1. Discussion of Dynamic Pricing in MLB
May 2014

2. 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)

3. Demand Drivers in Sports
Tune the channel:
Economic factors
Game by game factors
Marketing and pricing tactics
Change the channel:
Team Performance

4. Season Tickets Demand

5. 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

6. 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

7. 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

8. Pricing Strategy 1 3 2

9. 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

10. 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