Universal Parks & Resorts transforms their customer data ecosystem on AWS
Universal Parks & Resorts (UPR) sought to build a 360-degree view of their guests to transform from a transaction-centered approach to person-centered for better insights. However, the theme park would need to integrate guest data from disparate marketing systems if they were to create such a 360-degree view. Additionally, UPR's data quality only gave an acute view of their guests with only fractioned pieces of information being provided by their systems. Previous attempts were met with limited success due to lack of scalable, highly performant, and economic computing platform.
Merkle and Universal Parks & Resorts mutually concluded that Amazon Web Services (AWS) would be the ideal platform to build the proposed solution. AWS provides fully managed storage, computing, and analytics services on its platform, thereby resulting in faster time to value, and ease of development.
Merkle helped integrate the park's guest data, transactions and interactions on an AWS-based, cloud-native solution while enabling its data science team to segment guests more granularly to create personalized offers.
As part of this, Merkle developed a marketing data platform on AWS that allowed the theme park company to ingest guest data from multiple source systems, resolve guest identity across systems and link them together. The cloud-based environment served as the focal point for data consumption by various theme park company teams to understand guest activity and experience in the park, to segment guests for marketing purposes, import marketing lists into a campaign tool for personalized offers, and for deriving analytical insights such as guest propensity to visit the park, perform certain activities, etc.
Further, to enhance existing data quality, the team generated global unique identifiers for guests, standardized and cleansed all PII information through various different Merkle proprietary tools under its Merkury suite of products. Having a global identifier attached to each guest allowed the park to link the guest activity across disparate systems and generate insights which were previously not possible.
Merkle also leveraged its data asset called Data Source for reverse email and phone appends to create a more complete PII profile of an individual. Data Source also helped enrich the PII profile with demographic elements which were previously not available to the themes park entertainment company, such as age, household income, number of children in the household, etc. These additional elements provide important information to marketers to granularly segment the audiences for personalized campaigns.
Merkle used the following services from AWS services to build the solution:
Redshift: Cloud based database to build and host guest 360 view
AWS Elastic Computing Cloud: Compute machines to build Python based data pipelines using Merkle proprietary Data Loading Framework (DLF)
AWS Simple Storage System: Landing area for raw data acquired from disparate source systems
Elastic Container Service: Airflow containers for orchestration of data pipelines
Relational Database Service: Postgres database to store metadata from Airflow and Microsoft SQL Server for data pipeline metadata
How did Universal Parks and Resorts put data agility at the heart of experience transformation, in order to master the rapidly changing approaches to the acquisition, management, mining and activation of data in real time and in a privacy-safe manner so that they can continue meeting their customers’ needs?
records were processed from 15 different raw feeds
records were enriched with additional demographic attributes
Ability to analyze 20M identified guests on an annual basis
deployed to production in 3 months
Keys to success
- Integrating guest transactions and ticketing data to develop Guest 360 view on AWS
- Enabling personalized campaign capabilities in a flexible, nimble, scalable, high-performing Cloud environment
- Rapid deployment to enable media and CRM teams with faster time to value
- Focus on business-critical use cases for Minimum Viable Product (MVP)
- Continuous enhancements to MVP over time for additional features and functionalities