Birmingham retail units: is my 50-day figure distorted by stale listings?

R

radar.wise

Property investor
I’m comparing retail units in two Birmingham neighbourhoods before deciding whether to pursue one. In the £630,200–£945,400 range, my sample suggests roughly 50 days to find a buyer.

Most outliers appear connected to building reserves, but I’m mainly looking at listings still online. Should recent completed sales carry more weight, and how would you account for withdrawn units, relistings and neighbourhood boundaries? The citywide average seems too broad to help.
 
The online sample is almost certainly tilted towards slower stock: the units that moved quickly disappear while stubborn listings remain visible. I’d compare completed, withdrawn and still-marketed properties from the same listing period. Otherwise 50 days describes today’s survivors, not necessarily the typical unit.
 
What event ends your 50-day count: an agreed sale, removal from the portal or completion? Also, are you using fixed neighbourhood boundaries? Portal labels can put nearby units into different areas, which matters when the sample is already narrow.
 
Completed deals help, but they are backward-looking and may reflect an earlier financing environment. A unit can attract a buyer promptly yet take much longer to complete because of funding or property-specific issues. I wouldn’t combine marketing time and completion time into one figure.
 
Anna’s question is crucial. I’d make one row per unit with first-listing date, any price cut, agreed-sale date if known, withdrawal date and completion date. Keep blank fields blank rather than treating an unknown outcome as 50-plus days.
 
Also watch for relistings. A unit can look new after an agent or description change even though the seller has been trying for much longer. Conversely, counting from the original date may hide the effect of a meaningful price reduction.
 
How are you identifying the building-reserve issue? Is it stated consistently, or inferred from the few slow listings? Condition could be doing some of the work too. Two similarly priced retail units may require very different levels of spending before occupation.
 
That’s why I’d separate the reserve-linked units rather than simply removing them. Compare their marketing times with units of similar condition. If reserves and poor condition overlap, the current sample cannot tell you which factor buyers are reacting to.
 
I’m not convinced reserves explain the outliers at all. Seller motivation is usually invisible in listing data. A seller holding firm can create a long marketing period, while another may cut early or withdraw, even where the properties look comparable.
 
Try a cohort approach: take units first listed during the same period and follow each to sale, withdrawal or continued marketing. Then repeat for each neighbourhood. That avoids mixing fresh listings with stock that has already spent months on the market.
 
I wouldn’t discard the citywide number completely. It can serve as a rough comparison: if both chosen areas behave similarly to each other but differently from Birmingham overall, that is useful. It just shouldn’t replace the neighbourhood-level work.
 
Buyer financing deserves its own note where the information is available. A slow completion does not necessarily show weak demand, and a withdrawal does not necessarily mean no buyer existed. Those outcomes should remain separate rather than being labelled unsuccessful sales.
 
How many new listings entered your range during the period? Without that, 50 days can move sharply whenever one old unit appears or a quick one vanishes. I’d report the count beside the figure rather than presenting the timing on its own.
 
Agreed. The useful output may be a range rather than one precise average: ordinary-condition units, reserve-linked units and units needing work. Add counts and outcomes for each group. That would show whether the headline is robust or being driven by two or three cases.
 
Before splitting the data, freeze the two neighbourhood boundaries on a map and apply them consistently. Don’t change the boundary to capture a convenient comparison. If an edge property serves a different retail pitch, flag it separately rather than quietly including or excluding it.
 
My practical order would be: fix the boundaries, deduplicate relistings, record new-listing volume, separate agreed sales from completions, and retain withdrawals as their own outcome. Then mark condition, price-cut timing, reserves and any known financing delay. Until that is done, I wouldn’t use the 50-day figure to time an offer.
 
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