How Generative AI Will Enhance the Future of Event Measurement
Last month, we began to explore how AI is impacting event measurement. We felt it was important to go a little deeper and share some examples of what we might expect. Generative AI, defined as a set of algorithms that can create new content such as text, imagery, audio or synthetic data, has the potential to significantly enhance how marketers analyze event data in the future. Here are a few ways this could happen:
Improved data analysis: Generative AI can be used to analyze vast amounts of event data and generate insights that marketers can use to inform their strategies. For example, it can identify patterns and trends that might be missed by human analysts, and highlight correlations that could help marketers make better decisions. As with any data analysis, using AI will be about asking the right questions. Marketers will need to experiment and learn how to phrase queries so that the machine provides usable insights as a result. Similar to learning to get the best results from searching the web, effectively working with Generative AI will be a new skill, even if the AI is really intuitive.
Personalization: Generative AI can be used to personalize event experiences for attendees based on their preferences and behaviors. Imagine technology that makes recommendations about event content an attendee should check out (that is customized to their profile), or which helps them find a person they really should meet at a buzzing networking session. Imagine personalized follow-up surveys that reference specifically what guests have experienced at a given event. The possibilities are incredible - limited only by an event marketer’s creativity… and perhaps your budget.
Chatbots: Generative AI can be used to create chatbots that can interact with event attendees in real-time. These chatbots can provide attendees with information about the event, answer questions, and provide personalized recommendations based on attendee interests. Furthermore, marketers can use these chatbots to understand elements of the event or experience that are not as intuitive, allowing for iterative development or increased clarification.
Accessibility: Technology can help make experiences more equitable by using personal data, shared anonymously, to ensure that the event is accommodating diverse needs and preferences across an array of backgrounds (for example, providing assistive tools for people with neurological differences or recommending environmental considerations for physical needs).
Predictive analytics: Generative AI can use event data to make predictions about future events, such as attendance numbers or potential revenue. This information can be used by marketers to plan and execute more effective marketing campaigns.
Overall, generative AI has the potential to transform how marketers analyze event data, and help them make more informed decisions about their event strategies.