Transforming Theme Park Operations with AI-Powered Queue Insights

United Parks & Resorts leverages AI-driven queue monitoring to deliver accurate wait times across 66 rides, transforming guest experience and operational efficiency.

Overview

United Parks & Resorts Inc. (NYSE: PRKS) is a leading theme park and entertainment company, as well as a global leader in zoological care and conservation. Through immersive experiences, thrilling attractions, and meaningful wildlife encounters, the company inspires guests to protect the animals and the wild wonders of our world. With a diverse portfolio of award-winning park brands—including SeaWorld®, Busch Gardens®, Discovery Cove®, Sesame Place®, and Aquatica®—the company operates 13 parks across the United States and Abu Dhabi.

As part of a broader digital transformation initiative, United Parks & Resorts invested in developing new in-park companion apps designed to enhance the guest experience. These apps were designed to help visitors navigate the parks more efficiently, ensuring they could make the most of their visit. A key aspect of this initiative was optimizing how guests managed their time—a crucial factor in maximizing their enjoyment at the park.

With limited hours and numerous attractions, time is the most valuable commodity when visiting a theme park. Guests need the ability to plan their day effectively to experience as many rides as possible rather than spending excessive time in queues. Recognizing this, United Parks & Resorts prioritized integrating real-time ride wait time predictions into the apps, enabling guests to make well-informed decisions and optimize their park experience.

Challenges

United Parks & Resorts faced several challenges in providing accurate ride wait times:

Inaccurate Wait Time Predictions

Previously, ride operators visually scanned the lines and estimated wait times, calling in updates every 20 minutes. However, these updates were inconsistent, often missed, and heavily dependent on the operator's experience. Many were seasonal employees with limited training, leading to fluctuating and often inaccurate estimates. Additionally, queue dynamics changed more frequently than the update cycle, causing posted wait times to be outdated and unreliable. The previous app did not display wait times, further limiting guest planning capabilities.

Widespread Customer Dissatisfaction

Inaccurate wait times were the number one guest complaint. Guests voiced their frustrations through negative reviews on iOS and Android app stores, noting the lack of reliable wait time information. The disconnect between expected and actual wait times disrupted their schedules, affecting overall satisfaction and the park's reputation for delivering a smooth, enjoyable experience.

Limited Scalability of Traditional Solutions

Alternative solutions lacked the necessary accuracy and adaptability. These systems struggled with frequent recalibrations, maintenance challenges, and difficulties in adjusting to dynamic queue conditions, making them unsuitable for a large-scale, high-traffic environment.

Solution

United Parks & Resorts set clear objectives for the project: achieving at least 85% wait time accuracy, ensuring scalability across 73 rides, and implementing an efficient solution that could be sustained long-term. To meet these goals, the company conducted an extensive time study to evaluate the accuracy of its existing wait time estimates. This assessment identified the rides most in need of improvement, guiding the prioritization process.

To address these challenges, United Parks & Resorts evaluated multiple solutions, including beam breaker sensors. However, these alternatives failed to meet the accuracy and scalability requirements due to frequent recalibration needs, algorithmic tuning difficulties, and limitations in dynamic queue conditions.

Recognizing the need for a more reliable and scalable approach, the company sought a solution that delivers real-time queue monitoring and accurate wait time estimates. This led to a partnership with Dragonfruit AI, whose computer vision-based solution offered the precision, flexibility, and maintainability required to meet United Parks & Resorts' goals.

The decision to implement an AI-driven queue monitoring system was based on several key factors:

Higher Accuracy & Reduced Maintenance

Unlike beam breaker sensors, the AI-powered system continuously analyzes queue movement, adjusting for fluctuations in real-time without requiring frequent recalibrations.

Scalability Across Rides & Attractions

Designed for seamless expansion, the solution was deployed across 66 rides in a structured, two-year rollout, proving its adaptability and effectiveness.

Versatility Beyond Rides

Existing cameras were repurposed, extending the system's functionality to restaurant queue lines and other high-traffic areas.

Cost Efficiency

The ability to use current infrastructure reduced capital expenses, while automated updates minimized ongoing operational costs.

Enhanced Reporting & Performance Monitoring

The system provided detailed analytics on ride wait times, helping optimize operations and improve guest flow.

The ability to reuse existing cameras made deployment more cost-effective and future-proof. Additionally, the system's low maintenance requirements ensured long-term reliability, reducing the need for frequent recalibrations and upkeep.

Deployment & Refinement

The rollout required close collaboration between United Parks & Resorts' digital team, Dragonfruit AI, and park operations teams. Implementation involved:

Infrastructure Setup

Ensuring proper power and network connections for camera systems.

Training & Tuning

Fine-tuning the AI models to adjust for different ride dynamics.

Gradual Expansion

Scaling the system across 66 rides in a phased multi-year approach.

Ongoing Refinement

Regular audits, recalibrations, and algorithmic tweaks to maintain high accuracy levels.

Impact

The results of this initiative directly addressed the challenges identified:

Aligned with Guest Experience Goals

By providing real-time, accurate wait times, the system improved park planning capabilities and enhanced guest satisfaction.

Fewer Guest Complaints

With reliable wait time information, negative app reviews and guest frustrations over unexpected delays were greatly reduced.

Sustained High App Ratings

The introduction of accurate wait times reinforced positive feedback and reduced complaints.

Operational Improvements

Park operators gained valuable data insights to optimize guest flow and ride efficiency, driving continuous operational enhancements.

"Our partnership with Dragonfruit AI has been transformative in addressing one of our guests' biggest pain points. By deploying a powerful AI-driven solution, we've not only enhanced the guest experience with more accurate wait times but also improved operational efficiency across our parks. This collaboration exemplifies how technology and strategic partnership can drive meaningful improvements at scale."

Next Steps

Building on the success of the solution by Dragonfruit AI, United Parks & Resorts plans to:

Expand to Additional Rides & Attractions

Bringing the AI-driven solution to more park locations to further enhance guest planning.

Refine Accuracy for Existing Deployments

Ongoing AI model enhancements to optimize prediction precision.

Extend to New Use Cases

Leveraging the system for restaurant queue times, park hour monitoring, and other guest services.

Deepen the Partnership with Dragonfruit AI

Continuing collaboration to drive future digital transformation efforts.

Through this ongoing relationship, United Parks & Resorts continues to lead in guest experience innovation, leveraging Dragonfruit's advanced AI technology to deliver a seamless and enjoyable visit for every guest.