About Our Data: Sources, Methods & Accuracy

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Where Our Data Comes From

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StaySTRA pulls from multiple independent data sources to build a comprehensive picture of each market. Our primary sources include:

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Public listing data: We aggregate publicly available information from major short-term rental platforms, including Airbnb and VRBO. This includes listing details, pricing history, availability calendars, guest reviews, and property attributes. By collecting data across platforms, we can identify properties listed on multiple sites and build a more complete view of each market’s supply.

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County tax records: Property tax assessments, ownership records, and parcel data help us understand the underlying real estate fundamentals in each market. This lets us connect rental performance to property values and estimate realistic investment returns.

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Census and demographic data: Population trends, household income, employment figures, and tourism statistics from federal and state sources give us the broader economic context that drives short-term rental demand.

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Regulatory databases: We track local ordinances, permit requirements, HOA restrictions, and zoning rules that affect short-term rental operations. This information comes from municipal records, public meeting minutes, and published regulatory frameworks.

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How We Process It

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Raw data is messy. The same property can appear with different names, addresses, and details across platforms. Our processing pipeline handles this through several steps:

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Data cleaning: We standardize addresses, correct formatting inconsistencies, and validate data types. Listings with incomplete or clearly erroneous information are flagged for review rather than silently included.

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Deduplication: Our matching algorithms identify the same property listed across multiple platforms. We use a combination of geographic coordinates, property attributes, photos, and text similarity to merge duplicate records into a single unified listing.

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Normalization: Different platforms report metrics differently. We normalize pricing to a consistent nightly rate, standardize property type classifications, and convert all measurements to common units so comparisons across markets are meaningful.

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Outlier detection: Statistical models flag data points that fall outside expected ranges. A listing showing $10,000 per night in a market where the median is $150 gets flagged and investigated. This prevents bad data from skewing market averages and projections.

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Revenue Projections

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Our revenue estimates are the numbers investors care about most, so we take extra care to make them reliable. Here is how the key metrics are calculated:

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Average Daily Rate (ADR): We calculate ADR using actual booked rates from comparable properties in the same market, adjusted for property size, amenities, and quality tier. Seasonal pricing patterns are factored in so the annual ADR reflects real-world pricing swings rather than a single snapshot.

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Occupancy rate: We estimate occupancy by analyzing booking calendars of comparable properties over trailing 12-month periods. We account for seasonal demand patterns, local events, and day-of-week trends. New listings typically see lower occupancy in their first 90 days, and our projections reflect this ramp-up period.

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Gross revenue: Projected annual revenue combines ADR and occupancy rate estimates, then applies platform fee adjustments. We present revenue in ranges (conservative, moderate, and optimistic scenarios) rather than a single number, because honest analysis requires acknowledging uncertainty.

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Comparable property selection: The quality of any projection depends on choosing the right comparables. Our algorithm selects comps based on proximity, bedroom count, property type, amenity overlap, guest rating, and listing maturity. We weight recent performance more heavily than older data to capture current market conditions.

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Market Metrics

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Beyond individual property projections, StaySTRA provides market-level intelligence that lets investors compare opportunities across geographies:

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Supply metrics: Total active listings, new listings added, listings removed, supply growth rate, and saturation indicators. These help investors understand whether a market is growing, stable, or becoming overcrowded.

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Demand indicators: Average occupancy trends, booking lead times, seasonal demand curves, and review velocity. Rising demand with stable supply signals opportunity. Falling demand with growing supply signals risk.

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Regulation risk: We score each market’s regulatory environment based on current rules, recent policy changes, pending legislation, and enforcement activity. Markets with stable, STR-friendly regulations score lower risk. Markets with active restriction efforts or recent crackdowns score higher.

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Investment fundamentals: Median home prices, price-to-rent ratios, property tax rates, and insurance cost estimates round out the picture. These numbers come from county records and are updated as new assessments become available.

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Update Frequency

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Stale data leads to bad decisions. We maintain different refresh cycles based on how quickly each data type changes:

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• Listing data (pricing, availability, reviews): Refreshed regularly to capture booking activity and rate changes.

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• Market statistics (supply counts, occupancy trends, ADR averages): Updated monthly with trailing calculations.

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• Regulatory data (ordinances, permit rules, zoning): Reviewed quarterly, with ad-hoc updates when significant policy changes are announced.

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• Property tax and census data: Updated annually when new assessments and surveys are published.

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Limitations and Transparency

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We believe honest analysis means being upfront about what our data cannot do:

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Projections are not guarantees. Our revenue estimates are based on historical patterns and comparable performance. Actual results depend on factors we cannot model, including property management quality, guest experience, marketing effort, and unforeseen events.

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Platform data has blind spots. Not all bookings are visible through public calendars. Direct bookings, last-minute reservations, and blocked dates for owner use can affect the accuracy of occupancy estimates.

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Geographic coverage varies. Our 2,600+ markets cover the vast majority of active US short-term rental areas, but smaller or emerging markets may have limited data. We indicate confidence levels for each market so investors can weigh the data accordingly.

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Regulatory landscapes change. Local governments can enact new restrictions with little notice. While we monitor regulatory developments closely, our quarterly review cycle means there can be a lag between a policy change and its reflection in our data.

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Past performance is not predictive. Markets that performed well historically can decline due to new competition, regulatory changes, or economic shifts. We encourage investors to use our data as one input among many when making investment decisions.

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