EVENT

No Show Prediction

MACHINE LEARNING

The client, a leading B2B trade show organiser, manages hundreds of events annually with tens of thousands of registrants, and was struggling to reliably predict attendance. Through structured collaboration with their marketing and data teams, we explored the challenge and identified the key drivers affecting visitor participation.

Agoya helped define a clear approach to better understand attendance patterns and prepare the organisation for a smarter, data-driven solution, laying the groundwork for the predictive model and targeted interventions described in the following sections.

#CHALLENGE

Reducing event No-Shows at scale

The client faced a growing operational challenge, managing over 200 events annually across multiple industries and countries. Their business model relies on exhibitors paying to participate while visitors attend for free, resulting in tens of thousands of registrants, yet nearly 40% of registered visitors never show up.

As events scaled, manually identifying which registrants were likely to attend became impossible for the marketing team. Sending reminders and communications to all registrants was costly, inefficient, and risked missing the most impactful opportunities. The client needed a smarter, data-driven approach to focus efforts where they mattered most and improve attendance rates.

#SOLUTION

Machine Learning to focus effort where it truly matters

Agoya partnered closely with the client’s marketing and data teams to develop a predictive machine learning model.

Daily predictions of likely no-shows: The model analysed registration patterns, historical attendance, and contextual data for each event.
Targeted marketing workflows: High-risk registrants were flagged for focused communications, ensuring outreach was efficient and personalised.
Human + AI collaboration: Marketing teams could review AI suggestions and adjust campaigns, combining expert intuition with data-driven prioritisation.
Scalable and adaptable: The system continuously updated predictions, allowing teams to handle hundreds of events without additional workload.

The solution turned raw registration data into actionable insight, giving the client a repeatable framework to improve attendance across all events.

#OUTCOME

Higher attendance, lower costs, stronger exhibitor satisfaction

The predictive model delivered immediate, measurable impact:

Focused engagement: Marketing campaigns concentrated on registrants most likely to miss events.
Reduced costs: Fewer unnecessary reminders, lowering overall marketing spend.
Higher attendance: Targeted interventions improved visitor turnout.
Scalable solution: Hundreds of events and tens of thousands of registrants managed efficiently.
Improved exhibitor satisfaction: Better attendance increased perceived value and strengthened relationships.

What was once a manual, resource-intensive challenge became a data-driven growth lever, combining human expertise with AI to maximise attendance and operational efficiency.