A transparent process for evaluating lodging projects.

We start by understanding the project — site, unit count, bedroom mix, guest capacity, finish level, planned amenities, ownership goals, and any financial assumptions already prepared.

We define the relevant market: drive-time radius, lake or resort sub-markets, event catchment, and demand drivers. This determines whose data is actually comparable to your project.

We combine STR market data (AirDNA-style, PriceLabs), platform listings (Airbnb, Vrbo), DMO and event calendars, public records, and our own operator data sets. No single source tells the full story.

We build a comp universe by hand — review counts, photo quality, amenities, bedroom counts, guest capacity, lake access, and finish level. Then we segment true comps from broad-market noise.

We map booking pace, weekday vs weekend behavior, event-driven peaks, and shoulder season risk so revenue assumptions reflect the real annual shape — not a flat average.

We build ADR by season and stay length, calibrated to comparable comp behavior and pricing tools. Occupancy is grounded in true comps, not market-wide averages.

We evaluate which amenities, layouts, and bedroom counts actually move ADR and occupancy in your market — and which ones add operating cost without improving revenue.

Conservative, realistic, and upside annual gross revenue ranges, with the assumptions behind each scenario documented in plain language.

We surface the risks: regulatory, supply growth, channel concentration, seasonality, operational complexity, and assumption sensitivity.

A clear go / no-go / adjust recommendation with the reasoning, key risks, and recommended next steps for design, financing, or further analysis.