Furnishing and fit out
furnished homes
shell rentals
upholstered rentals

Furnishing Share by Location: A Practical Guide to Reporting Period, Measurement Unit, and Listing Coverage

Use this Netherlands-wide view to compare furnishing share across Dutch locations. Furnishing Share by location is most informative when method, geography, and comparison are read together. Furnishing share shows how rental supply is split between shell, upholstered, and furnished homes. That mix affects move-in costs, flexibility, and the tenant profile a market tends to attract.

City views
77
Listings in the sample
138,000+
Unit
Share in percent
Longest period
12 months

How furnishing mix shapes rental market choice

Furnishing share shows how rental supply is split between shell, upholstered, and furnished homes. That mix affects move-in costs, flexibility, and the tenant profile a market tends to attract. Read it as a signal of housing use and leasing style, not as a measure of quality or value.

furnished homesshell rentalsupholstered rentalstenant mixmove-in readinesslease flexibility
City views

Furnishing Share by Location in every covered Dutch city

Open a city to read Furnishing Share by Location for that local rental market, with the sample size behind each view shown next to the city name. Cities appear here once Luntero represents enough listings to describe them responsibly.

Amsterdam25,000 listings analysedRotterdam12,000 listings analysedThe Hague10,000 listings analysedGroningen7,500 listings analysedUtrecht7,500 listings analysedEindhoven5,500 listings analysedMaastricht4,500 listings analysedEnschede4,500 listings analysedTilburg3,500 listings analysedDelft3,000 listings analysedBreda2,500 listings analysedLeiden2,500 listings analysedLeeuwarden2,000 listings analysedHaarlem2,000 listings analysedArnhem2,000 listings analysedNijmegen2,000 listings analysedAmstelveen1,500 listings analysedAlmere1,500 listings analysed's-Hertogenbosch1,500 listings analysedZwolle1,500 listings analysedHeerlen1,000 listings analysedWageningen1,000 listings analysedHaarlemmermeer1,000 listings analysedApeldoorn1,000 listings analysedAlkmaar1,000 listings analysedHilversum950 listings analysedDeventer950 listings analysedSittard-Geleen950 listings analysedAmersfoort900 listings analysedPurmerend800 listings analysedAssen750 listings analysedDiemen700 listings analysedZoetermeer700 listings analysedLeidschendam-Voorburg700 listings analysedRoermond650 listings analysedLelystad650 listings analysedZaanstad650 listings analysedRoosendaal650 listings analysedHengelo550 listings analysedSchiedam550 listings analysedNieuwegein550 listings analysedRijswijk500 listings analysedHelmond500 listings analysedVenlo500 listings analysedHoorn500 listings analysedEmmen500 listings analysedZeist450 listings analysedEde400 listings analysedKerkrade400 listings analysedDordrecht400 listings analysedMiddelburg400 listings analysedBergen op Zoom400 listings analysedOss400 listings analysedAlphen aan den Rijn400 listings analysedCapelle aan den IJssel350 listings analysedDen Helder350 listings analysedHeerenveen350 listings analysedVeldhoven350 listings analysedSmallingerland350 listings analysedWassenaar300 listings analysedWeert300 listings analysedVlissingen300 listings analysedHeerhugowaard300 listings analysedGoes300 listings analysedKampen300 listings analysedGooise Meren300 listings analysedNoordwijk250 listings analysedDoetinchem250 listings analysedOosterhout250 listings analysedLandgraaf250 listings analysedGouda250 listings analysedZutphen250 listings analysedAlmelo250 listings analysedEtten-Leur200 listings analysedTerneuzen200 listings analysedMeppel200 listings analysedBrunssum200 listings analysed
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Furnishing Share by Location: A Practical Check on Data Recency, Reporting Period, and Measurement Unit

The value in Furnishing Share by Location becomes meaningful only when the measure, geography, period, and available observations remain aligned. Move from the displayed result on Furnishing Share by location to geography, comparison, and time window before interpreting the pattern.

What the data shows

  1. 1

    A higher furnished share often points to demand for convenience, shorter stays, or tenant groups that value immediate occupancy.

  2. 2

    A larger shell share usually fits households planning longer tenancies and bringing their own furniture.

  3. 3

    Upholstered supply can sit between the two, offering a compromise on cost, effort, and flexibility.

  4. 4

    The mix helps compare markets that may look similar on price but differ in how ready homes are for occupation.

  5. 5

    Furnishing structure can influence turnover, tenant expectations, and the kind of lease terms that are practical.

What to look at next

  • Use furnishing mix to distinguish convenience-led markets from longer-term household markets.

  • Compare shell, upholstered, and furnished supply as a proxy for tenant expectations and setup costs.

  • Explain how furnishing structure can affect mobility, turnover, and lease style without relying on price alone.

  • Frame the topic as a market composition signal rather than a simple amenity preference.

  • Show why two locations with similar demand can still serve different renter needs because of furnishing norms.

Related metrics

Metrics that answer the neighbouring question

Measures from the same market family come first, followed by other indicators that are useful next to this one when you are building a fuller picture of a Dutch rental market.

See All Metrics
Euro per monthfurnished rentunfurnished rent

Read Rent by Furnishing by Location as a bounded market observation whose usefulness depends on consistent definitions and coverage. Rent by Furnishing by location addresses a defined market question; geography, comparison, and source set the limits of the answer.

Rent by Furnishing by Location
Euro per m²furnishing premiumrent per m²

Furnishing Rent per m² by Location isolates one local rental-market measure so its level, direction, and limitations can be examined clearly. Treat Furnishing Rent per m² by location as market evidence only where geography, comparison, and source remain compatible.

Furnishing Rent per m² by
Euro per monthRental pricingMarket direction

The value in Average Rent by Location becomes meaningful only when the measure, geography, period, and available observations remain aligned. Average Rent by location is most informative when geography, comparison, and time window are read together.

Average Rent by Location
Euro per monthasking rentpricing benchmark

Open Median Rent by Location when you need one local indicator and the context required to compare it responsibly. Ground any comparison from Median Rent by location in the same geography, comparison, and time window used by its source.

Median Rent by Location
Euro per m²rent efficiencysize-normalized rent

Price per m² by Location provides a focused view of a local rental signal with its measurement choices kept visible. Before drawing a conclusion from Price per m² by location, verify geography, comparison, and source in the documented method.

Price per m² by Location
DaysMarket speedRental liquidity

Time on Market by Location turns a local dataset into one interpretable measure without presenting it as a forecast or recommendation. Interpret Time on Market by location with geography, comparison, and source attached to the reported value.

Time on Market by Location

Next from Furnishing Share by Location: Source Methodology, Market Segment, and Data Recency

Read Furnishing Share by location as a signal shaped by time window, source, and segment, rather than a complete market verdict. Select a Dutch location to review furnishing share in local context, including its direction, definition, and methodological limits.

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