London inventory shifted in March 2025 — asking prices versus completed deals

[makeTheCanvas]

I’m tracking London property in March 2025 and struggling to reconcile asking-price data with completed sales. In my sample, well-presented mixed-use buildings appear to be moving in roughly 92 days, while homes needing work remain available longer. The visible gap between asking and completed prices is close to 7.7%.

Does this look like seasonal noise, or are buyers becoming more selective? I’d particularly value completed transactions or direct neighbourhood observations. Please say which part of London you follow rather than extrapolating from a citywide headline.

 

[bakesAndView]

Before treating 7.7% as a market-wide discount, how large is the sample and which asking price are you using: original, latest reduced price, or the figure shown near agreement? Those produce very different gaps. Mixed-use buildings also should not be pooled with ordinary homes. The 92-day figure may reflect property mix more than a London trend.

 

[readTheEcho]

There is also a timing mismatch. Sales completed in March were generally marketed and agreed earlier, whereas March asking inventory reflects sellers entering the market then. Completed-sale records can arrive late or be revised, so a first March extraction may understate volume. I’d compare cohorts by listing month and neighbourhood, then rerun the completed figures later.

 

[makeTheCanvas]

Fair points. The 7.7% is against the asking figure visible in my records, but I haven’t consistently separated original asks from later reductions. The sample is also mixed across London and includes both mixed-use buildings and homes, so I agree it is too broad for a citywide conclusion.

I’ll split it by property type, neighbourhood and listing month, and keep the first extraction so later revisions are visible. What minimum details would make local comparisons useful without turning this into a huge spreadsheet?

 

[readTheEcho]

Keep it simple: neighbourhood, property type, condition, original ask, final ask before agreement, completed price, listing date, agreement date and completion date. Even where a field is missing, mark it missing rather than substituting another date. Transaction count matters too; a percentage based on a handful of unusual buildings can look precise while saying very little.

 

[walksAndRoof]

Waiting for more completions improves coverage, while classifying homes by presentation may introduce a subjective judgment; neither resolves the comparison by itself. A well-presented property completing in 92 days could reflect its condition, but it could just as easily have entered the market at a more realistic price.

I would keep the condition field, then check it against the original asking price and every recorded reduction. That revision history is the fact most likely to show whether buyers paid for turnkey condition or simply responded to better pricing.

 

[readTheEcho]

Agreed, and policy timing could distort the monthly pattern as well if buyers or sellers were trying to complete around a known change. Rather than assigning that effect in advance, annotate any relevant deadline and see whether agreement or completion dates cluster around it. Also report both transaction volume and median gaps; a changing mix can move the headline even if comparable properties behave similarly.

 

[anika.dean]

A useful test would be to freeze the March 2025 cohort now, then revisit the same records after more completions appear. Publish the initial count, later additions and any corrected prices. If the 7.7% gap survives separate comparisons for neighbourhood, type, condition and original versus reduced asking price, selectivity becomes more plausible. If it disappears, this was probably sample composition, reporting lag or seasonal noise.