Objective:
The aim is to provide an independent, evidence-driven hotel ranking in the Brazil region, using only statistically robust guest review data. Each property is assessed based on the regional lowest and highest values, accurately placing it among its peers. As this analysis requires a significant quantity of verified customer input, even the most exceptional but highly exclusive hotels with fewer guests may score lower—or not be included—simply because of insufficient review volume. This is intentional and highlights our focus on broad, measurable confirmation by real guests.

Ranking Index Scale (0 – 999):
The resulting Ranking Index assigns scores from 0 (the lowest performance in the region) up to 999 (best possible score). A higher number reflects a stronger overall result within this ranking framework.

Data Sources:
Booking.com, TripAdvisor, Google Reviews, Expedia, Hotels.com, Trip.com

Key Methodological Components:

• Multi-Platform Rating Aggregation: Brings together and normalizes ratings from every platform to minimize any single-source influence.
• Sample-Size Confidence: Bayesian adjustments favor hotels with 100+ confirmed reviews, reducing the effect of smaller sample sizes.
• Rating Stability Factor: Hotels with less fluctuation in guest ratings receive a bonus for maintaining consistent quality.
• Cross-Source Consistency: Consistent ratings across different platforms signal reliability and are rewarded accordingly.
• Regional Benchmarking: Each metric is recalibrated between the regional minimum and maximum before being weighted, making sure outstanding performance is recognized.

Weighting of Ranking Factors

This methodology combines robust regional benchmarks with property-level data, resulting in a clear 0-to-999 scale that rewards high guest satisfaction, large review numbers, and excellence over competitors—while clearly explaining why exclusive boutique hotels may not always qualify due to limited data.