The Javier Effect: How to Price Unique STR Inventory With PriceLabs

Javier Vasquez, one of Freewyld Foundry's revenue managers, joins Jasper to walk through a pricing strategy he built from scratch for a portfolio of glamping dome units near Toronto. These units run at 97-98% occupancy year-round with booking windows of up to 212 days and a waiting list. Because they attract destination travelers who book specifically to stay in those units, standard PriceLabs market factors did not apply. So Javier turned them off entirely and built a custom Portfolio Occupancy-Based Adjustment matrix instead. The result: ADR jumped from $493 in July to $565 in August. Jasper and Javier walk through the full setup live, including the screen share.

You will learn:

What Portfolio Occupancy-Based Adjustment is in PriceLabs, and why it is the right tool when your inventory does not follow regular STR market patternsWhy Javier turned off both seasonality and demand factors entirely for this portfolio, and what that changes about how the base price worksHow the matrix calculates occupancy on a per-day basis rather than a date-range basis, and why that distinction is critical for high-demand destination inventoryHow to build separate matrices for different unit types and day-of-week patterns, including why Sundays need their own factor separate from weekdays and weekendsWhat the Javier Effect looks like in the data: ADR from $493 in July to $565 in August within two months of implementing the strategyHow to use the PriceLabs pacing dashboard to monitor whether a new strategy is working and where to adjust

We also talk about:

How to tell when your inventory warrants a custom strategy versus following standard market factors: the main tell is that your occupancy and booking patterns do not look like the market around youWhy last-minute discounts are built directly into the matrix for this portfolio, eliminating the need for separate last-minute discount settings in PriceLabsThe difference between regular occupancy-based adjustments (date-range basis) and portfolio occupancy-based adjustments (per-day basis), and why the distinction mattersHow booking windows shaped the date range columns in the matrix: 212 days for Forest Domes, 140 days for the middle units, and why a 366+ day column was added after October 2027 bookings started arrivingWhat the pacing report shows heading into October: ADR $30 higher than the same period last year with occupancy also aheadWhy most of the measurable impact so far is coming from weekday dates, and why the weeken