C ASE STUDY
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Custom Propensity Model Positively Impacts the Bottom Line for a Leading National Amusement Park
Propensity Model Development Process
First-Party Data Analysis
Score Users
(Ex. CRM Data)
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Challenge One of the nation’s top amusement parks was only focusing on driving season pass sales, and we saw an opportunity to measure more of what mattered to the brand. We collaborated with the amusement park to identify more ways to measure its success and impact on its business objectives. After determining what business challenges it needed to address, we focused on driving the number of summer park visits per user.
Build Cohorts
Activate and Apply User Bidding
Strategy Our data scientists collaborated with the amusement park’s media analysts to develop a propensity model based on first-party user scoring analysis. We analyzed the first-party data to identify customers with the highest likelihood to convert individually. These insights were leveraged to facilitate various activation strategies, such as utilizing our third-party identity matching solution to activate against the highest value users by pushing the audience segment into the DSP to target.
Success User scoring and bidding analysis unlocked powerful optimization strategies and audience discovery for future campaigns. We identified key factors that drove summer park visits: • Membership Status
• Climate and Geography
• Customers With Kids
• Local Factors
We leveraged these insights to enhance targeting strategies, including retargeting and look-alike modeling that only bid on users most likely to return to their local park.