Rental market metrics
Median and average asking rent, price per square meter, time on market, supply volume and the rest of the indicator library.
Browse metricsRent per square metre by furnishing compares median size-adjusted asking prices across represented Hoorn shell, upholstered and furnished rentals. Normalizing by floor area makes the groups more comparable than monthly totals and can reveal whether a furnishing-related price difference remains after size is considered. It does not isolate the cost of furniture: unit type, location, quality, size distribution and uneven samples within each furnishing category can still shape the medians.
Compare furnished and unfurnished segments by their median price per square meter to see whether convenience adds a clear premium in Hoorn. A wider gap suggests furnishing carries extra value beyond size, while a smaller gap points to pricing that is driven more by layout, location, or stock mix. Avoid reading a single segment in isolation.
Figures come from the rental listings Luntero represents for the selected period. Sample sizes differ per location and month, so read short movements together with the underlying listing counts rather than as exact market wide changes.
Furnishing can change the effective rent per square meter, not just the monthly total. In Hoorn, that makes it useful for separating a true furnishing premium from the effect of compact homes that naturally cost more per meter. The median helps show the typical pattern without letting a few unusual listings dominate the reading.
See whether represented Hoorn furnishing groups differ after rent is normalized for space. The medians improve direct comparison, but unit mix, quality and sample size still matter.
A higher furnished median can indicate a convenience premium beyond the effect of smaller unit sizes.
A narrow gap suggests furnishing matters less than stock mix, location, or dwelling type.
Median pricing reduces the influence of outliers, but it does not remove composition effects.
Hoorn comparisons are most useful when furnished and unfurnished homes are read side by side.
The metric helps separate size-driven pricing from the added value of move-in readiness.
Separate size effects from furnishing effects in Hoorn's rental market.
Use the median to understand the typical furnishing premium, not just extremes.
Compare furnished and unfurnished homes as different value propositions.
Read the gap as a convenience signal layered onto underlying space value.
Watch how stock mix can make compact furnished homes look expensive per m2.
This page documents one indicator. The Hoorn overview brings the median advertised rent, cost per square metre, three trend windows, listing supply and the bedroom, property-type and furnishing mix together in a single reading.
Stay in Hoorn and switch the question. The same represented listing sample powers every metric and report below, so you can move from asking rent to price per square meter, supply, space and neighbourhood detail without losing the local context.
Compare Furnishing Rent per m² by Location across supported Dutch locations using the represented listing sample. Differences reflect the covered sources, period and methodology and should not be treated as complete local-market or demand measurements.
Review the group medians and their composition, then compare monthly rents, furnishing shares or the national size-adjusted pattern.
Median and average asking rent, price per square meter, time on market, supply volume and the rest of the indicator library.
Browse metricsMulti measure analyses of pricing, supply, composition, space, affordability and market speed across the Netherlands and its cities.
Browse reportsSee the apartments, rooms and houses currently advertised in Hoorn and filter them by price, size and property type.
Search Hoorn rentalsHave an idea for a new housing market chart, dataset, or analysis? Submit your request and help shape the next generation of Luntero’s rental market insights. Whether it’s a new metric, city comparison, or visualization, your input helps us expand coverage of Dutch housing trends and create data tools that serve renters, investors, and researchers across the Netherlands.
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