December 12, 2023

How to Create a Fan 360 Profile with Snowflake & Fivetran

By phData Marketing

This blog was written by Sara Price and edited by Sunny Yan.

The fan experience is a critical component of how sports organizations operate. With terms like ‘Fan 360’ disrupting the industry, there’s never been a better time to harness the data of your fanbase to make more informed decisions. 

In this blog, we’ll demonstrate how to utilize data to drive successful targeted and personalized campaigns for your fanbase to increase revenue, boost operational efficiency, and improve cross-departmental collaboration—all while providing an enriched fan experience. 

Let’s go! 

What is Fan 360?

Fan 360 combines fan data from various touchpoints related to a fan’s interactions, behaviors, experiences, and preferences with a particular sports team to get a complete ‘360’ view of the fan and their needs. 

Sporting organizations that utilize the Fan 360 approach can often create a more personalized and satisfying fan experience that builds stronger fan loyalty, increases revenue, and keeps fans engaged, regardless of how the team performs.

How to Create a Fan 360 Profile

Step 1: Centralize Data

The first step in creating a Fan 360 profile is to collect and centralize the necessary data. Fan data encompasses a wide variety of touchpoints (Ticketmaster, stadium kiosk sales, etc.) spread across various departments. This data is usually stored in disparate locations, and wrangling it together can make it extremely difficult to create a comprehensive view that can fuel decisions. 

Rather than having data sources stored across the organization, it’s best to have everything located in a centralized location. To solve the problem of disparate data sources, many of our customers in the sporting world who have the best results rely on the modern data stack combination of Fivetran and the Snowflake Data Cloud

Your fan data is everywhere. Fivetran is the platform to pull it from any source, and Snowflake is the centralized place to store it.

Why Fivetran?

Fivetran is the industry leader in data integration. With over 400+ pre-built, automated connectors, Fivetran makes it easy to move data from all of your SaaS and on-prem data sources into cloud-based destinations like Snowflake. 

After the initial set-up, data is quickly and reliably streamed to a source destination (such as Snowflake) without requiring any code. Fivetran can also sync data as frequently as every minute, allowing for real-time insights. 

Another benefit of Fivetran is that data is normalized when it’s brought in, so it’s query-ready for your data team to work with. Fivetran is also embedded within the Snowflake product via Partner Connect creating a seamless experience between the two platforms.

Why Snowflake?

Snowflake is the industry leader in cloud-based data warehousing. Snowflake’s built-for-the-cloud architecture is highly performant and designed to handle large volumes of data and data consumers. Because of its cloud architecture, users do not have to worry about the maintenance of the infrastructure and the database going down at an inopportune time. 

In addition, Snowflake only charges based on the amount of data stored and computed, with the ability to scale down during times of low traffic. These features make Snowflake an excellent destination for fan data sources with fluctuating data storage or processing needs, such as ticketing, forms & surveys, and CRM funneling information. As a bonus, using Fivetran to automate the movement of this data into Snowflake carries a similar advantage – you will only be charged for the data that you move.

A complete view of the fan, rather than pieces of information spread across various departments, means less guesswork and more data insights. It also leads to more company-wide collaboration and cuts unnecessary organizational expenses.

Step 2: Analyze the Data

Once you have centralized your data using Fivetran, use a business intelligence tool like Sigma Computing, Power BI, Tableau, or another to craft analytics dashboards. These platforms can be connected directly to Snowflake to create fully automated dashboards that are updated in real-time. 

This way, decision-makers in all departments can ensure they always have the freshest data available to make strategic business decisions. 

Game day dashboards are often used to showcase items like ticket scans (type of device and time of entry), gate entries (entry), concession and merchandise purchases (type and # of items purchased, wait times, express pick-up, in-seat delivery), and Mobile App usage (operating system, live chat, page views, push notifications). 

An example of how real-time analytics can be used to drive insights would be noticing whether a specific gate is overcrowded and being able to redirect traffic by sending a push notification to fans.

Another way to analyze data is the concept of a Fan 360 profile.

