How it works

Methodology

WhenVerdict is a travel timing engine — not a travel blog and not an AI chat assistant. Every result is generated from a structured scoring model applied to real data, weighted by your declared priorities.

Data sources

Weather scores

Weather data comes from the Open Meteo Archive API using ERA5 reanalysis data — a globally consistent climate dataset that combines satellite observations and atmospheric models. We use 30-year normals (1991–2020) to generate monthly averages for temperature (high and low), total precipitation, daily sunshine hours, and humidity. These are real, validated climate figures — not editorial estimates.

Weather scores are then derived from this data using destination-specific thresholds. A 20°C day in Amsterdam is scored differently than a 20°C day in Bali, because local context determines whether that temperature feels ideal or disappointing.

Price scores

Price scores reflect seasonal pricing patterns based on published tourism authority data, hotel rate index research, and curated seasonal analysis per destination. They represent the relative cost of visiting within a destination across the year — not absolute price comparisons between destinations. A score of 9 means “among the cheapest months for this destination,” not “cheap compared to everywhere.”

Crowd scores

Crowd scores are based on destination-specific seasonal tourism patterns, sourced from tourism board seasonal reports and cross-referenced with publicly available data on visitor arrivals. These are directional indicators — a crowd score of 2 means “this is among the most crowded months for this destination,” not a precise footfall claim.

Event and atmosphere scores

Event scores reflect the density and quality of local festivals, cultural events, and seasonal programming. Atmosphere scores reflect how authentically “local” the destination feels — how many residents are present, how active the local market and dining scene is. These are editorial judgements, curated and reviewed per destination.

How scoring works

Each month receives five core scores (1–10): weather, price, crowd, events, and atmosphere. These are combined into a single composite score using weighted averages — where the weights depend on your declared priorities.

Your priorityWhat gets weighted most
Better weatherWeather score (45%), then crowd score (20%)
Lower pricesPrice score (45%), then crowd score (20%)
Fewer crowdsCrowd score (45%), then weather score (20%)
Local atmosphereAtmosphere score (40%), events score (20%)
Events & cultureEvents score (45%), atmosphere score (15%)
Beach weatherWeather score (50%), then crowd score (20%)

When you select multiple priorities, the weights are merged proportionally. This means the output genuinely changes based on what you tell us — User A (budget + crowds) and User B (weather + beach) will get different recommended months for the same destination.

Trade-offs are mandatory

No month receives a purely positive writeup. Every month in WhenVerdict includes at least two gains and two honest trade-offs. This is a design principle, not an accident. We believe presenting trade-offs is more useful than presenting a ranked list of superlatives — because every traveller’s acceptable trade-offs are different.

What we don’t claim

Updates

Climate data is stable by definition (30-year normals change slowly). Price and crowd scores are reviewed when destination patterns change significantly due to tourism shifts, infrastructure changes, or major events. Event scores are updated annually.