roadmap and positioned Fanatics as a design partner in bringing the tool to life.
Coaching with clarity, acting with speed
With Conversation Intelligence in place, the team uncovered major opportunities for improvement. Roughly a third of calls had incomplete or inaccurate wrap codes, which made it difficult to understand why fans were reaching out. Now, every interaction is tagged automatically, and the team is working to push those insights into their CRM to streamline workflows and reduce handle time.
Leaders can now coach at the individual level instead of reacting to team-wide trends. What once took hours of manual analysis can now be done in minutes.
The insights also revealed where fans wanted more control. Based on that feedback, Fanatics launched a pilot to extend cancellation windows and is planning to roll out new self-service purchase options in the near future.
Built to scale, poised to win
Today, when customers like Malik call with a return or cancellation request, Replicant’s AI agents answer immediately. Calls are resolved in seconds. If human help is needed, the call is routed with context already captured - no repeats, no confusion, no frustration.
The contact center runs more efficiently. Athletes feel more supported. And fans get the experience they expect from a brand built on loyalty and speed.
As the team ramps up for peak season, they’re more prepared than ever. Replicant helps Nigel and his team work smarter, not harder. They’re delivering consistent experiences at scale, identifying friction faster, and uncovering new ways to reduce inbound volume.
