Great Wolf Lodge spent too much time second-guessing and over-riding its revenue management system, leaving less time to test new revenue strategies. The family-oriented resort brand had automated pricing in place, but without sources of actionable information like web shopping data, it could not adequately refine its forecasting and pricing practices.
Partner with Duetto, whose Open Pricing philosophy fits Great Wolf’s view of revenue management, and use its application’s data sets to test and refine new strategies. Great Wolf and Duetto also developed a modification to the GameChanger application to enable the brand’s new strategy for growing total resort profitability by way of increased occupancy.
Alan Genin, Senior Vice President of Revenue and Ecommerce at Great Wolf Lodge, commented, “It’s really turned our revenue management system into a tailwind instead of a headwind. We’re spending a lot less time managing and second-guessing the system. It’s allowed us to find answers to tough questions very quickly and then optimize on them.”
“We’re spending a lot less time managing and second-guessing the system.”
Great Wolf sought to grow total resort profitability by encouraging greater on-site ancillary spending, which put a high value on driving more occupancy. Duetto modified the GameChanger application to incorporate the marginal spending for Great Wolf’s different suite types into the brand’s forecasts, giving Great Wolf the confidence to fill rooms and still be able to increase RevPAR.
Alan added, “The combination of Duetto being a true software-as-a-service product, as well as just generally progressive and nimble, enabled us to get the enhancement through quickly. We saw that impact on our business over the summer.”
How it Happened
- Implemented GameChanger application, replacing an RMS unable to execute Open Pricing or ingest web shopping data.
- Used web regrets and denials data to test and refine pricing and marketing strategies.
- Shifted Revenue Strategy to optimize profitability by driving occupancy and total on-property spend.
- Spent less time second-guessing pricing recommendations and more time analyzing data and forming strategies.