How people use Rail Radar: Traffic patterns from the first three months

The report covers data from 2026-01-26 to 2026-04-28. In that window, Rail Radar served 22,459 station visits from 2,561 unique visitors.

Departures were the dominant use case. Users opened 16,537 departure boards compared with 5,922 arrival boards, which fits the product's most natural job: checking what leaves next from a station nearby or on a planned route.

The country totals are not an even race. Italy had the longest runway and was already available before this report window, which naturally gives it more time to collect station visits. Several other countries were added during March, so their totals reflect both demand and a shorter measurement period.

Switzerland went live on February 16. Finland, Belgium, and the Netherlands followed on March 9; the United Kingdom and Ireland followed on March 22. Germany arrived on April 3, and Denmark on April 17. That timing is especially important when comparing countries near the middle or bottom of the table: a later launch can look like lower demand even when early usage is healthy.

Reading the timeline against the country table, the most interesting comparisons are the markets that punch above their runway. Belgium had only seven weeks of measurement and still landed fourth by visits; Ireland accumulated meaningful traffic in five weeks. Those are the early signs to watch as later cohorts mature.

Italy is the strongest country in this snapshot, with 5,531 visits. Switzerland follows with 2,121, while the United Kingdom, Belgium, Germany, the Netherlands, Ireland, Sweden, Norway, Finland, and Denmark all appear in the long tail. That lead is meaningful, but it is also helped by Italy being available earlier than several countries added in March.

Belgium and the Netherlands are useful examples of why the release timeline matters: both were added on March 9 and still appear in the upper half of the country table. Germany and Denmark had much shorter windows, so their totals should be treated as early signals rather than mature country comparisons.

Coverage, the share of a country's stations that received at least one visit, is the quietest column in the table, but probably the most revealing. Italy and Ireland both sit near 18-19%, meaning users are exploring well beyond the headline hubs. The United Kingdom and Germany sit near the bottom of that column despite healthy raw visits, which suggests demand there is still concentrated on a small set of well-known stations rather than spreading across the network.

Milano Centrale is the clear leader, with 845 visits and 254 unique visitors. The rest of the top group mixes major Italian termini, international hubs like Bruxelles-Midi and Zürich HB, and a few more local spikes that are worth watching in future reports.

The top ten stations account for 15.6% of all station traffic. That is concentrated enough to show obvious hubs, but not so concentrated that the map is only being used for the largest cities. To make that picture sharper, it helps to look at the leaderboard from two angles: which stations get the most views, and which stations reach the widest audience.

The two lists overlap, but not entirely, and the differences are the interesting part. Brindisi makes the most-visited list with only nineteen unique visitors, the signature of a small group checking the same board repeatedly. Zürich HB and Firenze Santa Maria Novella, on the other hand, surface in the unique-visitor leaderboard because they pull in many different people rather than the same ones returning. The first pattern looks like a daily-commuter habit; the second looks more like trip planning and tourism. Both are valid uses of live train data, and both will shape how the product evolves.

Provider health is important because every station view depends on an external rail data source. In this window, most providers returned successful responses almost every time, with several at 100.0% success in the sampled data.

RFI handled the largest request volume and also shows the widest latency spread: a p50 of 888 ms and a p95 of 8,837 ms. That makes it the main operational area to keep an eye on as Italian traffic grows.

Latency is what users actually feel. A station view that waits two seconds for live departures feels different from one that returns in under three hundred milliseconds, and the spread between the fastest and slowest providers in this table is exactly that gap. The Italian source carries the most weight, both because it serves the most traffic and because its tail latency is the one most likely to leak into the user experience.

Three months is enough to see shape, not enough to draw conclusions. The audience is real, the international tail is encouraging, and the providers are mostly behaving. What the next report should clarify is whether the late-launch markets converge toward the leaders once they have had a full quarter to accumulate, and whether the long tail of station coverage keeps widening or settles around the same familiar hubs.

Until then, treat the numbers above as a baseline rather than a verdict, a first picture of who shows up to a live train map, what they look at, and how the underlying data sources hold up when real people start asking questions of them.