
Inside AirDNA Adapt: Building the Future of Revenue Management
Revenue management is getting faster, smarter, and more accessible—but building the next generation of pricing technology comes with a surprising challenge: how do you get operators to trust the numbers? In this episode of The STR Data Lab, Chief Economist Jamie Lane sits down with AirDNA’s Data Science Manager Marc Moreno and Senior Product Manager Jordon Myers to go behind the scenes of building AirDNA’s new revenue management platform, Adapt. The conversation explores what AirDNA learned from hundreds of conversations with STR operators, including the surprising number of hosts still managing pricing manually and the widespread frustration with opaque pricing recommendations. Marc and Jordon explain why explainability became a core design principle, how millions of listings and noisy data shaped the modeling process, and why some of the most promising AI approaches had to be reconsidered. They also unpack how AI has fundamentally changed the product development process—from months-long handoffs to rapid prototyping, testing, and iteration with real users. Looking ahead, the team discusses where revenue management is headed as AI agents, APIs, and new data interfaces become more common. The future may not be about forcing operators into another dashboard—it could be about making reliable revenue management data and recommendations accessible wherever operators already work. You don’t want to miss this behind-the-scenes look at how the future of STR revenue management is being built. Key Takeaways Trust is just as important as accuracy. A pricing recommendation is only valuable if operators understand where it came from and feel confident acting on it. Clean data is the foundation of good pricing. With millions of listings across multiple channels, filtering noise and engineering the right signals can be just as important as the model itself. Events require proactive pricing. Rather than waiting for demand to appear in the data, revenue management systems need to identify external signals early enough to adjust pricing before bookings happen. AI is changing how products are built. Rapid prototyping and AI-assisted development allow teams to test ideas with real data and users much faster than traditional product-development cycles. The future may extend beyond the UI. As operators increasingly use AI agents, APIs, and their own internal tools, revenue management data needs to be accessible wherever decisions are being made. Sign up for AirDNA for FREE 👇 https://bit.ly/4j6s6qy ————— Connect with Jamie on social media LinkedIn: https://www.linkedin.com/in/jamiehlane/ Twitter: https://twitter.com/Jamie_Lane ————— Jordon Myers - Senior Product Manager: https://www.linkedin.com/in/jordon-myers/ Marc Moreno - Data Science Manager: https://www.linkedin.com/in/mmorenol/ ————— Connect with AirDNA on social media: Instagram: https://instagram.com/airdna.co LinkedIn: https://www.linkedin.com/company/airdna/ Twitter: https://twitter.com/airdna TikTok: https://www.tiktok.com/@airdna.co ————— Episode 195















