We Analyzed 456,000 Bangkok Property Listings. Here's What We Found.

Thailand's property market has a data problem. Not a shortage of data. The opposite. Listings are scattered across half a dozen portals, each with its own format, its own coverage gaps, its own definition of what a "listing" even is. No single platform has the full picture. Every agent, developer, and investor is making decisions on a fraction of the available information.

We decided to fix that. Over the past several months, we built scrapers for every major Thai property portal and loaded the results into a single Postgres database. The result: 456,000 Bangkok listings from six sources, normalized across 47 zones, with contact data, pricing, and property type breakdowns.

This is what the data looks like when you actually put it all together.

The Fragmentation Problem

The Thai property market runs on portals. LivingInsider is the largest by volume, with roughly 390,000 listings nationwide. PropertyHub follows with 277,000. Then there's a long tail: Teedin108 and KaiBaanThai each contribute around 64,000, Thailand-Property adds 42,000 for Bangkok alone, Kaidee sits at 24,500, and RentHub rounds things out with 18,000 focused on rentals.

Total volume across all sources exceeds 500,000 listings. But here is the critical part: overlap between portals is lower than you would expect. Only about 23% of listings appear on more than one platform, based on address and price matching. That means if you are only searching one portal, you are potentially missing three quarters of the market.

This is not a minor inconvenience. For developers scoping new projects, for agents building comparative market analyses, for investors trying to find undervalued pockets, working from incomplete data leads to incomplete conclusions. The first thing that becomes obvious when you aggregate everything is just how much each individual portal is missing.

Where the Supply Is

Bangkok's 47 zones do not contribute equally. The top 10 zones account for 58% of all listings in the dataset. The bottom 20 zones combined make up less than 9%.

Sukhumvit dominates. With 52,400 listings, it represents 11.5% of all Bangkok supply on its own. This is not surprising. Sukhumvit stretches across a massive swath of the city, covering everything from the ultra-premium lower sois near Asok down to the more affordable stretches past On Nut. It is less a single market and more a collection of micro-markets wearing the same name.

After Sukhumvit, the next tier includes Ratchadaphisek (31,200 listings), Ladprao (28,700), Bangna (26,100), and Rama 9 (24,800). These five zones alone hold 35% of total supply. They share a common trait: strong BTS or MRT connectivity, established residential infrastructure, and active condo development over the past decade.

On the other end, zones like Taling Chan (3,100 listings), Prawet (2,800), and Nong Chok (1,400) are dramatically underrepresented. Whether that reflects genuine low supply or simply less agent activity in those areas is an open question. Probably both.

Price Distribution: The Two Bangkoks

Pricing data across 456,000 listings reveals something the market already knows intuitively but rarely quantifies: Bangkok is two markets stacked on top of each other.

For sale listings, the median asking price sits at 3.2 million baht. But that median hides a bimodal distribution. There is a massive cluster between 1.5 and 4 million baht, dominated by condos in the mid-ring zones. Then there is a second, smaller peak between 8 and 15 million baht, driven by houses and townhouses in premium zones.

Rental listings follow a similar pattern. The median monthly ask is 15,000 baht, with a heavy concentration between 8,000 and 20,000 baht. Premium rentals in Sukhumvit, Sathorn, and Silom push well past 80,000 per month, but they represent less than 4% of total rental supply.

The zones commanding the highest per-square-meter sale prices will not surprise anyone: Silom/Sathorn (avg 142,000 baht/sqm), Sukhumvit lower sois (avg 138,000 baht/sqm), and Chidlom/Ploenchit (avg 156,000 baht/sqm). These three zones alone account for the majority of listings priced above 10 million baht.

Meanwhile, zones like Bangkae, Min Buri, and Nong Chok average below 45,000 baht per square meter. The gap between the most and least expensive zones is roughly 3.5x. That spread has been widening, not narrowing, over the past three years based on historical listing data.

Rent vs. Sale: A 60/40 Split

Of the 456,000 Bangkok listings, approximately 274,000 (60%) are for sale and 182,000 (40%) are for rent. This ratio varies dramatically by zone.

In Sukhumvit, rental listings actually outnumber sale listings 54% to 46%. The same pattern holds in Silom/Sathorn (57% rental) and the areas around Chidlom. These are zones with heavy expat populations and high condo density. Short term and corporate rentals inflate the numbers further.

