About TripTimi
A travel timing guide built on climate data, crowd patterns, and price signals — designed to answer one practical question: when is the right month to visit?
Who built this
TripTimi was created by Paweł Celeński, a developer and traveller based in Poland. The project started as a personal tool for comparing travel windows across European cities and grew into a full guide covering 71 cities and 852 city-month combinations.
The goal is to give travellers comparable, data-grounded answers instead of generic "best time to visit" articles that ignore crowd levels, price seasonality, and the actual shape of a month's weather.
Questions or feedback: contact@triptimi.com
How the TripTimi Score works
Each city-month page shows a TripTimi Score from 0 to 100. The score is a weighted composite of five factors derived from historical climate data and seasonal demand signals:
| Factor | Weight | What it measures |
|---|---|---|
| Temperature comfort | 30% | Optimal day and night temps for walking-heavy city trips (peaks around 22°C day / 14°C night) |
| Precipitation | 30% | Both rainy-day frequency and total rainfall mm — how often rain interrupts plans |
| Sunshine hours | 20% | Daily average sunshine hours — affects mood, photography, and outdoor time |
| Crowd level | 10% | Seasonal demand model based on tourism patterns and city population |
| Price level | 10% | Relative accommodation and travel cost vs. the city's own annual average |
Score tiers: 80+ Excellent · 68–79 Very Good · 55–67 Solid · 45–54 Mixed · <45 Only if the timing fits
Data sources
- Climate data — Open-Meteo historical climate averages (temperature, rainfall, sunshine hours, humidity) — 10+ year monthly averages per city.
- Crowd signals — Seasonal demand model built from population data, European tourism seasonality patterns, and city-scale multipliers.
- Price signals — Relative seasonal index — not absolute prices, but whether a given month is above or below a city's annual average.
- Points of interest — OpenStreetMap — popularity scores derived from edit frequency and map usage data.
- Editorial descriptions — AI-assisted copy generated with OpenAI models, reviewed against factual constraints from the data layer. Every description must reference specific attractions and real climate numbers from the facts.
Editorial standards
Destination descriptions on TripTimi are generated with the help of AI language models using structured prompts that enforce specificity: every summary, tip, and recommendation must reference named attractions and real data points from the climate and crowd datasets. Generic phrases and template filler are flagged automatically and trigger regeneration.
The TripTimi Score is an indicative index, not a travel recommendation. It reflects typical seasonal conditions based on historical averages — actual weather, prices, and crowd levels in any given year will vary. Always check current conditions before booking.