Using AI to Optimize Your STR Pricing

Jasper sits down at his laptop and shows you exactly how to use Claude to find pricing opportunities in your portfolio, from scratch, in under 30 minutes. No prior AI experience needed. Just PriceLabs and a question.

He walks through a live working session: uploading a single CSV from PriceLabs, asking targeted questions to find overpriced and underpriced nights, and using pacing data to flag periods where the market is booking and you are not.

Freewyld currently manages over 4,000 properties across 75+ clients worldwide and $200 million in annual bookings. That data set informs every recommendation in this episode.

You will hear:

Why AI should support a revenue manager's decisions, not replace them, and how Jasper's team uses it at Freewyld Foundry todayThe problem with 365 price points per listing and why a human can only realistically review 5 to 10% per dayHow to download your neighborhood data from PriceLabs and the exact chart options to have selected before you exportHow to prompt Claude to identify dates where you are currently priced 20% or more above the highest price you have ever booked atHow to refine that analysis to compare like-for-like days: weekdays to weekdays, weekends to weekends, and special events to special events

We also talk about:

How to flip the question and find nights where you are priced below what similar days have historically booked atHow to use pacing data to flag periods where the market is already getting bookings and your calendar has nothing yetHow to use Claude's voice input mid-session and how to teach it the output format you actually wantHow Jasper's team runs this analysis automatically every day across the full portfolio

Mentioned in the Episode:

PriceLabs: pricelabs.co

Free Revenue Audit: freewyldfoundry.com/get-started

Email Jasper: jasper@freewyldfoundry.com

Favorite Takeaway: