Hello from Bangkok — where should I start with Thailand market data?

R

RightRoom

Real estate agent
Established
My immediate difficulty is finding Bangkok information that compares like with like. I am looking at mixed-use property and trying to understand how renovation, transaction costs, occupancy and property management affect the difference between listing figures and completed deals.

I joined because comparisons with other markets may help expose assumptions that are easy to miss when reading only local material. Is there a Thailand board discussion or a small, clearly defined source that would be a sensible first stop?
 
One area and one building category should be the limit at first. I would not begin by reading the whole local board or choosing the largest dataset, because inconsistent definitions will create more noise than useful evidence.

Build a small sample for the same period and label each number as advertised, revised or completed. Then note condition, occupancy, renovation needs and management arrangements. That gives you something narrow enough to test while still using the board to fill specific gaps.
 
You have already identified the price and cost questions, but the meaning of “mixed-use” is still unclear. Are you studying one unit within a development, or the whole building with several uses?

For an individual unit, I would concentrate on comparable units, shared management and any renovation limits. For an entire building—for example, shops below with homes above—the tenancy mix, building-wide works and management burden become central. Decide which branch applies before choosing the data, and also say whether this is for a live property decision or general market research.
 
I’d go further and say a dataset may not be the best first read. Before collecting prices, write down exactly what each figure represents: asking price, revised asking price or completed price, and whether associated costs are included. A smaller table with consistent definitions is more useful than a large one mixing unlike numbers.
 
A practical starting sheet could have columns for date, location, building type, uses, area, condition, occupancy assumptions, advertised price, completed price where known, transaction costs and renovation allowance. Leave unknowns blank rather than estimating them silently. That will expose which information is genuinely missing.
 
Thanks, this is already helping. I’m not trying to force every mixed-use property into one category; the aim is to develop a repeatable way to compare them without pretending the data is cleaner than it is. I’ll begin with a narrow local sample and keep advertised and completed figures separate. The management and renovation variables are probably where my first version needs more work.
 
On those variables, separate one-off renovation spending from recurring property-management costs. Also record whether renovation affects usable space, likely occupancy or the timing of income. Two buildings with similar completed prices can produce very different models once disruption and ongoing management are considered.
 
For a first-purchase-style exercise, I would put the legal checklist before the return calculation. Mixed-use property can raise questions that a residential-only comparison misses, and the relevant position depends on the particular property and jurisdiction. Use the forum to identify questions, then have Thailand-specific professionals confirm anything that would affect an actual transaction.
 
Mortgage comparisons also deserve their own scenario rather than one universal assumption. Run the same property with no borrowing, with the financing terms being considered, and with renovation taking longer than expected. That shows whether the apparent opportunity comes from the building itself or from optimistic finance and timing inputs.
 
There probably isn’t one ideal first dataset. Your best route is to post the narrow sample on the local board and ask members where each completed-price figure can be verified. Then build three linked pieces: a price comparison, a transaction-cost and legal-question list, and an operating model covering management and renovation. Keeping those separate should make cross-market comparisons much clearer.
 
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