It's a tough time to run an attraction. Attendance is trending down, and 3 in 5 IAAPA members say revenue has dipped or stayed flat over the past quarter. When you can't count on more people through the gate, growth has to come from the yield of every guest already inside it.
Getting more from each guest means treating them as an individual. And that starts with knowing who they are. Many larger operators are already unifying their guest data into a single view; if that's you, it's the right foundation.
The instinct from there is familiar: route that profile to a CRM, hand it to a campaign team, and have them build the segments, journeys and campaigns. But that playbook was designed for scheduled marketing. It can't reason about one guest, in your venue, at 2pm in the rain, and it doesn’t support genuine one-to-one communication.
AI changes what's possible. An AI decisioning layer can reason over everything you know about a guest and the live state of your venue, and act in the moment with no segments, journeys or rules for anyone to predefine. You can't do that without the right infrastructure beneath it. This guide sets out what that architecture looks like, and how to get there.
You know all of it. But right on schedule, she gets the same push as everyone else on site: “Don't miss the 3pm parade! ☀️" — the parade that's just been rained off.
Every system did its job. The ticket was sold, the app sent the push, the data landed in a dashboard. Not one of them did anything for her.
Their feed lines up the next-best video. The playlist builds itself. The bank flags the odd transaction before they notice. Against that backdrop, broadcasting the same, pre-set message to everyone on-site feels broken.
Once you’re set up, the instinct is to route that profile to your segmentation team. In the usual setup it lands in a warehouse, feeds dashboards your team reads next week, and gets sliced into segments for their next campaign.
It’s designed to help a person decide what to do later, not to do anything for Jenny while she's still in the park. The knowledge is unified; it just has nowhere to act.
Until now that was analysts and marketers building segments, mapping journeys, writing the rules, and running tests. Even with perfect data, it's slow, broad work: decided in advance, applied the same way to thousands of guests, and capped by how much a team can produce.
A decisioning layer sits on top of the guest profile. AI reasons over everything you know about a guest and the live state of your venue, works out the single best next moment, and recommends it, automatically.
This is what we call Guest Orchestration.
If knowing that they bought lunch shows up tonight, or tomorrow, you've built a reporting system, not a foundation for guest orchestration. To act while the guest is still on site, the profile has to update instantly. That takes two things:
Step two closes the gap: Feed live venue signals into the same layer as the guest profile— weather, queues, capacity, location.
The new one is an agentic decisioning layer: an agent that reasons over the profile plus live context and picks the single next-best action for this guest, in the moment.
Step two closes the gap: Feed live venue signals into the same layer as the guest profile— weather, queues, capacity, location.
The channel matters less than the connection: the action has to flow straight from the decisioning layer to your guest.
