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What are You Actually Measuring For? Why Event Data Only Works When it has a Job to do.

  • Sep 1
  • 4 min read

data measuring

You can measure everything. But should you?


Footfall. Dwell time. Heatmaps. Bounce rates. Scan ins. Sentiment analysis. Sensor triggers. Exit flows. Social mentions. Engagement scores. Everyone from the brand manager to the safety officer has their own dashboard. The question is: who’s using it?


In today’s event landscape, there’s no shortage of data. The challenge is making it matter.


We’re not here to bash dashboards. We’re asking something different:


What are you actually measuring for?


Because unless the data is connected to a real operational or creative decision, it’s just noise with a password.



The Familiar Scene: Post Event Dashboard Dump

It’s the Monday after the big show. Everyone’s back at their desks, inboxes exploding. The wrap up report arrives. It’s a sleek PDF. Graphs, charts, heatmaps. Someone even made a pie chart that looks suspiciously like a doughnut.


You open it. You skim. You forward it. And then?


Nothing.


Not because it isn’t well designed. But because you’ve got 200 other decisions to make. And the report doesn’t answer any of them.



The Data Cliff

Event teams aren’t data phobic. In fact, they’re often drowning in it. From RFID badges to crowd density sensors, tech has made it easier than ever to track movement, mood, and moments. But more often than not, teams find themselves on the edge of a data cliff:


  • They collect everything in the name of future proofing.

  • They summarise everything into sleek, colourful reports.

  • Then they move on, because no one has time to decode it all post show.


So the same cycle repeats. New event, same noise.



The Case for Purpose First Metrics

Instead of starting with the tech, start with the question.


  • "Do we need more toilets at the west gate?" → Track queue length and dwell time in that zone.

  • "Which content format keeps people in their seats longer?" → Compare engagement scores and retention between formats.

  • "Did this sponsor activation change behaviour or just attract footfall?" → Look at before/after movement patterns, not just dwell time.


The best data strategies are built backwards: from the decision you need to make, to the metric that can support it, to the tech that can collect it.



Real World Proof: Less is Often More

Here’s how smart teams are rethinking data to make it actionable:



1. HubSpot at INBOUND 2023

Rather than measure every possible interaction, HubSpot narrowed focus to what would actually inform next year’s show: session participation, social engagement, and survey feedback. That’s it. And it worked. They gained high quality insight because they ignored vanity metrics. In practice, this meant they could identify not only which talks pulled the biggest crowds, but also which ones sparked the longest post session online discussions; a direct line between programming choices and audience resonance.



2. Bloomberg: Soft Data with Hard Purpose

RJ Crowder Schaefer at Bloomberg has been vocal about aligning tech with intent. They prioritise contextual insights: like what stakeholder group needs what data, when. For example, instead of obsessing over total attendance, they’ll zoom in on things like how investor focused breakouts compared to general sessions, or whether registration flows slowed at specific times of day. Sometimes, the decision isn't about the highest numbers; it’s about the most relevant friction point.



3. Event Tech Live (via Exposure Analytics)

At Event Tech Live, heatmaps and dwell time data were combined with exhibitor goals. The team adjusted staffing patterns and demonstrated clear ROI to sponsors. For example, they noticed peak footfall around mid morning coffee breaks and redeployed staff accordingly, reducing queue times and increasing engagement. Exhibitors were given concrete evidence of lead generation tied to those time windows, not just vague footfall reports. They didn't just measure; they made the data do something.



4. Event Footprints

Event Footprints specialise in aligning metrics with post event outcomes, not just marketing fluff. They use attendee behavioural data to power CRM linked insights that support lead scoring and content strategy. For example, instead of a generic “attendees spent X minutes on average,” they can show sales teams which individuals engaged with which sponsor content, directly feeding into follow up conversations.



What Not to Do: Common Pitfalls We See (Too Often)

  • Measuring for measurement’s sake. “Let’s track it, we might need it later.” Spoiler: you won’t.

  • Letting the platform dictate the plan. Just because your platform offers 18 types of heatmaps doesn’t mean they’re all useful.

  • Focusing only on what’s easiest to measure. Often, the most critical insights like emotional resonance or friction points require context, not just click rates.

  • Treating data as a report, not a conversation. Dumping it in a post show PDF rarely prompts action.


How to Build a Purpose First Data Strategy

If you’re planning your next event, here’s a simple framework:


  1. Start with the questions. What do we need to know to make this event better?

  2. Identify the decisions. Who needs to act on that data, and when?

  3. Choose metrics that align. Only collect what supports those decisions.

  4. Build in interpretation. Who’s going to turn raw numbers into insight?

  5. Design for re-use. Can this data feed sponsor reports, stakeholder updates, ops planning?


This isn’t about collecting less, it’s about collecting smart.



What This Means for Event Teams

  • Don’t start with the platform. Start with the problem.

  • Align your data capture with specific roles: what do ops leads need? What does the creative director need? What does your sponsor actually care about?

  • Limit your dashboard. Yes, really. One dashboard per decision area is often more useful than one mega board that serves no one.

  • Use data as a tool for storytelling, not just reporting.


To Be Clear: We’re Pro Data. But Even More Pro Clarity.

At The Imagination Collaborative, we work with teams juggling creative vision, compliance stress, spatial constraints, and sponsor pressure. Measurement is vital. But insight only emerges when the noise gets filtered.


Good data doesn’t just describe the event. It shapes the next one.



Seen smart data use in the wild? We’d love to hear about it.




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