Ticketmaster gives millions of fans – worldwide – fair and easy access to the biggest and best in live entertainment. Driven by innovation, unparalleled scalability, and unmatched support, Ticketmaster is the definitive leader in professional ticketing solutions. Over 12,000 artists, teams, and venues around the world trust Ticketmaster to power their amazing performances daily — with more than 500 million tickets sold each year.
Sales/Marketing Technology
5k+
Beverly Hills, CA, United States
Ticketmaster needed a way to handle high-volume questions quickly and accurately. They created an agent, but wanted a better understanding of how it was being used.
With Pendo’s Agent Analytics, Ticketmaster could speed up the process of understanding performance with a clear, data-backed view that was available to everyone.
After using Agent Analytics, Ticketmaster retained 81% of users leveraging their agent.
When you think of high-demand ticket sales, you’re thinking about Ticketmaster. Behind the scenes, those moments depend on fast, informed decisions from internal teams operating under intense pressure.
As a Product Manager at Ticketmaster, Brian Muehlenkamp felt that pressure on a daily basis. He was always getting hit with many questions without immediately accessible answers.
Ticketmaster’s internal teams are packed with domain experts. But even experts need data—constantly.
“How is this sale performing compared to benchmarks?”
“What happened last time we ran something similar?”
Before AI, getting those answers fast was challenging. Teams either filed requests with data providers or tried to dig through systems themselves. So Muehlenkamp introduced an AI agent directly into their internal tools giving users a faster path from question to insight. Instead of writing SQL or submitting tickets, teams could ask questions in plain language and get immediate answers.
That shift helped Ticketmaster move closer to what Muehlenkamp calls “data democracy”—making insights accessible to anyone who needs them.
But launching the agent created a new challenge: measuring its impact.
Initially, Muehlenkamp relied on raw audit logs. He could see conversations, but not who was asking the questions, how behavior changed over time, or whether the experience was improving.
Going through the audit logs was a time-consuming and manual process.
Leadership wanted to know a simple thing:
Was the agent actually helping?
Anecdotal feedback from early users was positive. But that wasn’t enough. Muehlenkamp needed a clearer, data-backed view, especially to uncover silent friction from users who weren’t speaking up.
With Pendo Agent Analytics, that visibility gap closed quickly.
Instead of digging through logs, Muehlenkamp had immediate access to metrics that showed both usage and impact:
Some of the most valuable insights were the ones he didn’t know to look for, saying, “Agent Analytics surfaced insights that I may or may not have known I needed.”
One standout example: a surge in questions about queue metrics (the number of users waiting during high-demand sales).
That insight gave Muehlenkamp a clear direction. He improved the agent’s responses for that specific theme, increasing accuracy where it mattered most.
Instead of guessing where to invest, he could prioritize based on real usage patterns.
Agent Analytics didn’t just improve answers, it improved the entire product experience. By tracking user behavior around the agent, Muehlenkamp identified:
That last insight led to a quick fix: users expected a button to close the chat panel, but it didn’t. Once that dead click was identified, the team prioritized and resolved it immediately.
These small improvements added up making the agent feel more intuitive and better integrated into daily workflows.
Ticketmaster started with a controlled rollout—about 30 to 35 power users who were already excited about the tool.
The results were promising, but scaling required proof. With Agent Analytics, Muehlenkamp had it.
He could clearly demonstrate that:
That visibility gave him the confidence to expand access much faster than planned—moving from a small cohort to an opt-in model across a broader user base.
“What Agent Analytics gave me was conviction… and the confidence to roll it out faster.”
By pairing AI agents with Pendo Agent Analytics, Ticketmaster achieved:
The key to strong product confidence is that it must be supported by real user behavior. Together, these outcomes helped Ticketmaster operate more efficiently, reduce wasted effort, and empower teams to act faster—key drivers of both cost savings and operational performance.
For Muehlenkamp, one of the biggest advantages of Agent Analytics is how it accelerates learning in a space that’s still very new and evolving daily.
“There’s no one with 10 years of AI agent experience. It just doesn’t exist.”
Instead of relying on assumptions, product teams can use real data to understand intent, measure impact, and continuously improve.
His advice to other product managers?
“Build it yesterday.”
