Success Story

Inside Stanford Athletics' New Revenue Engine

How AI-Driven Dynamic Pricing Captures 19.4% of Stanford Athletics Ticket Revenue, Powered by vivenu and WMT Digital

From Static Pricing to Real-Time Ticket Intelligence

The Challenge

For years, ticket pricing across industries, including college athletics, has been constrained by outdated systems that couldn’t keep pace with real-time demand. Pricing adjustments were blunt, manual, and often left revenue on the table.

For Stanford Athletics, this meant relying on broad blocks of seats grouped into Price Scales or Price Levels, where dozens or even hundreds of seats shared the same static price. Updates weren’t fully automatic, which required constant oversight. On top of that, Stanford Athletics lacked granular control over distribution, with little ability to manage how inventory flowed between primary and secondary markets

This created two major gaps:

  • Revenue left on the table because pricing couldn’t reflect true market demand down to the row;
  • Limited control over distribution, making it harder to manage inventory strategy across all marketplaces.

The Solution

To solve these challenges, Stanford Athletics’ primary ticketing provider, vivenu, partnered with WMT Digital to bring the best of both worlds: a modern, flexible ticketing system combined with an AI-driven pricing and distribution engine that gives organizations complete control of ticket value.

This integration delivered:

  • Dynamic micro-pricing down to the row level, ensuring every seat reflected real-time demand;
  • Automated, intelligent adjustments, eliminating the inefficiencies of manual price updates;
  • Granular control over distribution, allowing Stanford to manage how much inventory was sold on primary vs. secondary markets;
  • Near real-time data via vivenu APIs, powering faster, smarter pricing decisions.

A Higher Value Per Seat

Stanford Basketball

  • 19,4%

    Total ticket revenue driven by dynamic pricing

  • 872K

    Automated, seat-level price changes

  • 242

    Hours of manual pricing eliminated (equivalent to 26 work days)

  • 24%

    Increase per ticket on average

Revenue at Stadium Scale

Stanford Football

  • 12%

    Total ticket revenue driven by dynamic pricing

  • 3.9M

    Automated, seat-level price changes

  • 194

    Hours of manual pricing eliminated (equivalent to 24 work days)

  • 14%

    Increase per ticket on average

For years, ticketing was rigid. This collaboration proves that when you provide programs with API-first technology to price every seat intelligently, you unlock significant hidden value while freeing staff to focus on strategy rather than data entry.

Chris Freet

Chief Strategy Officer at WMT Digital

WMT Digital + vivenu

Stanford Athletics' breakthrough came from the integration of vivenu's modern ticketing revenue engine with WMT's AI-powered pricing models. Instead of static scales and delayed adjustments, the combined system delivers.

  • Real-time intelligence via APIs

    Every sale, demand signal, and inventory update flows instantly into WMT’s pricing model, ensuring no opportunity is missed.

  • Row-level precision

    Tickets are priced based on actual market conditions, creating value where static blocks once left money on the table.

  • Unified marketplace visibility

    Primary and secondary sales can be managed side by side, giving Stanford Athletics full visibility and control of distribution and pricing strategy.

  • Adaptive optimization

    Whether the goal is to maximize revenue, drive attendance, or balance both, the platform shifts automatically to match strategy.

WMT Digital + vivenu

About WMT Digital

WMT Digital gives organizations complete control of ticket value, using AI to adjust prices, optimize distribution, and unlock new revenue in real time. Its proprietary models use demand data to power precise, dynamic pricing in live events.

The Result

A new way to run ticketing for live events. Faster, smarter, more profitable. Every seat priced to its true market value, in real time.

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