Inside King County Metro's redesign: predicting ridership impact in Remix

Start watching on-demand. 

An overview.

What if you could see the impact of network changes before you put them into motion?

King County Metro did exactly that by piloting Remix’s new travel demand tool, Ridership Modeling—powered by Citymapper’s real-world mobility data. The result: a more rider-centric network shaped by actual travel behavior and AI-driven forecasts. This webinar walks you through how you can model demand, visualize travel patterns, and predict ridership impacts—all within the Remix platform you already know and love. 

• Use ridership data to make better decisions: How to turn hyper-localized ridership data into smarter planning decisions.
• Analyze rider impact before you launch: How King County Metro used Remix Ridership Modeling to forecast the impact of a major redesign on access, demand, and ridership.
• Connect your MaaS and planning strategy: How a new approach to Mobility-as-a-Service (MaaS) can elevate your planning strategy.

Curious to learn more? Take a look at the full King County Metro story here.

About the speakers

Melissa Gaughan

Senior Business Analyst, King County Metro

Melissa is a Senior Business Analyst at King County Metro, where she leads work on analytics, data tools, and process automation. She’s known for turning complex datasets into clear, actionable insights and for supporting teams across the agency as they adopt new technology and data-driven workflows.

Tobias Bartsch

VP of Data Science, Via

Tobias serves as Via’s VP of Data Science, guiding the development of the predictive models and optimization tools that underpin thousands of daily transit decisions. His work helps agencies understand rider behavior, improve service performance, and deploy resources more effectively.

David Frances

Director of Product Management, Via

David is the Director of Product Management at Via, where he leads the Citymapper product. He oversees the vision and development of tools that help riders plan journeys seamlessly and help cities understand real-world mobility patterns.