I’ve been working on a ground-up townhome development in Sevierville, TN and thought I’d share a few observations for anyone looking at STR-focused projects in high-tourism markets.One thing that’s become very clear is that designing specifically for long-term operational durability matters just as much as initial projections.

That’s worked well, but as I look toward the next phase (and eventual retirement), I want to intentionally shift from appreciation-driven growth to stable, income-focused investing for retirement income  I’m considering deploying ~$2M to buy 4-6 properties in all cash.

Thanks for sharing the data—that’s actually really helpful and lines up with what I’ve seen as well.

And that decision is mostly driven by one thing: does this listing make Airbnb money?

Software can pull the data, but you still need to understand WHY certain comps are higher or lower.

If your unit is sitting for more than 21 days, your process is broken.Here is how we keep vacancies low and tenant quality high:Data-Driven Pricing: Don't guess.

Curious what other hosts think about this.We’ve tried using AirDNA and similar tools to gain more insights into our listings’ performance but came up empty.I find myself obsessing more about our own year-over-year numbers e.g. this February vs last February or this years booking pacing vs last years booking pacing.Market data tells us what we already know: we are top tier and our listings don’t fit in the regular market trends.

Proximity to downtown and universities sounds great on paper, but you really need to dig into short-term rental regulations and actual AirDNA-style revenue data to see if hosts are consistently hitting occupancy.If your long-term goal is scaling, your first deal should prioritize strong, repeatable cash flow over speculative appreciation.

Week of February 23, 2026 in ReviewHousing data continues to show resilience.

All of the data on New Braunfels properties came from Mashvisor, which uses AI to generate their estimates.We were confused as to how they could provide the cap rate estimates as evidence without showing which properties they were referring to nor any of the data used to calculate the estimate.They also provided a HUGE Equity Comparison table, containing the current year's unprotested valuations for half of New Braunfels, which they apparently used to get the value for "GBA Price per Sq Ft" for the "Income Calculation Worksheet".So their "Indicated Value" was based on an inflated "GBA Price per Sq Ft" value and zeroed-out "Vacancy", "Management", and "Collection Loss" values.During the protest hearing the appraiser went through some of the data, but he constantly found and (supposedly) fixed many mistakes on-the-fly during the hearing.