data accumulation

Propertydata asia is using innovative data collecting procedures, combining advanced software tools and human quality checks. The property data is for each individual property market aggregated from 8-10 different sources and contains thousands of listings. The result is therefore a very stable and wide overview of the monitored property market. It’s aimed to get a full survey for each property market and the evaluation of these data is conducted on a quarterly basis.


The data collection sources on public available property listings (asking prices). The calculated prices and and benchmarks are based on an evaluation of asking prices. Transaction prices may differ from asking prices, especially in not very liquid markets.
The database for each reported region contains thousands of listings (eg. Bali 7’500, Bangkok 30’000) from across 8-16 different sources.
The price values are calculated in the lead currency of the particular property market (e.g. Bali US$, Bangkok THB) and are kept unadjusted between the different quarters and years (no adjustment of previous values over time).


Based on the aggregated real estate data, “urbanalyse” developed a cutting edge analysis method to visualize the property benchmarks in a compact and easy to read survey.
All values and benchmarks are grouped (disaggregated) into individual segments between five percentiles (10%, 30%, 50%, 70%, 90%) and therefore makes it possible to analyze different property price categories.

price allocation

A percentile (pctl) is a statistical measure. It is the value of a property offer that has a certain percentage of other offers that fall beneath it. The n% percentile of the price allocation is the value that cuts off the first n percent of the property offers when it is sorted in ascending order.
For example, the 30% percentile is the value below which 30 percent of the property offers may be found. The 50% percentile is known as the median and forms the boundary between the expensive and the inexpensive half of the property offers. Five useful property segments are grouped between these percentiles.


  • >90% percentile: high end segment
  • 70% – 90% percentile: expensive segment
  • 50% – 70% percentile: upper midfield
  • 30% – 50% percentile: lower midfield
  • 10% – 30% percentile: cheap segment
charts / graphs

To seek out useful information from the collected data, property data asia uses state of the art analysis and visualization software.
Various charts and graphs techniques have been developed which support the analysis of data. These visualisations are combined and clearly presented in standardised propertydata reports.

property market overview:
Each individual property listing is is displayed and the trend curve as well as percentile marks are indicated. In the shown example the property price in relation to the property size.

property price comparison:
Price allocation and key price indicators of local areas in comparison to each other areas in the same property market (region).

property parameter comparison:
frequency illustration of the bedrooms amount distribution and their comparison between other local areas.

benchmarks of key indicators:
Comparison of local and regional benchmarks.


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property data

propertydata asia is monitoring emerging property markets in south east Asia