Enhancing Theme Park Experience for Customers through Data Modeling

Executive Summary

A prominent leader in the entertainment industry faced challenges in managing a high volume of visitors and providing a personalized experience for their customers at their theme parks. The queue length for the park rides kept increasing during peak season, resulting in a significant reduction in customer satisfaction. To tackle these issues, Factspan collaborated closely with the client to develop a data-driven solution.

By employing a bidirectional machine learning model and integrating data from multiple sources, across operations and customer data platforms, the team successfully devised an all-encompassing solution to optimize park visits, reduce wait times, and enrich customer experience. The team enhanced the existing system to provide customers with real-time ride wait-time information and efficient navigation support. It resulted in a significant increase in customer contentment, a surge in revenue generated from customer spending, and a marked improvement in operational efficacy.

About the Client

The client is one of the prominent players in the entertainment industry, dedicated to delivering exceptional customer experiences at their theme parks. The client operates in many cities and across multiple countries. The theme parks are based on popular movies and characters. They attract millions of people each year, generating billions in revenue and providing significant employment opportunities, while creating memorable moments for their customers.

Business Challenge

The client faced the challenge of managing long queues and providing personalized recommendations to enhance customer experiences at their theme parks. During the peak season, the existing operational model showcased ineffectiveness, leading to customer dissatisfaction and suboptimal allocation of resources.

The client recognized the importance of a scalable and data-driven solution to address these challenges effectively. They aimed to optimize wait times, improve customer satisfaction, and increase revenue through enhanced customer spending. To achieve these goals, they sought the expertise of Factspan, leveraging their data warehousing and AI capabilities.

Our Solution

The Factspan team seamlessly integrated data from various sources, including park operations, visitor profiles, and ride wait times. By utilizing the power of BERT (Bidirectional Encoder Transformers), personalized recommendations were generated for each customer, enabling them to optimize their park visit and avoid long queues. This personalized approach enhanced customer satisfaction and ensured a memorable experience.

To facilitate seamless communication, Factspan worked with the client to provide their customers with instant ride information, navigation assistance, and personalized recommendations, enhancing every facet of their park exploration.

Factspan’s solution also focused on data movement and transformation. Leveraging AWS batch framework, our experts designed and implemented efficient ETL pipelines for data movement between Snowflake tables. This included ingesting files into Snowflake and performing necessary transformations to enable data scientists to utilize customer information for future recommendations and related services

Business Impact

Factspan’s solution has had a positive impact on the client’s theme park operations. It has effectively optimized resource allocation, improved operational efficiency, and allowed the client to create exceptional experiences for their customers. It also led to

• 20% reduction in average wait times
• 15% increase in customer satisfaction scores
• 10% rise in revenue from increased customer spending