About.
Wandering Well wants to improve travel by steering people away from overcrowded, overtouristed destinations, toward places that might welcome more visitors. We're talking about beautiful alternative locations. This would deliver a win-win-win: for the traveller, for the crowded destinations that get some relief, and for beautiful places that gain economic activity.
Most modern algorithms reward popularity: clicks beget more clicks. Popular places grow more popular. This has fuelled an overtourism crisis that has made both communities and travellers miserable. This site attempts to do the opposite: penalize popularity, and spread tourism around more equitably.
This is also an early experiment in agentic travel planning. By connecting our pages to online research tools and MCP servers, personal agents can help people research and book travel. The agent surface knows about each destination's nearest commercial airports and train stations with real Mapbox-routed driving times, plus a 30-year monthly climate normal from ECMWF's ERA5-Land — see MCP For Agents for the setup.
The score, briefly
The Wander Well Score (WWS) combines two halves at 50/50:
- Beauty — proximity to water and mountains, density of protected and heritage architecture, concentration of museums, restaurants, cafés and places of worship within walking distance, a learned aesthetic score on the destination's primary photograph, and how often photographers from many countries actually shoot the place (rather than how many photos a small handful take).
- Economic need — local income relative to the country's average and the regional unemployment gap, on the theory that traveller money is more useful in places that are beautiful AND comparatively under-resourced.
A tourism-intensity penalty is subtracted on top — Wikipedia pageview share, hotel density, and how disproportionately the place is talked about in English versus its own language. The full methodology with sources and edge cases lives at /methodology; this page is the plain-English version.
Where the data comes from
World Bank · UNESCO · Geoapify · OpenStreetMap · Eurostat (including hotel-occupancy statistics) · OECD · US Census ACS · ONS · StatCan · GDL · ILOSTAT · IBGE · Wikipedia · Flickr. Photo attributions on each destination page.
What this site is, and is not
- It is a research output and a writer's craft project.
- It is built to be readable by AI agents — see /llms.txt.
- It is not a booking tool, a travel agency, or affiliated with any tourism board.
- It is not a definitive ranking. The score is a perspective, not a verdict.