Founder & CEO at Thrill Analytics
Episode #001 February 5, 2026
Marcus Chen combines a deep passion for theme parks with expertise in artificial intelligence and data science. After spending a decade at Google leading machine learning projects, he founded Thrill Analytics in 2019 to revolutionize how attractions understand their guests.
Growing up in Southern California, Marcus spent countless weekends at Disneyland and Knott’s Berry Farm. These childhood experiences sparked a lifelong fascination with how attractions create emotional connections. “I always wondered why some rides had 90-minute waits while others were walk-on,” he recalls. “That curiosity eventually led me to build tools that help parks answer these questions.”
Thrill Analytics now serves over 200 attractions across 30 countries, from major theme parks to regional zoos and aquariums. The platform uses anonymized mobile data, weather patterns, social media sentiment, and historical trends to predict attendance, optimize staffing, and identify emerging guest preferences.
Marcus has been named to Forbes’ 30 Under 30 in Enterprise Technology and was recently recognized as one of Blooloop’s 50 Theme Park Influencers. He holds a Ph.D. in Computer Science from Stanford University and three patents in predictive analytics.
A self-proclaimed “coaster enthusiast,” Marcus has ridden over 400 roller coasters worldwide and maintains a personal ranking spreadsheet that his colleagues describe as “obsessive but impressive.”
Marcus Chen explains how artificial intelligence is transforming attraction operations. Learn how parks are using predictive analytics to forecast attendance, reduce wait times, and personalize the guest journey. Marcus shares real case studies showing 20%+ improvements in operational efficiency and discusses the ethical considerations of using guest data responsibly.
Host: Welcome back to Attractions Insights. I'm thrilled to have Marcus Chen with us today. Marcus, you've built a company that essentially helps parks see the future. How does that work?
Marcus: [laughs] We're not quite fortune tellers, but we're getting close. At Thrill Analytics, we aggregate dozens of data signals – historical attendance, local events, school schedules, weather forecasts, even social media buzz – and our AI models find patterns that humans simply can't see.
Host: Give us a concrete example.
Marcus: Sure. One of our clients, a major waterpark, was staffing based on day-of-week patterns. Saturdays were always fully staffed, Tuesdays were skeleton crews. But our system noticed something interesting: when the forecast showed rain on Saturday followed by sunny Tuesday, attendance actually flipped. People avoided the rainy weekend and came Tuesday instead.
Host: So you helped them adjust staffing?
Marcus: Exactly. Now they get recommendations 72 hours out. In that first summer, they reduced labor costs by 18% while actually improving guest satisfaction because wait times for food and attractions went down.
Host: Let's talk about privacy. There's a lot of concern about data collection. How do you address that?
Marcus: Privacy is foundational to everything we do. First, all our data is anonymized and aggregated. We don't track individuals – we track patterns. Second, we're transparent with guests. Parks using our platform add clear disclosure to their apps and websites. Third, we follow strict data minimization principles. If we don't need it to improve the experience, we don't collect it.
Host: That's reassuring. What's next for the industry?
Marcus: I'm most excited about real-time personalization. Imagine an app that learns your preferences and suggests your perfect day – the right mix of thrills, shows, and dining – optimized to minimize walking and waiting. We're already piloting this with three parks, and early results show guests are 40% more satisfied with their visits.
