AI-Enhanced RFM Marketing is Maximizing Revenues and Revolutionizing Fan Engagement

AI-Enhanced RFM Marketing is Maximizing Revenues and Revolutionizing Fan Engagement

Knowing exactly what piece of merchandise will make a season ticket holder open their wallet or precisely when a casual fan is about to lose interest in the organization isn't sports marketing science fiction (as thrilling a genre as that might be). It’s become reality for savvy rights owners now combining generative artificial intelligence with Recency, Frequency, Monetary (or RFM) marketing–and it’s helping those properties to maximize revenues and better engage their fans in real-time.

At its core, RFM marketing breaks fan engagement down into three key categories:

• Recency: When was the last time the customer interacted with the team/league?

• Frequency: How often do they engage with the property?

• Monetary: How much are they spending on tickets, merchandise, and affiliated services?

Most sports organizations are actively collecting RFM-related data points (think: ticket and merchandise sales, social media interactions). Far fewer have a true year-round RFM strategy in place that would enable them to market more effectively.

Some likely do not realize they have the elements to execute one as they’re simply unfamiliar with the approach.

Many others are still without the AI-powered tools need to turn insights gathered into actionable strategies and to scale RFM efforts. It is time intensive to set-up cohorts/segments and/or personas. 

But properties that have integrated AI-powered applications into existing RFM strategies have been able to turn each component of what was once a manual, time-consuming endeavor into a scalable, dynamic process that continuously adapts to fan behaviors and drives increased engagement and revenue (depending on the marketing artifact).

Recency Revolution

One of the more exciting shifts AI has brought to sports marketing is the ability for rights owners to move beyond one-size-fits-all promotional offers.

Historically, sports marketers have sent the same promotion to all fans. But with the help of GenAI, they can now send personalized messages to each one and significantly lift conversion rates.

Persado is among the solutions teams and leagues are leaning on to create customized offerings. The platform leverages historical interactions and uses natural language processing to craft distinctive dialogue that is optimized for engagement.

Fine-Tuning Frequency

Keeping fans engaged throughout the season requires timely personal interactions, and human efforts to maintain contact often fall short. 

That is where platforms like Attentive come in. The AI-powered application automatically sends personalized SMS messages to fans when their activity levels dip.

By delivering real-time custom content, the organization can keep the fan engaged. Remember, it’s far easier to command a greater share of wallet from an existing customer than it is to acquire a new one.

Monetary Maximization

Sports organizations will only be able to maximize revenues once they understand who their core audience is and what those individuals value. AI tools like Salesforce Einstein, Dynamic Yield, and HubSpot now exist to help rights owners analyze historical spending behavior and create hyper-targeted ticket and merchandise bundles capable of increasing per-fan spend.

However, marketers with access to these advanced applications are often at the mercy of the organizations’ business intelligence (BI) team. They’re only able to make an impact if BI’s analysis is done fast enough.

And that’s not always possible. According to a Google Cloud case study, "70% of the [Golden State] Warriors’ analytics team’s time was spent collecting and shaping data, and only 30% was spent analyzing it."

By automating data collection, with LLMs like OpenAI, Google Cloud Platform and Google Gemini, BI teams can focus their efforts on delivering insights in real time (rather than manual data processing) and empower their marketing execs to quickly execute personalized campaigns with AI-powered tools like Attentive and Persado.

Below are a couple of hypothetical examples that demonstrate how a rights owner would use an LLM alongside a powerful AI application to enhance fan engagement and drive business success.

To Re-Engage Lapsed Fans

• Prompt: “Identify fans who attended a game in the past 60 days but haven’t made a purchase since. Generate personalized messages encouraging them to attend future events.”

• AI Output: The LLM identifies a segment of fans and suggests messaging for each emphasizing the urgency of upcoming events. Historical data shows that fans in this cohort are 40% more likely to respond to time-sensitive offers (think: flash sales).

• Strategy: Send the messages via SMS or email with an AI application. Tailor offers to encourage attendance at the next home game. 

Maximizing Merchandise Sales

• Prompt: “Analyze fan spending patterns across merchandise and ticketing. Recommend personalized product bundles to increase per-fan revenue.”

• AI Output: The LLM identifies a segment of fans who have spent over $200 on tickets over the last 90 days. It notes that these fans are historically 50% more likely to buy limited-edition merchandise when it is packaged together with discounted tickets.

• Strategy: Create personalized marketing campaigns with an AI application. Offer high-spending fans exclusive ticket and merchandising bundles to maximize spend.

Sports properties ready to integrate AI into their RFM strategies should start by auditing existing CRM and fan data systems to ensure they are collecting the right data points. Next, integrate AI applications, like the handful cited above, to supercharge these strategies.

Then, begin piloting programs focused on high-value segments or lapsed fans to prove ROI. Start small with campaigns targeting four key cohorts. Gradually scale as the most effective strategies emerge and optimize the AI-driven insights accordingly.

Embracing AI-powered mar-tech platforms or LLMs can deepen fan loyalty and help turn data into dollars. That is something every sports organization should be prioritizing as they look to remain competitive and keep revenues growing.

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