Facing fierce competition for fan loyalty, sports and entertainment organizations have increasingly relied on fan data and engagement to personalize communications with fans across numerous touchpoints and channels. Today’s fans expect fully personalized customer experiences, from the advertising they receive to their game experience. Winning games is no longer enough: Teams must deliver individualized experiences that account for individual fans’ preferences. Understanding fan data allows organizations to determine which fans come to the game with their families, who arrives early, what sections they prefer to sit in, who their favorite players are, and whether they prefer Bud Light, craft beer, or lemonade. By leveraging this fan data and engagement, teams can create tailored experiences that enhance fan loyalty and transform casual spectators into passionate supporters.
Knowing the answers to these questions can give any team an edge in monetizing, segmenting, and growing their fan base (and their business). Unfortunately, many sports teams struggle with last-generation data systems, missing insights that will help them solve important business issues. Fragmented data sources, a lack of scalability, and limited customization all stifle sports organizations’ ability to understand their fans and their business. This results in lost revenue, lower ROI from marketing and advertising, and lower profits.
Fortunately, the technology and capabilities to extract insights from fan data have not only evolved—they’re more accessible than ever. Teams nationwide are realizing that a scalable, composable modern data stack can not only meet the needs of the business—sales, marketing, operations, finance—it can also provide the ownership and control over data that teams need.
Sports organizations rely on data from numerous disparate data sources (e.g., ticketing, merchandise sales, etc.), residing in silos that must be successfully integrated to produce business insights and accurate reporting. The modern data stack’s value lies in its ability to bring together numerous disparate data sources and quickly turn them into useful information. Think of all the ways fans interact with your team—buying tickets, buying merchandise, concessions, parking, and more. When data from each of these sources is not accurately integrated, you’re unable to see the full picture of your fan base, affecting all downstream outputs your organization relies on. These data challenges can significantly impact decision-making and overall business performance.
Traditional CDPs promise an integrated solution, but a one-size-fits-all approach inherently can’t be customized to your specific needs and data sources. The resulting data gaps and poor-quality data require precious resource overhead and ultimately prevent teams from truly engaging fans. The lack of data can also be an operational problem: Limited data refreshes reduce a team’s ability to operate the business, and incomplete data leads to poor decision-making.
A modern data stack uses multiple, specialized functional components to give you all the data management tools you need to create a custom, composable solution. Think of it in five parts:
These capabilities allow forward-thinking sports organizations to regain control over their data and overcome their specific challenges. By implementing a flexible, scalable, and composable data infrastructure, organizations can see numerous benefits.
A modern data stack solution represents a transformative leap forward for sports organizations. As sports teams continue to compete for fan dollars, the flexibility and composability a MDS solution provides are essential—not just a value add for reaching fans but a transformation of your sales, marketing, and operations capabilities. By implementing a flexible, scalable, and composable data infrastructure, they’re reaping numerous benefits:
With these benefits in mind, how can a team begin setting up a modern data stack?
Because a modern data stack solution touches so many aspects of your business, implementation requires careful planning and execution. A multi-phase process for each step can help ensure better outcomes.
In the first phase, make sure you have a comprehensive understanding of your current data landscape. Assess data quality and identify improvement opportunities, and from there, define what the scope of your data stack will be. What systems will it need to connect to right from the beginning? What capabilities are most important for you to get out of it? By knowing from the start what you’re aiming for, you’ll be better positioned to navigate challenges.
A technical review is also critical at this stage. Review your data sources, assess data quality issues, and determine your team’s goals for each data source. Understand the current state of the data and identify any challenges that need to be addressed before proceeding.
With those challenges addressed, you can begin to think about what technologies will be most effective for your needs, and then make the selection accordingly. You’ll want to ensure your selected tools are future-proof and aligned with long-term strategic initiatives. While embarking on this journey, ensure business and technical SMEs are committed and involved—they have key business knowledge and historical information that will make or break your solution. By doing this, you’ll be able to:
By thoroughly addressing these aspects in Phase 1, you’ll set a strong foundation for your modern data stack implementation.
