What factor beyond pricing might impact customer willingness

Reference no: EM133544316 , Length: word count:2500

Sport Business Analytics Case Study: Ticket Pricing Simulation

The Importance of Ticketing

Sports Events, as a product category, consists of the sale of tickets for professional sporting events including: football, basketball, baseball and other ball sports, plus motorsports including Formula 1 and NASCAR, as well as golf, tennis and similar sports. Ticket sales across these categories considers both the sale of digital tickets with QR codes, as well as the purchase of paper tickets. This is a high revenue area; in 2022 revenue in the Sport Events category is projected to reach US$27.62bn (Statista, 2022). Sport event ticket pricing remains complex, despite VIP and season tickets generating a major share of total revenue. Such complexity results from the use of dynamic pricing, allowing retailers to adjust prices based on market dynamics. In this way, the price of tickets varies based the specific stadium or seat, game rivalry, weather, time of day or day of the week, among other potential factors.

With such variability caused by dynamic pricing, casual attendees (especially in the USA) need to secure sport event tickets quickly upon schedule release. An article by Hoffman (2018) suggests variation between leagues when it comes to purchase schedules, but broadly recommends purchase as aligned to the below calendar of events:

• Major League Baseball: January and February
• Major League Soccer: January and February
• Women's National Basketball Association: March
• U.S. Open: June
• National Football League: Varies wildly from early spring
• National Basketball Association: August and September
• National Hockey League: August and September
• National Women's Soccer League: August and September

Season Ticket Holders
For consumers looking to guarantee access to the most popular games and matchups, being a season ticket holder (STH) is invaluable. STHs receive myriad benefits when considering access to games and events, but pay a premium for this privilege.

As a subscription market, season tickets entail a consumer contractually allocating the bulk of their business to one provider over a specified period of time (McDonald, Karg, & Leckie, 2014). This provides an important source of revenue within sports markets, and makes sport organisations particularly vulnerable to non-renewal. Non-renewal is a concern as STHs are finite, with high switching costs between competitors and distanced repurchase opportunities (typically annual). Therefore, a core tenant of sport organisations is to minimise churn, or increase consumer retention. To achieve this intervention and incentives are used to increase consumer satisfaction or loyalty, raise barriers to exit, and create strong long-term connections between the fan and the team.

In sum, while some churn of STHs is inevitable, effective management practice can be implemented to lessen the impact.

Using the simulation provided, present a response to each of the following:

Question 1. Which customer segment in your dataset would pay the most money to see Team 2 play? What insights can we infer about this segment based on this information?

Question 2. Which customer segment in your dataset has the highest average willingness to pay across teams in the league? What insights can we infer about this segment based on this information?

Question 3. Find the match up of the two most popular teams (highest willingness to pay to view across customer segments). What is the average willingness to pay, and which segment (individually) would pay the most to see this game? What are the implications of this match up for the rest of the league?

Question 4. Maintaining this match up, what is optimal ticket price? Explain and justify this decision.

Question 5. What factors beyond pricing might impact customer's willingness to pay? How can these be factored into more complex pricing models?

Question 6. Looking at customer segments A, B, C and D, which segment is the happiest with the season ticket price? Which segments would be better served paying casually for attend games? Does this change if the STH costs rose to $550 or was reduced to $450? Explain these connections and the implications of this on future pricing of tickets.

Question 7. Looking at customer segments A, B, C and D, what is the probability that each segment will be retained as a season ticket holders (STH) in the following season? What strategies should be employed for each of these segments? Justify your responses.

Question 8. Explore the Customer Value Estimation of the STHs. What do you notice? Explain this concept and its relevance.

Attachment:- Sport Business Analytics Case Study.rar

Reference no: EM133544316

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