AirDNA vs STRProfitMap: Which One Actually Helps You Make Smarter STR Investments?
AirDNA vs STRProfitMap: Which One Actually Helps You Make Smarter STR Investments?
In the crowded short‑term rental (STR) data space, two names appear most often: AirDNA and STRProfitMap. Both promise to help hosts and investors vet markets and underwrite deals, but they take very different approaches. This comparison walks through an operator’s workflo (from market idea to deal check) and contrasts where each tool shines and where it falls short.
The Core Workflow of STR Investment
Successful STR investment follows a predictable set of steps: you identify a promising market, gather comparable listings, underwrite the numbers and stress‑test your assumptions. Each step depends on reliable data. Experienced investors know that occupancy and average daily rates fluctuate with seasonality, regulations and guest preferences. A tool that glosses over those nuances can make a deal look much better than reality.
What AirDNA Offers
AirDNA built a reputation by aggregating millions of Airbnb and Vrbo listings. The platform provides market‑wide stats, a revenue calculator and investability scores. It touts global coverage and gives users access to five years of historical data and six months of forward‑looking projections. Those features make it useful for broad trend spotting or comparing entire cities. However, AirDNA relies on scraped data and includes thousands of “raw” listings that may no longer be active. On their own demo page, STRProfitMap notes that AirDNA returned more than a thousand listings for Oakhurst, California, while only about 600 were actually reliable. In a maturing STR market where oversupply and saturated neighborhoods are a growing problem, that kind of noise can inflate revenue averages and obscure risks. AirDNA doesn’t let users export full datasets to Excel, either, which makes underwriting tedious.
How STRProfitMap Is Different
STRProfitMap was designed for investors who need clean, apples‑to‑apples comps. The platform intentionally filters out fluff and only retains reliable listings, defined as entire‑home properties with at least nine months of rental history and verified guest stays. Its interactive profit map color‑codes ROI from dark green (high return) to red (low return) and allows you to filter by bedroom count, property type, price range and performance metrics. Additional data layers overlay the map with saturation indexes and local STR regulations so you can avoid overbuilt ZIP codes or towns with permit caps. STRProfitMap’s AI Buy Box goes further: it processes guest reviews to identify value‑driving amenities and generates a revenue potential score for specific property configurations. The combination of curated comps and amenity insights helps you avoid chasing inflated averages.
Cincinnati Studio Teardown
Consider an investor evaluating a small studio in Cincinnati. AirDNA’s dashboard showed a lofty average revenue across hundreds of listings. But a closer look with STRProfitMap’s ZIP export revealed that most high‑earning listings were large houses with hot tubs and game rooms. Filtering to studio apartments and plugging the data into an Excel model exposed a lower revenue ceiling and inconsistent occupancy. Armed with reliable comps, the investor decided not to pursue the deal, saving roughly $250,000 in capex and lease commitments. This case demonstrates that sometimes the smartest investment decision is to walk away.
When to Use Each Tool
AirDNA excels at macro‑level market research. If you’re deciding whether to enter Denver or Dallas, its broad data and investability scores can provide context. But when you need to vet a specific ZIP code, confirm that comps actually match your property and test sensitivity in Excel, STRProfitMap’s curated dataset and export functionality give you the precision you need. The platform’s regulation layer is also indispensable in a regulatory environment where cities like New York and San Francisco require host registration and impose occupancy restrictions.
Verdict
Choosing the right data tool can mean the difference between a profitable purchase and a costly mistake. AirDNA remains helpful for high‑level trend spotting, but for decision‑stage underwriting, STRProfitMap’s emphasis on reliability, micro‑market filtering and AI insights makes it a more effective companion. If you’re ready to test it yourself, request a free ZIP export and see how your numbers change when you remove the noise.
