Bangkok asking prices versus what actually moves

R

RightRoom

Real estate agent
Established
If I mistake old advertisements for weak demand, I could draw the wrong conclusion about what Bangkok properties are actually selling. My notes cover mainly mixed-use buildings advertised between THB 4,896,000 and THB 7,344,000. Their median visible exposure is about 111 days, but confirmed transaction information is scarce.

What should be verified before that figure means anything? I can divide the sample by smaller neighbourhoods and condition, but I am less sure how to identify duplicate advertisements, withdrawals and relistings. Seller urgency and financing may also explain why similar-looking properties move at very different speeds. Is there a reliable listing event or other evidence worth recording before I classify a disappeared advertisement as a sale?
 
Start with neighbourhood boundaries. “Bangkok” is too broad for this comparison, and even nearby streets can attract different buyers. I’d also treat 111 days as listing exposure, not necessarily time on market: a property can be withdrawn, moved between agents or advertised more than once. Without removing duplicates and relistings, the stale-stock picture may be exaggerated.
 
How are you defining a completed sale? Is it a confirmed transfer, an agent saying a deal was agreed, or simply a listing disappearing? Those are not interchangeable.

Condition also needs its own column. Two mixed-use buildings at similar asking prices may require very different spending before occupation, so comparing only price and location could hide the reason one moves quickly.
 
I wouldn’t dismiss the 111-day figure completely. Even imperfect listing data can show which asking prices fail to attract buyers. The bigger trap is assuming every unsold property reflects weak demand. Some sellers may have little urgency and hold their price, while buyers for mixed-use property may face different financing constraints from buyers considering a straightforward home.
 
Before adding another month of listings, I would lock the current group and observe what happens to each property. That sacrifices a constantly updated snapshot, but it makes the histories far easier to interpret.

The point about unmotivated sellers is valid, so disappearance alone should not be labelled a sale. Record every price change, agent switch, removal and return to the market, while counting genuinely new supply separately within the narrower neighbourhoods. You may still lack confirmed sale prices, but at least persistent stock, reductions and withdrawals will no longer be mixed together.
 
These replies have exposed two weaknesses in my notes: I haven’t consistently separated withdrawn listings from relisted ones, and my neighbourhood groupings are too loose. I’ll keep the THB 4,896,000–7,344,000 bracket but split the sample into smaller areas, add condition, and track the existing listings as a fixed group. I’ll also stop treating a vanished advertisement as a completed sale unless there is better confirmation.
 
That should make the results more useful, but I’d split the property type further too. “Mixed-use” can cover buildings with very different residential and commercial layouts, occupancy, access and repair needs. Those differences affect the likely buyer pool and may matter more than a modest asking-price cut. Compare like with like first; otherwise the neighbourhood split could still give a misleading answer.
 
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