The migration phase is where you build your system and transition over to it—a critical step for the immediate success of the system, but also one which will have a major impact on its long-term effectiveness. Initially, focus on setting up the new master data services software and tools, followed by data ingestion and comprehensive data modeling. This modeling should include an Identity Resolution (IDR) solution, which entails tool implementation, establishing matching logic, and defining winning priority rules, as well as selected data sources. Additionally, reverse ETL processes for feeding back to your email service provider and marketing tool are put in place.
As the project progresses, test, validate, and deploy your new system with users, validate models and IDR outputs, and ensure that the matching logic meets all requirements, then make any necessary updates or fixes based on feedback. Once these steps are completed, the modern data stack can be deployed to production, with the support of thorough documentation, knowledge transfers, and client training to ensure a smooth handover and long-term success of the implemented system.
In this stage as well, both technical and business subject matter experts will need to participate in modeling, IDR logic, and user acceptance testing. Your SMEs, with a thorough understanding of the current state of data and required fields, will also be important here. And finally, ensure you’re committing the right level of effort to setting up your IDR tool. Depending on the tool you selected, this may be a labor-intensive process.
At the conclusion of this phase, selected MDS tools will be set up according to best practices and function as expected. Identified data sources will have been ingested into the data warehouse according to client requirements. Data models have been built and should align with business use cases, validated & signed off by your SMEs. Your IDR solution will also need to have been implemented and validated. Make sure you’re also considering change management—user acceptance testing, documentation, and training sessions will get your teams actually using the system. Remember, the goal is not just to migrate data, but to transform how your organization manages and utilizes one of your most valuable assets, your data.
In this phase, your focus turns to optimizing and improving your data strategy using the new system. Additional Reverse ETL processes can enhance the flow of data from your data warehouse to operational systems. This is complemented by robust business intelligence practices, including the creation of dashboards and reports that provide actionable insights. While you may already have access to standalone reporting tools, reports will be most heavily used if they’re accessible. Consider using embedded analytics in the systems your end users are familiar with, letting them quickly get the data they need to do their jobs.
This is also when you can begin activating the data you find. With personalized messaging and fan segmentation powering targeted marketing campaigns, you’ll be able to maximize engagement and conversions. Ongoing support and maintenance are vital to ensure the smooth operation of your data ecosystem, as is incorporating additional data sources as your team adds new offerings. By focusing on these key areas, teams can unlock the full potential of their data and drive informed decision-making across all levels of the business.
A strong implementation partner is important to ensure the migration to a custom modern data stack solution is executed properly. There are a few key criteria to consider when selecting an implementation partner:
Sports and entertainment organizations that strive to be data-driven and use their data more effectively can overcome common challenges by leveraging a modern data stack solution. By doing this, sports teams can realize numerous benefits, enabling them to create a true fan 360 view by consolidating all their data. Key advantages of moving to an MDS include optimal fan engagement, comprehensive business reporting, improved data security, and overall ownership and control.
To ensure a successful migration to an MDS, organizations should assess project goals and outcomes as well as their level of technical expertise. Key considerations include having contracts with MDS tools in place, planning for MDS maintenance, evaluating available resources, and preparing data sources for ingestion. Also, selecting the right implementation partner with experience implementing MDS solutions for sports organizations can mitigate risk and ensure project success.
Spaulding Ridge’s experience and expertise in MDS migrations involves a multi-phased, proven approach. Spaulding Ridge’s experience in handling ticketing data (and as a Ticketmaster Nexus partner) along with experience working with various sports teams, sets Spaulding Ridge apart in the industry. Example outcomes from our sports clients demonstrate the tangible benefits of MDS adoption when implemented in a proper, proven manner. We’d be happy to talk about how your organization can get these benefits—just contact us.
