Leveraging Generative AI to Create Sponsorship Proposals That Convert

Leveraging Generative AI to Create Sponsorship Proposals That Convert

JohnWallStreet will be introducing a series of AI-powered solutions in the weeks ahead that can help rights owners grow revenues and optimize operations. These are the easy wins that every sports organization should be taking—an AI Playbook, if you will.

Unlike others advising on how to leverage emerging tech, however, we have a deep understanding of how major sports properties operate and real-world experience implementing the solutions. 

Shripal Shah will pen the column. The former Washington Commanders (then Redskins) chief strategy officer has spent much of the last decade helping media companies, big box retailers, and innovative startups enhance their businesses using AI. 

He’ll now take what he learned, including all best practices, and explain how to apply it/them within a tier one sports property. 

His first column under the JohnWallStreet banner focuses on improving sponsorship sales conversion rates and bringing in new partners; a guide to creating proposals that convert.

“If someone [implemented the proposed solution below], and they did it every day for 30 or 40 sponsorship pitches and the average sponsorship is worth $250,000, they could probably make upwards of an extra quarter million dollars,” Shah said.

77% of companies are either using or exploring the use of artificial intelligence in their businesses. 

But integrating AI into the sponsorship evaluation and pitch refinement process isn’t about keeping up with the Jones’. The powerful tech can be used to gain deeper insights on a prospective partner, to craft convincing narratives, and ultimately to drive successful tie-ups in an increasingly competitive sports sponsorship landscape.

I recently had a chance to review a sponsorship proposal that was sent from one emerging pro league to a large home improvement brand (think: revenues of $1bn+). While it highlighted some of the property’s strengths, like its use of innovative technology and broad media exposure, the pitch felt generic. 

Moreover, the asking price seemed high relative to the offering.

Now, with the rapid evolution of generative AI, sports sponsorship executives can be certain before pressing send. 

Had the agency behind the proposal simply ran some basic prompts, it could have made the deck more compelling. And it would have realized a significant gap existed —nearly $300,000— between the package’s proposed price and the value of the assets included.

Below is a step-by-step guide for using ChatGPT-4 to enhance sports marketing proposals. I uploaded the startup league’s deck to show how effective prompt engineering can deliver the results desired.

Step 1: Start by taking a comprehensive look at the pitch’s strengths, and more importantly, the areas of it that require improvement. 

The following plain text prompt generated the insights I needed.

“Take on the persona of a sports marketing executive with 20+ years of experience, who has been a Sports Business Journal 40 under 40 winner, a CMO at a professional sports team, and an SVP at an agency like WME or The Marketing Arm. Evaluate the sponsorship proposal for a professional sports league and list out the key strengths and areas for improvement.”

Below is the output from ChatGPT after reviewing the league’s pitch.

7 Strengths:

1. Innovative Technology Integration: Highlighted cutting-edge use of cloud-based systems.

2. Comprehensive Media Exposure: Detailed broadcast metrics and logo placements.

3. Detailed Asset Overview: Clear delineation of partnership assets.

4. Valuation and Financial Clarity: Thorough financial valuation of assets.

5. Exclusive Content and VIP Experiences: Unique access and custom content.

6. Leveraging High-Profile Personalities: Involvement of recognized figures.

7. Diverse Media Platforms: Multi-channel approach ensuring wide exposure.

Areas for Improvement:

1. Engagement Metrics Beyond Viewership: Lacked deeper insights into social media interaction or fan sentiment.

2. Sponsorship ROI Projections: Needed specific ROI projections or case studies.

3. Extended Partnership Opportunities: Could benefit from outlining long-term partnership opportunities.

4. Customization and Flexibility: Emphasizing flexibility to cater to specific brand needs.

5. Enhanced Visualization and Storytelling: Needed stronger visual elements and a cohesive narrative.

Step 2: Implement the suggested changes.

The first four recommendations in our real-world example seem self-explanatory. I used the following prompt to help with enhancing pitch visualization and improving the proposal’s narrative elements.

“As an experienced sports marketing executive, suggest enhancements for the visualization and storytelling aspects of a sponsorship pitch. Focus on how to integrate dynamic content, compelling visuals, and a cohesive narrative to make the proposal more engaging.”

ChatGPT 4.0 suggested we do the following to improve the sponsorship offering and presentation’s flow. We summarized its output for brevity.

1. Dynamic Content:

   • Use interactive presentations (Prezi, Visme) with clickable elements like videos and infographics.

   • Start with a high-energy sizzle reel and include testimonial videos.

   • Offer live demonstrations and showcase real-time data and analytics.

2. Compelling Visuals:

   • Utilize high-resolution images, 3D renderings, and animations.

   • Create infographics for key data points and use color-coded charts.

   • Develop mockups illustrating the partner’s branding in various contexts.

3. Cohesive Narrative:

   • Tell the story of the Command Center with a clear beginning, middle, and end.

   • Include real-life impact stories and quotes to create an emotional connection.

   • Paint a vivid picture of the future with the partner on board and discuss potential growth.

Example Structure for an Enhanced Pitch

1. Introduction: High-energy video and overview of the Command Center.

2. The Story: Narrate the development journey and emphasize innovation.

3. Brand Impact: Showcase brand integrations and testimonials.

4. Data-Driven Insights: Present data through interactive charts and infographics.

5. Emotional Hook: Include quotes and success stories.

6. Future Vision: Discuss the future with the partner’s involvement.

7. Call to Action: Outline next steps and invite the partner to join.

Step 3:  Next, assess the true market value of the sponsorship assets being included. You don’t want to price out potentially interested partners. 

I used the following prompt to get a breakdown of the proposal’s various components. 

“Acting as the sponsorship agency for a home improvement brand with over $1 billion in revenue, estimate the real value of a sponsorship deal with a professional sports league. Consider factors like media exposure, VIP experiences, digital amplification, and naming rights.”

It revealed the package’s actual value was significantly lower than the proposed price.

The Simulated Math:

• Media Exposure: Adjusted for actual engagement rates, valued at approximately $86,572.

• VIP Experiences and Additional Assets: High-engagement potential experiences estimated at $85,000.

• Social Media and Digital Reach: Valued at $25,000, reflecting potential for digital engagement.

• League Rights and Naming Entitlement: Significant brand impact valued at $100,000.

Step 4: Based on the valuations, reduce the proposal’s asking price to between $500,000 to $600,000. Doing so would closer align with the market’s realities and still leave the home improvement brand with room for negotiation. 

Now, the proposal can be sent. 

It's important to note that prompt results and AI recommendations will vary depending on the version of ChatGPT used. 

• ChatGPT 3.5 is free but may miss nuanced insights that some of the more advanced models can deliver. 

• ChatGPT 4 (paid) tends to provide the most accurate valuations and suggestions.

• ChatGPT 4 Turbo (paid) enhances the speed and efficiency of evaluations making it best for real-time analysis.

It should also be mentioned that even enterprise-grade AI is best used as an aid, not a replacement for humans. We’ll address the potential for bias in AI models and the need to ensure accuracy in AI-generated insights in future articles. 

SPONSORED BY PLAYFLY SPORTS CONSULTING

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