Using AI to Improve Sponsorship ROI

This blog was originally published on The Sponsorship Guy Blog.

Sponsorship is a powerful marketing practice that can help businesses increase brand awareness and customer engagement. However, with the rise of artificial intelligence and data analysis, sponsorship has taken on a new dimension, with AI providing insights and predictions that were previously much more difficult to derive. Let’s explore the power of data and how AI can be used to improve sponsorship return on investment (ROI).

Benefits of AI for Sponsorship ROI

Improved Targeting and Personalization: AI can help companies understand their customers’ behavior and preferences, enabling them to tailor their sponsorship activities to meet their specific needs. This way, companies can provide a more personalized and engaging experience for their customers. Salesforce Einstein is one example of a tool that makes it easy to target specific audiences and build richer relationships faster. 

More Effective Activation and Engagement: AI-powered chatbots and virtual assistants, like the ones provided by Quickchat, can engage with customers in real-time, providing them with the information they need about sponsorship events and activities. This kind of engagement can help you build a stronger relationship with your customers and helps you meet your customers where they are. You don’t need to be working at all hours of the day and night to help them.

Better Measurement and Optimization: AI can provide companies with real-time analytics and insights into their sponsorship activities, enabling them to optimize their strategies for better ROI. Platforms like Adobe Analytics provide data that companies can use to measure engagement levels, attendance rates, and other metrics to gain a better understanding of their sponsorship performance.

How AI can be used in sponsorship

Companies can use AI in sponsorship in a variety of ways, including:

Data Analysis and Predictive Modeling: AI can analyze customer data and provide predictive modeling to help companies make informed decisions about their sponsorship strategies. By analyzing data, companies can predict customer behavior and preferences, which can help them optimize their sponsorship activities. PecanAI is one example of software designed to turn data into intelligent predictions.

Chatbots and Virtual Assistants: Again, the power of AI-powered chatbots and virtual assistants cannot be overstated. By engaging with customers in real-time, providing them with personalized information about sponsorship events and activities, customer experiences can be efficient, tailored, and standardized. Platforms such as IBM’s Watson Assistant deliver high engagement scores that can help companies build stronger relationships with their customers.

Increase email deliverability: AI can assist you in easily generating subject lines and email content for your sponsorship outreach. The platform Phrasee uses AI to analyzes company’s historical email performance data to create subject lines that are more likely to drive engagement and conversions. This will allow you to compare A/B tests on subject lines and clicked links to see what content inspires your target audience to reach out to learn more. 

Building Personas of Your Intended Audience: AI can be used to drill down and research key organizations in your particular niche. This will help you create a clearer picture of who your audience is and what companies might fit in it. Pulsar is a platform that uses CRM data to create detailed audience personas so that you can create actionable and segmented campaigns. You can use AI to filter down by location, size of the company, and more. Just keep in mind, as of March 2023, even the new GPT4 language model has limited knowledge of events before September 2021. 

Best practices for using AI in sponsorship

Here are some best practices that companies can follow when using AI in sponsorship:

Ensuring Data Privacy and Security: Companies should ensure that they have the necessary data privacy and security measures in place to protect their customers’ data. One of the primary security concerns when using AI is the protection of the data it uses. Companies must ensure that the data used to train and operate AI systems are secure from cyber threats such as hacking, data breaches, and malware attacks. This requires implementing robust data privacy and security measures that comply with relevant regulations such as GDPR, HIPAA, and CCPA.

Training and Upskilling Staff for AI Adoption: Companies should invest in training and upskilling their staff to ensure that they are equipped to handle AI technologies and tools effectively. One way to train and upskill employees in AI is to provide relevant training courses and workshops. These courses can cover topics such as machine learning and data analysis, Companies can also offer online training resources, such as video tutorials, webinars, and e-learning modules, to help employees access the training materials at their convenience. Another way to upskill employees is to provide hands-on training through projects and collaborations. 

The power of data and AI cannot be overstated when it comes to improving sponsorship ROI. By leveraging these technologies, brands can achieve more effective targeting and personalization, activation and engagement, as well as better measurement and optimization. Real-world examples have demonstrated the potential impact of AI on sponsorship, from chatbots to predictive modeling and data-driven optimization. It is essential to follow best practices in choosing the right tools, ensuring data privacy and security, and upskilling staff for adoption. As the sponsorship landscape continues to evolve, brands that embrace the power of data and AI will have a competitive advantage in achieving their sponsorship goals and driving ROI.