Discussion of Dynamic Pricing in MLB May 2014
History of Ticketing 500 B.C.: In Turkey and Greece, clay, bone or metal pieces were used as tokens to admit customers to theater events 100 A.D.: Roman Coliseum used clay shards as admission tickets 1754: Benjamin Franklin printed tickets for a theater in Philadelphia 1994: Bar code ticketing introduced (Cleveland Indians) 1996: Internet sales introduced (Seattle Mariners) 2000: Print-at-home tickets introduced 2007: Paperless / mobile tickets introduced 2009: Dynamic pricing introduced (SF Giants)
Demand Drivers in Sports Tune the channel: Economic factors Game by game factors Marketing and pricing tactics Change the channel: Team Performance
Season Tickets Demand
Dynamic Pricing in MLB Dynamic pricing means that once a ticket goes on-sale its price is subject to change Market conditions American lifestyle changes (time and convenience) Buyer power (knowledge and access) Technology Ticketing system advancements Data and analytics capabilities
How is Dynamic Pricing used? Strategy Algorithm Execution 3 Common Approaches: “Buy Early and Save” Match supply and demand Price flatten Algorithm Inputs (proxy for elasticity): Team performance (expectations) Day of week / time of year Opponent Economic factors Secondary market data Promotions / special events Price Change Methods: Daily, weekly vs a few times per year Game day premium Sales channels Manual vs automated
Purchase Behaviors 50% of Indians single game ticket revenue comes from transactions within 4 days of the game and 34% comes from transactions on game day
Pricing Strategy 1 3 2
Learnings from Dynamic Pricing Dynamic pricing is still relatively new in MLB and teams are still learning, but teams generally have found around a 10% increase in revenue Business Impact Higher demand games have generally been underpriced and lower demand games are generally overpriced (larger pricing fluctuations over time) 70% of incremental revenue in top 10 games per year 70-80% of games are lower priced on average Capitalize on unforecasted demand (e.g., milestone game or postseason run) Limited impact on number of tickets sold (incremental growth from more efficient pricing) Drive fans to specific seating locations Smaller walk-up crowds Fan Impact More value for season ticket holders – average discount for a season ticket holder increased from 22% to 46% Most fans understand the practice from other industries (e.g., airlines, online consumer products) Some fans can react emotionally and sense a lack of trust with the team
Challenges and Next Steps Understanding elasticity More customer level data (digital tickets and customer profiles) Elasticity by customer type and across price categories Technology Mobile entry adoption Link between pricing algorithm and ticketing system Communication Fan knowledge and understanding of pricing strategy Reinforce trust between team and fan Talent IT and analytics skill sets