Ideal Fan 360 Profile Example: Victory Vicky

Let’s give our Fan 360 profile a name. We will go with Victory Vicky because who doesn’t like to win? We are going to break down what we know about Victory Vicky based on all the data sources we have centralized in our data warehouse. 

First, we know Victory Vicky is a female because she identified herself as such in the profile section of the loyalty program. The loyalty program is located in the MarTech Stack, and the data moves effortlessly into the data warehouse. 

Second, we know she has attended seven home games, and her average time of entry is game time because her ticket scans are tracked as she enters the stadium. This information is also funneled into the data warehouse. 

Our third and final example is knowing Victory Vicky’s favorite player. We know this because she purchased a women’s jersey of this player, and merchandise information is also being funneled into the data warehouse.

Step 3: Data Insights Drive Campaigns

Continuing with the example, it’s time to activate based on what we know about Victory Vicky.

Now that we know Victory Vicky, we can personalize her emails and ads about joining the women’s program or showcasing women’s merchandise. We also know she has attended seven home games but didn’t arrive until game time. We can take that information and send her emails like Game Day Previews to promote partner activations near the stadium to get her to come earlier. 

Arriving early on game day helps logistically with parking and entry. Additionally, we could further incentivize her with a coupon for concessions/pre-game activities to increase her spending. 

Another detail we have on Victory Vicky is her favorite player because of the jersey purchase. With this information, we can personalize her email content to include their imagery or even send an email coming from that player. This type of engagement and personalization is meant to give Victory Vicky a better brand experience and increase fan loyalty, impacting revenue growth.

What is the Future of Fan 360?

The future of the Fan 360 holds exciting possibilities with the combination of AI and Machine Learning. As technology advances, these tools are certain to transform how sports organizations understand, engage, and cultivate relationships with their fans. 

Listed below are a few key trends and possibilities for the future of Fan 360 profiles:

Predictive Analytics for Fan Behavior

Machine Learning can be used to predict fan behavior based on historical data. By identifying patterns and trends, organizations can anticipate the preferences and actions of individual fans. This allows proactive and targeted engagement strategies, such as predicting attendance for specific events, tailoring promotions, and optimizing marketing efforts.

Enhanced Fan Experience Through Chatbots

AI chatbots can provide instant and personalized interactions with fans. These bots can handle routine inquiries, deliver customized content, and even simulate conversations with fans. Integrating natural language processing capabilities allows for more human-like interactions, enhancing the overall fan experience.

Continuous Learning and Adaptation

One of the key advantages of AI and Machine Learning is its ability to learn and adapt regularly. Fan preferences and behaviors develop over time, and these technologies allow organizations to stay ahead of trends, expanding their engagement strategies based on the latest insights.

Example of a Successful Fan 360: Denver Broncos

The overall goal for any sports organizer is to give fans the best possible experience while attending a game. Check out this eye-opening story of how the Denver Broncos leveraged a Fan 360 approach to please fans and fuel a sell-out streak by leveraging insights from data.

Leveraging the data stack below, the Broncos achieved 20+ hours of weekly time savings in data pipeline maintenance, faster real-time access, and improved fan experiences.

Broncos Data Stack:

ELT Fivetran
Data warehouse Snowflake
Connectors Dynamics 365, Eloqua, Qualtrics, Google Analytics, YouTube Analytics, Fivetran Log
BI Tableau


The Fan 360 approach is truly a “game-changer” for sports organizations. The journey to creating a Fan 360 profile is a strategic and data-driven process that holds immense potential for sports organizations. 

The first crucial step involves centralizing data through platforms like Snowflake and Fivetran, breaking down organizational silos, and providing a comprehensive view of fan information. 

If your organization is interested in creating a successful Fan 360 experience, the data experts at phData can help! From hundreds of successful migrations to Snowflake to advanced expertise in Fivetran and other Modern Data Stack technologies, phData can consistently help you wield the power of data to make more informed decisions. 

Take the first step today in your Fan 360 journey by reaching out to our experts for advice, best practices, and actionable strategies.

Take the first step today in your Fan 360 journey by reaching out to our experts for advice, best practices, and actionable strategies.

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