Decision Intelligence in Sports Marketing

Decision intelligence in sports marketing refers to the use of advanced analytics and decision-making tools to inform strategic decisions related to sports marketing initiatives. It involves the collection, analysis, and interpretation of data to gain insights into consumer behavior, market trends, and the effectiveness of marketing campaigns. By leveraging decision intelligence, sports organizations can optimize their marketing strategies, improve fan engagement, and drive revenue growth. Key applications of decision intelligence in sports marketing include customer segmentation, personalized marketing, pricing optimization, and social media analytics. Considering big data (BD) has become a vital tool in contemporary research and sports management practices, managers, business leaders, and marketers have all the information they need to make informed decisions efficiently. Yet to make sense of the data, they often rely on artificial intelligence (AI) and related technology, thus contributing to the rise of the new academic discipline that blends engineering, social sciences, and management and decision theories called decision intelligence (Duan et al., Int J Inf Manag 48: 63–71, 2019). AI is not a stranger to the sports industry. From match outcome predictions and strategic and tactical decision-making to fantasy sports injury predictions, AI has crept into sports at various degrees of application and acceptance (Beal et al., Knowl Eng Rev 34: e28, 2019). Recent projections regarding the global AI in the sports market point out that it could reach a value of 19.2 billion USD with an annual growth rate of 30.3% until 2030 and highlight machine learning as one of the most lucrative segments on the market (Beesetty et al., Artificial intelligence in sports market. Allied Market Research, 2022). This opens the door for a wider application of AI technologies in nurturing decision-intelligence practices in the sports industry. One of them is sports marketing, as one of the fastest-growing aspects of sports (Fullerton et al., Sport Mark Q 17: 90–108, 2008). As a result, this chapter aims to explore the role of decision intelligence in sports marketing with an emphasis on the use of predictive analytics. This chapter first familiarizes the readers with the topic, the objectives, the scope, and the purpose of this chapter. Then, readers can take a look at a detailed overview of the existing literature and the related work explaining the current stage of decision intelligence as well as sports marketing, through a concise evolutionary framework and a summary of common practices and findings. Afterward, the authors introduce the readers to decision intelligence and sports marketing and the possibility of them going hand in hand to boost sales and growth for sports teams and related organizations in the industry. This chapter goes on to emphasize the application of predictive analytics in sports marketing to determine the likelihood of specific future events happening. Despite descriptive analytics, the power of sophisticated data analysis lies in predictive analytics that can model possible fan behavior to renew sports season tickets, likely fluctuations of prices, factors that drive attendance at sports games, and more (Hensley, Why fans crave predictive analytics-and how sports can deliver them. Forbes, 2022). Being aware of this information has the potential to significantly improve the productivity of sales departments of sports organizations, enhance the effectiveness of marketing efforts, lead to increased efficiency of the use of resources, and ultimately drive profits (Mumcu & Fried, Sport Managt Educ J 11(2): 102–105, 2017). Predictive analytics in sports marketing is possible with software like Microsoft’s Power BI that crunches the numbers of relevant factors through AI-driven algorithms and comes up with decision alternatives, fostering a decision intelligence climate for members of the management and marketing teams. Based on the presented data, this chapter will outline the next steps and future paths of research and practical application of decision intelligence in sports marketing and the process of making informed decisions aided by data and AI. This will be followed by a set of conclusions for researchers, managers, and marketers, thus contributing to a deeper understanding of how decision intelligence is applied in sports marketing, most notably for predictive analytics of likely outcomes. Largely, this chapter highlights the importance of decision intelligence and predictive analytics as powerful tools for professionals in sports marketing, enabling them to make data-driven decisions and improve competitiveness and organizational growth.