Manchester duplexes at 88 days: are active listings distorting the picture?

[sketchTheBench]

I’m looking at Manchester duplexes priced from £605,300 to £907,900. The active listings in my sample have taken roughly 88 days to find a buyer, with the longer cases appearing linked to financing costs. Before I draw conclusions, should I rely more heavily on recent completed sales, or does the time spent by stock still online tell us something useful?

 

[MaraSage]

The 88-day figure is useful, but active stock has survivor bias: attractive or correctly priced homes leave the pool, while difficult ones remain visible. Completed sales can balance that, although they describe an earlier market because completion comes later. I’d compare both rather than replace one with the other.

 

[bakesAndView]

The neighbourhood mix could be weakening the comparison. Duplexes between £605,300 and £907,900 may attract quite different buyers across Manchester, so an 88-day average is tempting but not necessarily representative.

I would split the sample by area first, then decide how to handle withdrawn and relisted properties. Are you measuring from the earliest known appearance, or starting again after a relisting or price change? That choice could alter the result substantially.

 

[readTheEcho]

I’d be cautious about attributing the outliers mainly to financing costs. Condition, an ambitious initial price and seller motivation can all produce a long listing period. Unless you know why individual buyers walked away, financing is an explanation rather than a finding.

 

[sketchTheBench]

Fair challenge. My sample crosses more than one neighbourhood, and I’ve been using the first visible listing date. I haven’t separated withdrawn and relisted stock consistently, which could be stretching the 88-day figure. I’ll split the areas and stop treating financing as the default explanation.

 

[CelineLinden]

Property condition deserves its own column. A duplex needing work can sit beside a finished one at a similar asking price, but buyers may assess the total commitment very differently—especially when financing is already expensive. Photos and descriptions are imperfect, yet even a simple condition grouping would improve the comparison.

 

[calm_chart]

I have checked the age of the visible listings, but it is still unclear how much fresh stock entered the sample during the same period. A quiet month for suitable duplexes would leave an older-looking pool even if demand had not changed.

Add the listing date for every property and count how many comparable homes appeared in each period. If plenty of new choices arrived while the older stock remained available, condition, price or seller expectations become more convincing explanations than the average alone.

 

[readTheEcho]

One practical approach: keep separate groups for completed, under-offer, active, withdrawn and relisted properties. Then record the first asking price, current asking price and when any reduction appeared. You may find that the important difference isn’t total days online but how long sellers waited before adjusting.

 

[readTheEcho]

I’d also resist averaging every completed deal together. A seller accepting quickly because they need certainty is not directly comparable with one prepared to wait for a particular price. We won’t always know motivation, but unusually short or long cases should be inspected rather than allowed to drive the headline.

 

[bakesAndView]

That framework works, but don’t let the categories become more precise than the underlying information. Withdrawals are especially ambiguous: some may be failed sales, some genuine changes of plan, and some later relistings. I’d show them separately and describe the uncertainty instead of folding them into days-to-buyer.

 

[DirectCairn]

So 88 days isn’t necessarily wrong; it is answering a narrow question about the selected listings. For a view of this month, I’d present the median age of active stock alongside recent completed deals, new-listing volume, withdrawals and price-cut timing, all within consistent neighbourhood boundaries. That would make the outliers visible without letting them define Manchester as a whole.