Extracting Hidden Consumer Insights
Applying user propensity modeling helped to unlock new audience discovery and optimization strategies for a national amusement park brand.
One of the nation’s top amusement park brands looked to expand its focus beyond driving season pass sales. Through multiple collaborative brainstorms, Goodway recommended focusing on increasing repeat summer park visits for season pass holders as the highest leverage strategy to impact short-to-medium-term business objectives.
Goodway data scientists worked in concert with our client’s business intelligence group to develop a propensity model based on first-party, season pass holder data. We were able to identify customer traits that predicted a high likelihood of repeat park visits and used these insights to drive audience-based media activation strategies.
Our propensity model results unlocked previously unconsidered optimization strategies and opened up potential new audiences our client could tap and target in future marketing campaigns. Additionally, these learnings helped us enhance existing tactics, including retargeting and look-alike modeling, that focused our efforts on targeting users most likely to revisit their local amusement park.
From data ingestion to regression analysis, it was critical to collaborate with all of our client stakeholders and our internal Goodway team throughout this unique and productive engagement.
Results
Our propensity model gave us insight into the ideal audience the amusement park should target:
17%
Park members predicted as highly likely to be repeat visitors
2x
Increased repeat visit likelihood for dining pass holders
1M+
Predictions made from first-party data analysis
