Like all businesses today, sports franchises are feeling the seductive pull of artificial intelligence (AI), and seeing the value of analytics applied to operations. The most well-known uses of AI in sports can be compared to “Moneyball 2.0,” with the technology’s ability to do multivariate analysis elevating sabermetrics to new heights. However, it is the commercial uses of AI, though still fairly nascent, that hold great promise for ROI. The true potential of AI in sports is off the field.
Confluences of forces — increase in computer power, abundance of data and some recent discoveries in deep neural networks — have jump-started the new era of AI. Today’s AI systems, such as Google’s AlphaGo, can beat Go world champions and translate data into innovation for industries like finance and energy. For example, clients in finance are processing data from Bloomberg, analysts’ reports, social media, and other streams to predict macro events and gain advantage over the market. Successful funds have seen promising results, with one investment firm manager estimating that artificial intelligence could be involved in 99 percent of investment management in 25 years.
Similar systems can be used for increasing fan engagement and sponsors’ ROI in stadiums. AI is already in use at a handful of stadiums, often taking the form of a helpful chat bot to answer questions about parking or guide guests to the concession stand (see: SunTrust Park or the Thunder Bot at the Tampa Bay Lightning’s Amalie Arena). In turn, the data generated from these apps can be married with decision science to influence consumers’ choices to not only improve customer experience and maximize engagement, but also increase revenue. The customized content delivered can take into account data from many sources (social media, historical purchases, etc.) and make smart recommendations to better serve consumer preferences and maximize drivers for following a team.
Taking it a step deeper, AI can boost a team’s sponsorship revenue with relevant, meaningful, and automated insights for key accounts. If you are a sports property owner, you probably have high value accounts (HVA) that sponsor events and your team. Today, sponsorship research teams have to use available data sources to create in-depth reports of each HVA. Updating these reports using manual methods is exhaustive and labor-intensive, as the aggregation and analysis of disparate data sources is time-consuming. Thanks to the recent developments in AI, we have solved the problem of perception, improved our grasp of natural language understanding and allowed us to reason deeply, which can enable us to extract human-like insights at machine scale. Imagine that your sales team can create sponsorship products especially customized to each sponsor’s objectives in the matter of a few hours instead of months.
The amount of time required to gather the information is of key concern because it limits the resources available to analyze data and understand trends, which are what really create valuable insight for the benefit of corporate strategy and sales account executives. The aggregation effort also limits the number of accounts that can be analyzed and thus the number of HVAs is severely capped or limited without AI’s cognitive abilities. In addition, these products cannot incorporate your unique value proposition to your key accounts to maximize returns for them.
AI software can enable the research team to refresh existing HVA reports and create new ones with substantially less effort. A high value artificial intelligence (HVAI) tool can query, aggregate, classify, rank, and summarize disparate data sources. If leveraging Internet of Things (IoT) technology to capture fan preferences, that data can be added to the HVAI application. Improved natural language technology can automatically read and understand the context of thousands of pages of unstructured data pertaining to each brand, industry, or product and tie content to the passion drivers of your fans.
What does this look like in total? For fans, it means logging into an official team app for assistance on game day, bonus features or contests, and special offers for completing a brief survey. For sponsors, it means an accurate segmentation of who is attending the game and why, research on what they interact with and how, and accurate, up-to-date predictions of how to best engage. For franchises, it means more engaged fans, true insights that sponsors are willing to pay for, and more revenue.
These technologies present a valuable opportunity for all parties involved. Though the use of AI to choose players may be what builds teams, its use in the stands is what builds successful engagement, and that is what truly builds a franchise. It’s time to bring the algorithms that beat Go to the big leagues.
Usman Shuja (@kshuja) is the founding executive and general manager for Industrial IoT at SparkCognition. He serves on the U.S. advisory board for the International Cricket Council and is the all-time leading wicket taker for the U.S. national cricket team, on which he played from 2006-15.
