Sydney retail listings: what does 91 days on market really indicate?

[loft.balanced]

I’m sense-checking a Sydney sample dominated by retail units priced from A$522,900 to A$784,300. The typical listing has remained visible for 91 days. My working theory is that energy performance helps separate the quick sales from the stale stock, but there are more listings than properties I would actually buy.

Would you investigate the older listings for negotiable sellers, or wait for better new stock? I’m especially interested in completed sales, withdrawals and when price cuts occur.

 

[SashaRidge]

I think you’re putting too much weight on energy performance. It may matter, but 91 days could just as easily reflect an ambitious asking price, poor condition or limited buyer financing. Compare the stale listings with recent completed sales in the same small area and property category. Asking prices alone won’t tell you where buyers and sellers are actually meeting.

 

[talia_plans]

I’d be reluctant to act on the 91-day figure until the clock itself is checked. A unit withdrawn and advertised again may look like fresh stock even though buyers have already rejected it, while a genuinely continuous campaign tells you more about seller flexibility.

I’d also narrow the comparison to streets and retail units serving similar buyers. If the older stock has remained continuously available, compare its condition and price with recent completed sales. If it has mostly been recycled through new listings, treat the portal days as unreliable and investigate the withdrawal history first.

 

[SolidAnchor]

I wouldn’t discard the energy idea, but for a retail unit I’d first separate building efficiency from the unit’s overall condition and suitability. A buyer may accept higher running costs if the property otherwise works, while an efficient unit can still sit if it needs substantial work or the seller will not adjust. Financing and seller motivation could overwhelm the energy difference.

 

[talia_plans]

That’s why I’d split the sample rather than search for one explanation. Groups could include sold, still advertised, withdrawn and relisted. Then compare price changes, condition, energy information where available, and days visible. If the quick sales consistently look stronger on energy after those other differences are considered, Diego’s theory becomes more persuasive.

 

[SolidAnchor]

New-listing volume is another missing piece. More listings do not automatically mean more genuine choice if much of the increase is unsuitable or repeatedly recycled stock. A weekly count of genuinely new units, separate from relistings, would help explain the gap between the headline supply and Diego’s “not many I’d buy” reaction.

 

[SolidAnchor]

One more thing: record the timing of the first price reduction, not just the final asking price. A unit sitting for 91 days without a cut suggests a different seller from one reduced early and still unsold. That distinction may be more actionable than the average time online.

 

[iris_reads]

The street boundary point deserves emphasis. For retail property, two nearby units can face quite different immediate surroundings, so broad suburb comparisons may create false bargains. I’d only use completed sales as close comparables after checking that the location, condition and basic property characteristics are genuinely similar.

 

[talia_plans]

Agreed, although making the comparison too narrow can leave you with almost no sales. I’d use two layers: a tight local set for direct comparison and a wider Sydney set to test whether the same patterns appear elsewhere. That avoids treating one unusual street or one motivated seller as the market.

 

[SolidAnchor]

For the stale listings, the practical next step is to ask the selling side a consistent set of questions: has the campaign been continuous, have earlier offers or contracts fallen away, has the price guidance changed, and does the seller have a preferred timeline? The answers may be incomplete, but asking the same questions across listings makes differences easier to spot.

 

[KindCreek]

I’d also avoid assuming that every withdrawal represents failed demand. Some owners may simply decide not to proceed, while others return with altered pricing. Keep withdrawals as their own category until you know more. Otherwise they can distort both your days-on-market figure and your impression of seller motivation.

 

[sailsAndVale]

The sensible decision rule seems to be: don’t wait purely because the typical listing has reached 91 days, and don’t chase stale stock purely because it looks negotiable. Shortlist units that meet your condition and location requirements, compare them with completed sales, then investigate campaign history and seller flexibility. Energy performance can remain one testable factor rather than the main explanation assumed in advance.