Forecasting Success: How Predictive Modeling Helped AEM Shape Exhibitor Outcomes

Case Studies
Written By Todd Snell

How can data predict success before it happens?

For the Association of Equipment Manufacturers (AEM), understanding what drives exhibitor performance at major tradeshows like CONEXPO-CON/AGG is key to delivering value for members and optimizing show strategy.

To help answer those questions, HAI applied predictive modeling—using exhibitor data across multiple years to identify what really influences lead generation, booth performance, and ROI.

The result? A model that didn’t just reflect the past—it forecasted future exhibitor outcomes with clarity and confidence.

In this case study, you’ll see how HAI:

  • Synthesized data from two major events to identify statistical trends

  • Built a live model that accurately forecasted exhibitor leads

  • Translated insights into pricing, booth placement, and marketing strategy decisions

For AEM, these insights turned data points into strategic clarity—helping their exhibitions team make decisions rooted in evidence, not assumptions.

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Explore the full story: Download the Predictive Modeling for Exhibitions Case Study (PDF)

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Todd Snell

My mission is to keep our operations seamless, empowering our team to deliver exceptional, data-driven solutions for associations and their members. From strategic planning to financial management, I oversee the behind-the-scenes so we can stay focused on impact. When I'm off the clock, you’ll probably catch me tinkering in my woodworking shop or rolling up my sleeves to help out in the community.

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In Partnership with AEM: Making the Most of Market Share Data