Ticketmaster · Ticketing and pricing dataModernized the data underneath every ticket.
In ticketing, the data underneath is the product. I owned requirements and delivery for event data and seat-level pricing in an 8 to 12 person pod.
Who we built for.
A fan buying a ticket, and the pricing and event teams publishing the data behind it.
See the seat they can buy, at the price they will pay.
A high-demand event where seats and prices can change quickly.
Accurate price and availability at high volume, for every experience built on the platform.
What got in their way.
- 01TrustThe fan has to trust the seat, availability, and price before committing.
- 02Time pressureChanging inventory amplifies uncertainty.
- 03Moving systemsConnected systems were being modernized while fans bought tickets.
One system, four moves.
- Distribute
Move event data at scale.
Kafka NextGen Phase 4 · Event Details Page
- Price
Price at the seat.
Whole House Pricing · Seat-level pricing encoding
- Sync
Change connected systems in phases.
DCM runs across HOST and MFX · MFX Phases 2 and 3
- Sell
Sell on data that agrees.
Accurate price · Accurate availability
What we prioritized, and what it cost.
In ticketing, the data underneath is the product. Pricing only works for fans when inventory, pricing, and event data agree.
- Event-data distribution and seat-level pricing first
- Deliver the platform work in validated phases
- Visible features, for platform work
- A shorter timeline
What we believed, and what moved.
Pick an assumption to see how we tested it.
Priced at the seat, not the section. Toggle the map.
A sketch of seat-level pricing. Not Ticketmaster data.
Everything that shipped.
- Event Details Page requirements and delivery
- Kafka NextGen Phase 4
- Whole House Pricing
- Seat-level pricing encoding
- DCM runs across HOST and MFX
- MFX Phases 2 and 3
Tools and methods.
- Kafka NextGenPlatformEvent-data distribution at scale
- Acceptance criteriaTestingTechnical stories engineering could build and verify
- DCM runsTestingChecks across the HOST and MFX systems
- Phased releasesDeliveryPlatform changes validated phase by phase
- Trigger checksTestingBackend checks for event and pricing triggers
- JiraDeliveryBacklog, sprints, and release tracking
What moved.
- Event dataOn a more scalable distribution layer
- Seat-levelPricing encoding
- Whole HousePricing
Additional platform-scale outcomes available on request.
Building a ticketing, pricing, or platform product?
I lead product strategy and delivery with cross-functional teams across growth, retention, monetization, and customer experience.
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