The UAE real estate market gets covered endlessly in terms of property prices and transaction volumes. What gets less attention is the agent layer sitting underneath all of it. Who are these people? How experienced are they? What languages do they speak? Which agencies dominate by headcount?
I put together a structured dataset of every active agent listed on PropertyFinder UAE as of May 2026. This is what I found, and what the data is actually useful for.
What the dataset contains
19,994 agents, each with 51 fields covering:
- Contact details: email, phone, WhatsApp, LinkedIn
- Professional background: years of experience, position title, bio, nationality
- Credentials: BRN license number, verified status, superagent status
- Performance: platform ranking, average rating, full rating distribution, median listing quality score
- Active listings: broken down by residential sale, residential rent, commercial sale, commercial rent
- Transaction history: total deal count, total volume in AED, average sale and rent prices
- Response behavior: average WhatsApp response time in minutes
- Languages spoken
- Top active locations (as location IDs, joinable against a separate locations table)
- Agency: name, address, city, logo URL
- Direct profile URL for each agent
A few things that stand out
The market is genuinely multilingual.
This is not a market where English is assumed. A meaningful portion of agents list languages like Arabic, Russian, Hindi, Urdu, Persian, French, and Mandarin. If you are building a lead routing system or a CRM that matches clients to agents, language matching is a real feature, not a nice-to-have.
Experience range is wide.
The experience_since_year field shows agents who have been active since the early 2000s sitting alongside people who started last year. If you are doing any kind of agent quality scoring, tenure is a useful baseline signal alongside rating and transaction volume.
Transaction volume tells a different story than listing count.
An agent can have 50 active listings and a claimed deal volume of zero. Another agent might have 8 listings and 200 million AED in claimed transactions. The dataset captures both, which means you can segment agents by activity type rather than just volume of listings on the page.
WhatsApp response time is tracked.
This surprised me. PropertyFinder tracks and exposes average WhatsApp response times per agent. For a market where WhatsApp is the primary sales communication channel, this is a real operational signal. The variance across agents is large.
Agency concentration.
The agency_id and agency_name fields let you count agents per agency. A handful of agencies account for a disproportionate share of total agents. If you are doing competitive research on agency market share, this is a straightforward query.
What the data is actually useful for
PropTech and CRM tools
If you are building anything in the UAE real estate space, you need a structured agent directory. This dataset gives you a ready-to-use starting point for agent profiles, lead routing, search, and filtering. Building it yourself means collecting, cleaning, and deduplicating thousands of records before you write a single line of product code.
B2B outreach and marketing
19,994 agents with email, phone, and WhatsApp. Segmentable by language, experience, specialty (residential vs commercial), agency, and location coverage. If you are selling software, financial products, or services to UAE real estate agents, this is a usable prospecting list.
Market research
Which nationalities are most represented in the agent population? How does average rating vary by agency? What is the distribution of experience across the market? These are answerable questions once the data is in a spreadsheet or a database.
Investment and partnership decisions
If you are a developer, an investment fund, or an agency looking to partner with top-performing agents in specific areas, the combination of transaction volume, claimed deal data, and location IDs gives you a shortlist starting point faster than reading individual profiles.
A note on the location IDs
The top_location_ids field contains pipe-separated PropertyFinder location IDs representing each agent's primary areas. These IDs reference a separate locations table (which I also have as a dataset) containing 15,248 UAE locations with names, types, coordinates, and hierarchy. Without that table, the IDs are opaque. With it, you can answer questions like "show me all verified agents whose top locations include Dubai Marina or Downtown Dubai."
Format and availability
The dataset is available as a CSV file. 19,994 rows, 51 columns, UTF-8 encoded, no JSON blobs. Every column is a readable value.
If you want a sample or have a specific use case in mind, get in touch.
Final thought
Real estate data in the UAE tends to get packaged at the transaction and property level. Agent-level structured data is less common, which is part of why it is useful. The people executing these transactions are not well represented in public datasets. This is one attempt to change that.
Wants to get the dataset, check here: https://payhip.com/b/bld1P
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