How Business Analytics is Disrupting the Sports Industry

(8 min read – Published on 13th April 2016)

There are two types of analytics within the sports industry. The first one – sports analytics – was created in the 1970’s by Bill James who was first to use statistics in baseball. Michael Lewis then popularized it thanks to his bestselling book, Moneyballpublished in 2003. Sports analytics is the science of learning from data to improve sports performance. Business analytics is the science of learning from data to improve business performance. Even though on-field performance drives revenue, teams are now concerned with how to prevent their business performance from the slings and arrows of sports fortune. Let’s discover how business analytics is disrupting the sports industry.

Ticket pricing analytics: get the best out of your venue

For most sports franchises, ticketing accounts for the majority of their revenue and season-ticket holders are their main concerns. It is even more important for teams playing lots of regular season games in their home venue such as Major League Baseball (MLB) with 81 home games, and the National Basketball Association (NBA) and National Ice Hockey League (NHL) each with 41 home games a year. The San Francisco Giants were the first to adopt dynamic pricing for single-game tickets in 2009. Dynamic pricing uses algorithms to measure demand and price sensitivity to a particular game on a real-time basis. Lots of factors are considered such as weather, a winning or hitting streak, day of the week, secondary market prices (such as StubHub), etc.

“Previously teams used to set their prices six to nine months in advance, when they have no idea what is ahead of them.– Barry Kahn, CEO of Qcue, a software-based dynamic pricing solution.


Interestingly, many sports organizations don’t need to implement dynamic ticket pricing solutions to improve their revenues. For instance, the English Premier League soccer clubs have no major issues in filling their stadiums. For them, business analytics has different characteristics.

Prove your sponsorship return on investment

As seen with Yokohama Rubber becoming the official shirt partner of Chelsea FC in July 2015 with one of the biggest shirt sponsorships ever signed ($300 million over 5 years), teams are now relying on data analytics to better price and negotiate their sponsorships contracts.

Last season Chelsea FC was the most watched Premier League team on television worldwide, with over 31,000 broadcast hours. Chelsea is now one of the most recognized and influential sports brands in the world with more than 500 million fans.

Sponsorship analytics aims at computing sponsorship return on investment (ROI) through data. Teams and sponsors can use licensed products to get data, such as Repucom Sport24 Media Evaluation tool, which computes the detailed TV exposure of a brand (number, time on screen, average exposure length, exposure size screen location…). Otherwise, sports organizations mainly use quantitative and qualitative marketing intelligence studies to assess their own ROI through some metrics such as Net Promoter Score, brand recognition, and brand attribution.

Acquire new fans through lead scoring

Sports teams have two different ways to acquire new fans. There is outbound: team to customer and inbound: customer to team. Business analytics is improving both methods in different ways. By collecting and analyzing data about their fan base, teams are now able to better target and identify the best prospects to contact, generally by phone through their sales representatives teams. For instance, the Detroit Pistons (propriety of Palace Sports & Entertainment) used Marketo to carry out ongoing campaigns to nurture potential season ticket holders before they are ready to have a conversation with the Pistons’ sales team. In another way, teams are also tracking online activities on their websites and other digital applications in order to better foster inbound fan acquisition. SAP has recently partnered with Phizzle in order to help sports organizations better understand digital fan behavior. For instance, they have worked with the NFL along with the Super Bowl XLIX in order to build an interactive experience that transports fans into a world of numbers, images and insights.

Fan engagement: give the fans what they want

One of the first and most used tools to engage fans is the newsletter. This tool is evolving, as teams are increasingly implementing profile and behavior targeting newsletters to better engage with their fans and give them the content that they prefer. For instance, Major League Soccer (MLS) has seen a 39% increase in unique click rate in their personalized newsletter when compared to their previous static ones.

“Based on email response data, the personalized email saw a 39% increase in unique click rate versus the static email.” – Charlie Sung Shin, Director of CRM and Analytics, Major League Soccer

In addition, social networks play a crucial role in fan engagement through the in-game experience by multiplying the number of interaction points – also called touch points – between fans and their favorite teams, from the moment they step foot in the stadium. For example, Facebook launched in January 2016 the Facebook Sports Stadium, a dedicated place to experience sports in real-time with the 650 millions of sports fans present on the social network.

