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Sports Properties are Revolutionizing Ticket Sales Using AI to Scout Buyer Behavior
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Sports Properties are Revolutionizing Ticket Sales Using AI to Scout Buyer Behavior
Ticket sales strategies have evolved from largely ‘smile and dial’ to more sophisticated, data-driven approaches over the last decade. Today, many sports organizations leverage AI and machine learning to try and improve convergence rates and ultimately to drive higher sales volume.
McKinsey claims companies using AI in their sales processes have been able to grow revenues by as much as 5%.
But there are two types of AI: traditional and generative. Traditional AI uses historic data to make predictions or decisions (think: NFL Next Gen Stats). Generative AI, an advanced form of the technology, can create original content (think: personalized email copy or chatbot responses).
Both have roles in a modernized ticket sales strategy. However, the vast majority of teams, leagues, and federations still only leverage the former’s capabilities.
Rights owners and event promoters across the landscape use platforms like Ticketmaster Sport, Eventellect, and TicketSell, all built on traditional AI, to make better, data-informed decisions on pricing strategies. Far fewer are taking advantage of ChatGPT’s ability to analyze email correspondence for buyer, or potential buyer, intent.
AI’s true power in the ticket sales process lies in its ability to produce deep, actionable insights on trends and fan behavior.
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While more robust solutions do exist on the market, OpenAI’s LLM has a low barrier to entry for organizations looking to kick tires on the tech’s capabilities before making a meaningful investment in it. ChatGPT Plus costs just $20/mo.
But one should not confuse the nominal price with poor quality or limited abilities. Having a subscription is akin to adding a long-time scout –specifically to analyze ticket buyer behavior– to your team.
ChatGPT can quickly examine email threads between sales reps and fans, and accurately identify key purchase intent indicators allowing for timely, targeted follow-ups. Remember, the number of emails exchanged with a prospect is not necessarily indicative of a potential sales opportunity.
It can also filter necessary follow-on correspondence based on priority and promotions, and draft customized scripts for each fan based on successful patterns found in correspondence with previous buyers and potential buyers.
In essence, the tech can provide sales reps with the real-time feedback and guidance needed to respond to, or follow up with, specific prospects, eliminating the need for a sales manager to review each exchange.
The reality is no sales manager has the time to review every email, which is why so many end up coming off poorly written and/or tone deaf to the recipient.
But a reduction in the need for manual oversight does remove a common bottleneck in the sales process and should allow for quicker decision-making and reps to send more emails in less time. As a result, the sales team can collectively manage a greater number of interactions, close more deals, and ultimately increase revenues.
Several sports properties have reported substantial increases in ticket sales and conversation rates after implementing AI-powered personalized marketing campaigns into their processes.
And by streamlining internal communication practices, managers should have more time to focus on high-level strategy and planning rather than day-to-day correspondence.
It’s worth mentioning that as the LLM continues to learn from a growing number of fan interactions, its analysis will only become more accurate and actionable.
Ready to add a buyer behavior scout to your team?
Start by having the GenAI platform review some recent email correspondence. You will need a PDF of the email thread, or to tell ChatGPT to ‘see the email thread below’ and paste it in.
Then enter the following prompt:
'Analyze the following email thread between a sports team ticket agent and a potential ticket buyer. Identify indicators that suggest the buyer's intent to purchase tickets, such as inquiries about pricing, availability, specific games, or seating preferences, and expressions of urgency or commitment. Predict whether the buyer is likely to continue asking questions or if they are close to purchasing. Provide a summary of your analysis, including key points and your prediction.'
Once you’ve received your AI-generated scouting report, the next step is to craft targeted email responses. GPT can help here too by tailoring communication based on buyer intent. It will create urgency with the hottest leads and maintain engagement with lukewarm prospects.
The scouting report can be integrated (or linked to) the team’s existing CRM systems giving the sales manager(s) a comprehensive look at high-potential prospects. By having a snapshot of all the best leads, a senior executive can better assist their reps; helping them to prioritize outreach, optimize correspondence, and in theory, close more deals.
But an AI-powered sales scout can do more than just digest emails for intent and craft custom responses. For example, it can support FAQ management inside an organization by generating comprehensive tailored responses to fan questions freeing up skilled staff members to focus on higher-value interactions.
In fact, the most progressive organizations may even want to consider building a custom chatbot for their ticket sales website. Having a 24/7 digital assistant capable of handling queries should enhance engagement and could potentially provide a sales lift.
Use a no code platform or an app that integrates with OpenAI (or another leading LLM) if going down that route.
It’s worth reiterating that AI implementation isn't about replacing human personnel. It’s about empowering your team to focus on what they do best, which is building relationships and generating revenue.
The Generative AI playbook for ticketing is clear: sports organizations should leverage the emerging tech to scout buyer intent, craft personalized communication, and enhance the overall fan experience. We’ll see who is forward thinking enough to run it and reap the clear benefits.
Editor’s Note: If you have questions about the use case cited or would like to discuss how Generative AI can make your organization more money or more efficient reach out to [email protected]. We are taking on select consulting projects.
About The Author: Former Washington Commanders chief strategy officer Shripal Shah has spent much of the last decade helping media companies, big box retailers, and innovative startups enhance their businesses using AI. He’s now transforming sports businesses using much of the same playbook.
Shah is also a professor in Georgetown University's Sports Industry Management Program and the author of “Leveling Up With AI: A Strategic Guide to AI in Sports Marketing” and “The Art of Victory: Generative AI and the New Frontier of Global Sports.” You can reach him direct at [email protected].
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