About
Beth
Founder, When Should I Travel · Canadian in the UK
I'm a Canadian living in the UK, which means I've spent years navigating the peculiar British obsession with booking holidays during the six-week school summer window — paying peak prices to visit places that are simultaneously at their most crowded and most expensive.
After one too many Augusts fighting for space on a Dubrovnik wall walk or paying €270/night for a room that costs €140 in September, I started tracking shoulder season windows properly. What began as a personal spreadsheet turned into this guide — now covering 110+ destinations worldwide.
The site reflects what I actually think, not what affiliate commissions suggest — there's no booking engine here, no paid placements, and no "sponsored" recommendations. Just honest timing data and the occasional strong opinion about when not to go somewhere.
About the site
A data-driven shoulder season travel guide covering 110+ cities in 63 countries — built to answer one question: when is the best time to visit, if you want fewer crowds, lower prices, and a place that feels like itself again?
Most travel content is experiential — "I visited in October and loved it." This site is built differently. Every shoulder season window is backed by hotel price data, climate records, crowd indicators, and published tourism arrival statistics. The goal is a recommendation you can trust even if we've never been to the same place at the same time.
Why shoulder season?
Most travel planning tools optimise for convenience — cheapest flights, warmest weather. Neither answers the real question: when should I go to get the best version of this destination?
The answer is almost always shoulder season. Not because it's cheapest — though it usually is. But because shoulder season is when Santorini's sunset is watchable rather than queue-able. When the Amalfi Coast road is driveable. When the restaurant you came for takes reservations. When the city, once the summer tourists have gone, becomes itself again.
This site makes that timing specific — not just "go in September" but exactly which months work for each destination, what temperatures to expect, what hotel prices look like, and how crowd levels compare to peak.
Data & methodology
Each destination guide is built from six data layers. Here's exactly what goes into each one:
Hotel price data
Mid-range averages (3–4 star) sourced from aggregated booking platform pricing. Shoulder season rates are compared against peak month pricing to calculate the savings percentage shown on each destination page. Prices are indicative — actual rates vary by specific dates, lead time, and property.
Flight pricing
The 37% cheaper figure is sourced from KAYAK's published shoulder season analysis across transatlantic and intra-European routes. Destination-specific flight data is sourced from Skyscanner historical fare data. Individual routes will vary significantly.
Temperature & weather
Average high/low temperatures and rainfall are based on 10-year historical climate data per destination. They represent typical conditions — weather is variable by nature and year-to-year anomalies occur. Sea temperatures are included for coastal and island destinations.
Crowd indicators
Crowd levels are assessed using a combination of Google Trends search volume patterns (which correlate strongly with tourist arrivals), published national tourism board arrival statistics, TripAdvisor seasonal popularity ratings, and cruise ship port call schedules where relevant. Each destination's crowd rating is calibrated relative to its own peak — not against a universal benchmark.
Shoulder season windows
Each destination's shoulder season window is defined individually — not by applying a blanket calendar. Mediterranean shoulder season (April–May, September–October) is different from East African safari shoulder (June, October–November), which differs from Japan's (May, October–November). Each window requires weather, price, and crowd conditions to align simultaneously.
Data updates
Destination data is reviewed annually. Hotel price data is most subject to change; climate data is stable. Where significant changes are detected — new direct flight routes, major new hotel supply, post-disaster recovery periods — guides are updated outside the annual cycle.
How we measure crowd levels
"Crowds" is the hardest thing to quantify in travel data — official statistics lag by months, and personal accounts vary wildly. We use four sources in combination to build a crowd profile for each destination and each month:
Google Trends
Monthly search volume for '[destination] holiday' and '[destination] travel' queries correlates closely with actual tourist arrivals — a reliable crowd proxy without requiring access to official tourism statistics.
Tourism board arrival data
Where national or regional tourism boards publish monthly arrival statistics, these are used to calibrate peak vs shoulder differentials. Spain's INE, Portugal's Turismo, Croatia's HTZ, and Thailand's TAT all publish reliable monthly data.
TripAdvisor seasonality ratings
TripAdvisor's 'busy season' indicators, derived from booking and review volume patterns, provide a useful cross-check against other crowd signals — particularly for cities where official arrival data is less granular.
Cruise ship schedules
For port cities (Dubrovnik, Kotor, Santorini, Barcelona, Venice), cruise ship arrival schedules have an outsized impact on single-day crowd levels. Ports with 3+ ships in port simultaneously can see a 30–50% surge in visitor numbers for that day.
What the crowd ratings mean in practice: A destination rated "Low crowds" in May doesn't mean empty streets — it means visitor volumes are meaningfully below the July–August peak for that specific destination. A "High" crowd rating in a normally quiet place may still represent fewer people than a "Medium" month in Barcelona. Ratings are calibrated to each destination's own scale.
What this site isn't
Not a booking platform. There are no flight or hotel sales here, no affiliate commissions, and no sponsored recommendations. The timing analysis is independent — there's no financial incentive to recommend one destination or window over another.
Not a traditional travel guide. The focus is specifically on when to visit rather than what to do when you get there — though the destination guides do cover key attractions through a shoulder season lens.
Not an AI-generated content farm. Every destination page is researched individually using the methodology above. Where data is uncertain or unavailable, we say so.
Coverage
Currently covering 110+ cities across 63 countries on every inhabited continent. The focus is on destinations with meaningful shoulder season dynamics — places where timing genuinely changes the experience and price.
If you have a destination suggestion, a data correction, or want to flag something that looks wrong, reach out at beth@whenshoulditravel.com. Data corrections are taken seriously and updated promptly.
Start exploring
Use the destination finder to search 110+ cities by month, budget, temperature, and trip type. Or read the shoulder season price report for the full data and methodology.