Flip to the outer zones and the ratio inverts. Bangkae runs 78% sale, 22% rental. Ram Intra is 74% sale. Nong Chok is 81% sale. In these areas, the market is primarily homeowners selling to other homeowners. Rental stock is thin and mostly single houses, not condos.

This split matters for anyone building a business around property data. A platform focused purely on sales misses nearly half the market in the city's most commercially active zones. A platform focused on rentals is irrelevant in the suburbs. You need both, and you need them broken down by zone, not just citywide averages.

Contact Quality: The Hidden Data Problem

Here is something most people do not think about: how many of those 456,000 listings actually have usable contact information?

We classified every listing into one of four contact categories. Direct phone number (the agent or owner's real number). LINE ID (increasingly the preferred contact method in Thailand). Hashed or masked contact (the portal hides the number behind a "click to reveal" wall or replaces digits with asterisks). And no contact at all.

The results are sobering. Only 41% of listings across all sources have a direct, unmasked phone number. Another 18% have a LINE ID but no phone. That leaves 27% with masked or hashed contacts that require portal registration to access, and 14% with no contact information whatsoever.

Contact quality varies enormously by source. LivingInsider is the best performer at 68% direct contacts. Its API returns phone numbers in plaintext for most listings. Thailand-Property sits around 52%, though their agent contact endpoint requires account registration. Kaidee and RentHub hover near 35%. PropertyHub is the worst at just 22% direct contacts. The rest are hidden behind their messaging system.

For anyone building a CRM or lead distribution system on top of listing data, this is the real constraint. Raw listing counts mean nothing if you cannot actually reach the person behind the listing. Contact quality is the moat.

Agent Concentration: A Long Tail Market

One of the more interesting patterns in the dataset is agent concentration. We identified approximately 87,000 unique agents or listing owners across all 456,000 listings, based on deduplicated phone numbers and LINE IDs.

The distribution follows a steep power law. The median agent has 2 listings. The mean is 5.2. But the top 1% of agents (roughly 870 individuals or companies) control 34% of all listings. The single most prolific agent in the dataset has 4,200 active listings across three portals.

This creates a natural segmentation. At the top, you have professional agencies and developer sales teams who manage hundreds or thousands of listings and are already sophisticated about data. In the middle, there are part-time agents with 10 to 50 listings who are the backbone of the market but lack tools. At the bottom, there are individual owners posting one or two listings who will churn out of the system within months.

The middle segment is the most underserved. These agents are active enough to benefit from market intelligence, pricing comparisons, and lead management, but too small to build or buy enterprise tools. They are juggling spreadsheets, LINE groups, and manual portal logins. Every portal gives them a dashboard for their own listings, but none gives them a view of the broader market.

What Fragmentation Really Means

Here is the uncomfortable truth about Thailand's property data landscape: fragmentation is not a bug. It is the business model. Every portal benefits from keeping users inside its own ecosystem. LivingInsider has no incentive to help you compare its listings against PropertyHub. PropertyHub has no incentive to surface data from Kaidee.

This creates three problems that compound on each other.

First, pricing intelligence is poor. Without cross-portal comparison, agents and owners price listings based on gut feel and whatever they see on their primary portal. We found that identical properties (same building, same floor, same unit type) are listed with price differences of up to 18% across portals. That is not market variation. That is information asymmetry.

Second, lead quality suffers. Serious buyers and tenants learn to search multiple portals, which means agents get duplicate inquiries from the same person across different platforms. The agent has no way to deduplicate or track these leads without manual effort.

Third, market analysis is guesswork. When a developer wants to understand supply in Rama 9 before launching a new project, they are looking at one portal's data and extrapolating. With 456,000 listings aggregated, the picture changes. Zones that look undersupplied on one portal turn out to be saturated when you count everything.

Fragmentation is an opportunity for anyone willing to do the aggregation work. But it is also a tax on everyone operating in the market today.

What We Built

This analysis is not theoretical. Every number in this post comes from a live database that we update continuously. Six scrapers running on rotating schedules, a normalization pipeline that maps listings to 47 Bangkok zones, deduplication logic based on address matching and price similarity, and a contact extraction layer that pulls phone numbers and LINE IDs from raw listing data.

We built Vurel to make sense of this data. Not another listing portal. A market intelligence layer that sits on top of all of them. Zone-level supply and pricing dashboards. Contact quality scoring. Agent concentration analysis. The kind of information that should exist but does not, because no single portal has the incentive to provide it.

The Thai property market is not short on listings. It is short on clarity. We are fixing that.

Explore the data at vurel.io.