Utrecht duplexes: is condition explaining the price spread?

[measureTheFinch]

The case for bidding now is that suitable Utrecht duplexes may not become cheaper, but I hesitate because the listings I saved do not behave like one market. Prices range from €493,100 to €739,700, while the snapshot reports 1.7% movement and about 101 days on market. Negotiating room seems to vary considerably with the amount of work required.

I suspect condition is a stronger divider than general demand, but asking listings are not enough to establish that. I would like to compare completed sales, reductions and withdrawn properties within tight neighbourhood boundaries, then check whether buyer-financing problems account for some of the longer listings. New-listing volume would also help show whether waiting is likely to produce real alternatives.

Does the evidence support that approach? Please include the Utrecht neighbourhood and exact property type with any example.

 

[HonestHorizon]

Condition could explain a large part of it, but advertised listings alone cannot confirm that. A renovated duplex may sell quickly without a visible cut, while one needing work can sit for 101 days and still be overpriced after reduction. I’d compare completed sales with similar layout, condition and immediate location rather than treating the full €493,100–€739,700 range as one market.

 

[sasha.moss]

What exactly does the 1.7% measure—asking-price movement, completed-sale prices, and over what period? That distinction matters. I’d also separate genuine time on market from listings that were withdrawn and later returned. Otherwise the 101-day figure may mix motivated sellers with stock that is simply being tested at an ambitious price.

 

[radar.round]

I’m not convinced maintenance is necessarily the main driver. Buyer financing and seller motivation can produce the same pattern. A well-kept duplex may still linger if its asking price sits beyond what the likely buyer pool can finance, while a property needing work may move if the seller prices that burden honestly. Neighbourhood boundaries could also distort a citywide comparison.

 

[eli_west]

Build a small table for each saved listing: neighbourhood, floor area, asking-price history, first-listing date, current condition, obvious work required, withdrawal/relisting history and final status. Then record when the first price cut occurred. Compare only duplexes with broadly similar layouts. That should reveal whether condition is associated with longer marketing, larger cuts, or merely a lower starting price.

 

[green_glass]

Seller motivation is the missing item I’d try to establish before bidding. Has the property already been reduced, and did that happen early or only after most of the 101-day period? A late cut can indicate that the original expectation failed; an early cut may reflect a deliberate attempt to generate interest. Neither automatically tells you what discount will be accepted.

 

[green_glass]

Following Felix’s table idea, I’d add weekly new-listing volume and mark anything that disappears without a recorded sale. That prevents withdrawn stock from being mistaken for buyer demand. I’d also keep the 1.7% figure in a separate city-level column rather than applying it to every duplex. The practical bid case should come from the closest completed sales, adjusted cautiously for condition and necessary work.