Revenue Estimator Pro Methodology

Revenue Estimator Pro Methodology

PriceLabs' Revenue Estimator Pro: A Three-Step Methodology

The Revenue Estimator Pro (RE) by PriceLabs is a powerful tool designed to provide accurate and actionable revenue estimates for short-term rental (STR) properties. This article outlines the three key steps involved in arriving at these estimates: Data Collection, Data Cleaning, and Calculating Metrics. Each step is crucial in ensuring that the estimates are reliable and reflective of real market conditions.

1. Data Collection

The first step in the RE methodology is data collection, which is foundational to the entire estimation process. To ensure a robust and representative sample, the tool starts by gathering data within a 15-kilometer radius of the target property, aiming to include at least 120 listings. If this threshold isn’t met, the search radius is expanded to 35 kilometers. This approach ensures that the data pool is both broad and relevant, capturing a wide range of properties in the area.

For larger properties, such as those with five or more bedrooms, the search criteria are further refined by including listings with a bedroom count of +/- 1 (only if less than 120 listings are of the given bedroom category are present). This adjustment helps in gathering more comparable data, which is essential for accurate estimates.

The data is collected for the last 365 days (1 year), ensuring that the estimates reflect the most recent market trends. To maintain quality, the number of active listings considered is capped at 350, and the number of inactive listings used is proportional to the active listings.

2. Data Cleaning

Once the data is collected, the next step is data cleaning. This step is crucial for removing inaccuracies and ensuring that the data used in the estimates is reliable. The process begins with analyzing daily property-level data. Any listings with extreme revenue figures, which are often due to scraping errors, owner blocks or other anomalies, are removed from the dataset.

After this initial cleaning, the data is aggregated to the property-monthly level. At this stage, an additional filter is applied: only property-monthly pairs where the listing was active for at least 75% of the month and blocked for no more than 50% of the month are retained. This filter ensures that the data reflects properties that were genuinely available and active in the market, rather than those that were listed sporadically or had significant downtime.

3. Calculating Metrics (Revenue, ADR, Occupancy)

The final step in the RE methodology involves calculating the key metrics that users rely on: revenue, average daily rate (ADR), and occupancy. After the data has been cleaned and aggregated, it is grouped by month to derive the monthly metrics. These metrics are what users see on the RE tool's line charts, providing a clear view of how properties have performed over time.

The monthly metrics are then aggregated to derive annual metrics (mean or sum of monthly metrics), offering a broader perspective on the potential revenue for the year. This step is particularly important for users planning their STR investments, as it provides a comprehensive view of expected performance based on past data.

Conclusion

The Revenue Estimator Pro by PriceLabs employs a detailed and methodical approach to provide accurate revenue estimates for STR properties. By following the three key steps of Data Collection, Data Cleaning, and Calculating Metrics, the tool ensures that users receive reliable estimates that reflect real market conditions. However, it's important to remember that while these estimates are valuable, they should be considered as part of a broader strategy when evaluating STR properties.


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