How data analysis is informing event design

This global tech brand’s annual user conference generated consistent attendance and buzz. But in today’s digital age, any brand must stay on the forefront of what keeps attendees coming back for more, then exceed expectations once on site.

user conference attendees networking during break

Profitably engaging 8,000+ enterprise IT attendees from around the world is no small task, especially in a tech landscape primed with disruption. That’s why event leaders looked to ITA Group—their partner of 10+ years—and its event analytics team to conduct an attendee analysis. The goal? Impact audience engagement and overall event profitability by answering burning event design questions like these:

What event strategy and design elements created the most value?

Where were attendees optimally engaging, and where was engagement correlating with sales?  

Were “ancillary events” creating intended and worthwhile value?

Were the optional pre- and post-event opportunities, like VIP events and dedicated “developer days,” living up to their potential, or should other investments within the larger fixed event budget be prioritized?

Data Collection Revealed Most Profitable Attendee Segments  

Nine unique sources. A host of formats. 130+ data points. Using event strategy and design expertise, the ITA Group team transformed robust raw data into a model that laid the groundwork for further analysis on key event trends and insights that revealed themselves along the way. 

130 Data Points (Examples)

  • Attendee role/title
  • Role in organization
  • Company size
  • Content track sessions including duration, day and session type

9 Unique Data Point Sources (Examples)

  • Event app
  • Registration data
  • Marketing tool 
  • Sales data

Data Analysis Indicated Key “Likelihood of Sale” Findings

The consolidated data did its job, creating clear insight into how attendee segments and on-site engagement influence post-event purchasing behaviors. 

  • Some Attendee Roles Are More Profitable—Analysis revealed three roles with a higher likelihood of sale.
  • More Isn’t Necessarily Better—Not when it comes to ancillary event attendance, anyway. Sales probability dropped off beyond two ancillary events attended, and findings showed ancillary event attendees craved more targeted content. 

Not All Session Types Are Created Equal

  • Session Structure—Overall, two specific session structures were shown to reduce likelihood of sale the more sessions an individual attended. 
  • Panels—Individuals who attended more than one panel session were significantly less likely to buy. 
  • Personalized Content Is Critical—Sales probability jumped significantly with role-specific sessions and trainings with deeper content, indicating content depth outweighs content volume.  

Today, Data Segmentation Informs Event Design 

Optimal value lives here. With a set budget guiding the process, event owners can pinpoint which attendee segments to target, how to best engage them during the experience and how to design each subsequent experience to maximize potential sales. 

graphic of predictive model

Predictive Model Prioritizes Year-Over-Year Strategy

Agenda segments. Breakout session types. Content suited to boost future sales likelihood from individual attendees. Besides validating data collection assumptions with machine learning simulations, the trained predictive model uses a host of variables to personalize the on-site attendee experience. And the long-term tool is designed to continually inform event leaders about variables that impact likelihood of sale. 

Seeing our data analyzed to this degree shed light on things we never would have spotted before. Looking at sale probability numbers per activity ... was eye-opening and will enable us to make better decisions on ... how to segment our data to the right audience.

Client Stakeholder