Even with this new innovation, teams don’t abandon all their previous communication channels for the sake of digital ones. Indeed, teams like Aston Villa FC have their own call center in order to better communicate and engage with their fans. For instance, if a season-ticket holder doesn’t show up for 2 games in a row, the team will call him to be sure that everything is okay.

On another level, teams can better engage with their most valuable fans – the season ticket holders – by selecting the most suitable artists to perform in their stadiums. LiveAnalytics – the analytics team of Ticketmaster and LiveNation – presented this product during the 2013 MIT Sloan Sports Analytics conference.

Leverage the Customer Lifetime Value of your fan

One of the first ways to improve the Customer Lifetime Value (CLV) of the fans is to use upselling technics. Unfortunately, upselling might bring up images of self-serving salespeople trying to line their pockets by selling extra products fans don’t need. But when used properly, upselling can bring teams closer to their fans, while bringing more revenue, and enhancing the fan experience. This strategy is all the more important for teams which have no trouble in filling their stadiums. Therefore, they need to focus on how to monetize the millions of fans all over the world who will surely never have the chance to attend a match of their favorite team. In order to better know and communicate with these fans, Arsenal FC developed a free digital membership where every fan can have access to all the video content of the club as well as exclusive e-newsletters, in exchange for basic information such as name, age, and country.

“We have about 1.3 million digital members worldwide and about 70% of them are based outside of the UK.” – Michael Leavey, Media, Marketing & CRM Director or Arsenal FC



With this information, Arsenal FC has now the ability to better communicate with these overseas fans. The challenge is now to be able to monetize them – directly by offering additional services or indirectly by implementing foreign partnerships – in order to enhance their Customer Lifetime Value.

Besides upselling, another strategy to improve the CLV of the fans is to enhance the cross-selling of your products. In this matter, business analytics helps clubs better target the fans most likely to buy side-products such as parking tickets, food and beverages during the game with a push notification on the fan’s smartphone, or even specific and targeted merchandising products.

Create loyal fans by preventing churn

The second important dimension of the CLV – after improving the average fan basket value with upselling and cross-selling – is the loyalty. Lots of sports organizations are now implementing loyalty programs such as the Blue Loyalty program of the Birmingham City soccer club in England. The “True blue members” program succeeded in a 66% uplift in average ticket spending per person for the 2013-14 season, as explained by Tom Rowell – Head of Brand and Marketing at Birmingham City FC – during the Sports Analytics summit of November 2015.

Sports organizations are also very concerned about the churn rate of their fan base, and more precisely, their season ticket holders. Every year, the Team Marketing and Business Operations department of the NBA – an internal consulting team of the league – is surveying all the season ticket holders of the 30 NBA teams in order to help them better prevent churn. The NBA retention model built out of this survey helps the teams to better target the fans who are the most likely to renew, first through an emailing campaign, and then making personal calls to those who are the less likely to renew.

A long and difficult journey

Unfortunately, implementing a data-driven business strategy is not an easy thing to do. Not every team owner is as nerdy as Mark Cuban, and not every top executive is able to handle statistics on a day-to-day basis. Even though every organization understands the key role of analytics, not all of them are on an equal footing in terms of maturity. Moreover, finding the right person to suit the Business Analytics job is not an easy task. Indeed, being able to express complex ideas in simple terms is almost as important – if not more – as being able to compute advanced statistical analysis. The business analytics expert needs to possess the ability to adopt his or her communication style to suit their audience while still conveying the results of their analysis. Besides having analytics skills, teams must also bridge a technological gap. Data acquisition and data management are crucial for every organization implementing a 360-degree analytics approach. That said, just a handful of teams have implemented efficient data warehouses which not only centralize all the data available but also automatically create analytical reports. The business analytics revolution is slowly, but surely, underway.

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Author’s note: This is a personal article. Any views or opinions represented in this article are personal and and do not represent those of people, institutions or organizations that the author may or may not be associated with in professional or personal capacity, unless explicitly stated.