Understanding your fanbase starts with leveraging the data you already have

A few weeks ago, I wrote about the disconnected interruptions that are so common in our lives today – that constant flood of outreach from companies, including sports teams, that is not tailored to us as individuals. Disconnected interruptions take many forms – perhaps the most common one being automated e-mails.

This begs the question – why don’t sports teams (and leagues) do more to tailor content and offerings to different types, or segments, of fans? Discussions across the industry reveal that while some teams have become fairly advanced in understanding their fanbases, others struggle to do more than basic CRM, capable of little more than pushing out those disconnected interruptions.

Within any fanbase, there is a wide variety of fans, each with their own consumption patterns and drivers of demand. The Kansas City Chiefs present a relevant example – fans range from stalwart season-ticket holders to burgeoning fans enamored with recent on-field success to younger women drawn by a connection to Taylor Swift. Each type of fan has demographic variables as well as behavioral and attitudinal characteristics that inform the fan’s demand drivers, and therefore the growth paths available to the organization.

Getting to the point where these are understood, and can be actioned upon, requires a four-step organizational journey. I will dig into the first two of these today.

1.????? Create a robust data platform (the Context Stream) connecting various sources of customer data

2.????? Develop rich fan understanding

3.????? Shift organization priorities to include customer engagement planning

4.????? Enable advanced capabilities to engage fans where and how is most meaningful

Create a robust data platform

Behind any useful insight is quality data. Fortunately, within sports a wealth of fan data exists, such as purchase history at multiple levels, online engagement data, and demographic data. The historical challenge has been marrying this data into something that enables better fan insight, thereby creating opportunity to unlock value by tailoring communication and offerings. There are a number of reasons for this – outdated CRM systems that don’t “talk” to other data (i.e. league data, POS, ticketing, merchandise, online engagement, etc), lack of prioritization by leadership, or belief that what exists is “good enough” to send outreach to fans.

Building an integrated data ecosystem is a process. However, there is much value to be gained along the way – even with limited data. Teams should work with available data to establish the foundation and then scale as new data sets become available. ?For simplicity, I have broken this down into three phases, which begin with building a data strategy, move to creation of a Customer360, and ultimately to creation of the Context Stream, which is the next evolution of the Customer360. Until now, Customer360s have leveraged available structured data. The Context Stream introduces unstructured data to give an incredibly robust view of the fan. This is a longer-term goal, and something not previously possible, but with advances AI & Machine Learning, it is reality.

Laying the Groundwork: Defining Data Strategy

The first step any organization must undertake is to define a data strategy. This is not a document to create and put on the shelf, but rather something that will involve change management and culture shift. Core components include:

1. Short, near, and long-term goals that data can enable. Specifically, how can data assets be leveraged to generate new revenue streams or improve operational efficiencies?
2. Data sets that are available (or can be obtained) that can inform insights in pursuit of these goals
3. Data architecture required to organize this data

Depending on where the organization is starting from, these goals will look different. However, they should include gaining deeper fan insight, improving fan experience and loyalty, identifying cross-sell and upsell opportunities, and improving agility and responsiveness to changing fan needs as they progress in their fan journey.

Further, a critical part of data strategy is defining ROI metrics early on so value can be measured along the journey. Demonstrating impact at each step is necessary?in shifting organizational culture to value data-driven decision-making.

Making Data Available & Creating a Customer360

Creation of the Customer360 enables base-level analytics of the fanbase. Even with limited data, opportunity exists to customize marketing and begin mitigating disconnected interruptions. For example, by only leveraging ticket purchase history, we can glean a significant amount of information about a given customer:

• Does he or she attend games on certain days? Against certain teams? Sit in specific sections? How many tickets? Etc.
• Even with this limited information, the team can gain deeper insight into groups of fans with similar purchase history – and tailor offerings to those groups accordingly.

A first step in this process is ensuring that all available data (fan purchase data, fan demographic data, league-level data, partner data, third-party purchased data, etc.) is available in a data warehouse / data lake. Essentially – the data needs to be able to “talk to each other.”

Moving to a Customer360 model is easier today than in the past. Advances in data management have led to numerous “off the shelf” platforms that can be stood up, leveraging robust frameworks and practices that have been established across industries. Well-defined data governance processes can be followed, allowing teams to unlock the value the democratization of data brings.

Tying all Knowledge Together: Building the Context Stream

The Context Stream takes the foundation of the Customer360 and greatly enriches fan data by layering in any context – including from unstructured data – such as new sources of fan insight, observations, needs, trends, environmental factors (like team/player performance), fan experience, and prior touchpoints. With advances in AI & Machine Learning, leveraging unstructured data to create the Context Stream is now possible.

Ultimately, all this data can be used to help inform where each fan is at a given time in their fan journey, inform “Next Best Actions” from the team for engagement, and enable precision marketing to each micro segment of fans. While Next Best Action approaches have become the norm in some industries (i.e. pharma), they are fairly novel in the sports industry, and will allow teams to play a direct hand in shepherding a fan along the fan journey.

Leveraging the Context Stream will require advanced analytical (and potentially AI-powered tools) to enable best-in-class customer engagement, but should be considered a future state for any organization wanting to unlock the deepest insights data (both structured and unstructured) can provide about its fanbase.

Develop Rich Fan Understanding

Getting to a future state where the Context Stream is a reality will be a journey for teams and leagues. However, there is much value to be gained along the way in terms of understanding the fan base, not least of which is leveraging customer data to inform fan segmentation and understanding of fan journeys, thereby doing away with the “one size fits all” approach to fan marketing that is unfortunately all to common in professional sports today.

For many sports teams, a base segmentation of their fanbases would be a significant step forward. This would allow team marketers to begin to customize offerings and outreach, thereby reducing disconnected interruptions. With better segmentation, the team or league can identify the groups of fans that will drive growth and design products, services, and experiences tailored to them.

Customer centricity should be at the heart of every strong marketing organization. After all, the fans and their passion are the reason to be for professional sports teams and leagues. Fandom is extremely emotional, and the resulting loyalty can be very powerful, so being fan-centric in everything the organization does must be viewed as table stakes in a mutually beneficial relationship, one where fans have rich experiences and participate in a vibrant community, while the team unlocks continued growth from ever-deepening fan engagement. The first step is leveraging the data that exists to better understand the fans themselves so they can be better served by the organization.