Real Estate Agents Google Maps Scraper

Scrape real estate agents, REALTORs, and brokerages from Google Maps and enrich each result with emails, social media links, brokerage affiliation, specializations, property types, NAR designations, languages spoken, services offered, listing-portal presence, customer review sentiment, online-booking / free-home-valuation detection, metro area classification, and agent-type classification (solo / team / brokerage office).

Built for real-estate-tech SaaS, mortgage lenders, title companies, recruiting brokerages, real-estate marketing agencies, and investors who need structured, CRM-ready data from Google Maps.

What data do you get?

Each scraped agent / brokerage includes up to 35+ fields across these categories:

Category	Fields
Identity	name, category, subCategories, brokerageName
Location	address, city, state, postalCode, country, latitude, longitude
Contact	phone, website, email
Social Media	instagram, facebook, linkedin, twitter
Real Estate	specializations, propertyTypes, designations, languagesSpoken, servicesOffered, listingPlatforms
Niche	hasOnlineBooking, bookingPlatform, bookingUrl, hasFreeValuation, freeValuationEvidence, freeValuationUrl, isMetroArea, metroName, metroTier, agentType, agentTypeLabel, agentTypeConfidence
Reputation	rating, reviewCount, reviewSentiment (label, score, topThemes, snippets)
Operational	hours, isOpenNow
Metadata	placeId, mapsUrl, scrapedAt, searchTerm, searchLocation

Sample output

{
    "name": "Jane Doe — Compass Real Estate",
    "category": "Real estate agent",
    "subCategories": ["Real estate agent", "Luxury real estate agency"],
    "brokerageName": "Compass",
    "specializations": ["Residential", "Luxury", "Investment"],
    "propertyTypes": ["Single-Family Home", "Condo / Townhouse"],
    "designations": ["Certified Residential Specialist", "Accredited Buyer's Representative"],
    "address": "90 5th Ave",
    "fullAddress": "90 5th Ave, New York, NY 10011, United States",
    "city": "New York",
    "state": "NY",
    "country": "United States",
    "postalCode": "10011",
    "latitude": 40.7368,
    "longitude": -73.9929,
    "phone": "+12125550100",
    "website": "https://janedoe-nyc.com/",
    "email": "jane@janedoe-nyc.com",
    "instagram": "https://instagram.com/janedoe.nyc",
    "facebook": "https://facebook.com/janedoenyc",
    "linkedin": "https://linkedin.com/in/janedoe-realtor",
    "twitter": null,
    "languagesSpoken": ["Spanish", "Mandarin"],
    "servicesOffered": ["Buyer Representation", "Seller Representation", "Free Home Valuation", "Home Staging"],
    "listingPlatforms": ["zillow.com", "realtor.com", "compass.com"],
    "hasOnlineBooking": true,
    "bookingPlatform": "calendly.com",
    "bookingUrl": "https://calendly.com/janedoe-nyc/30min",
    "hasFreeValuation": true,
    "freeValuationEvidence": "free home valuation",
    "freeValuationUrl": "https://janedoe-nyc.com/home-value",
    "isMetroArea": true,
    "metroName": "New York Metro",
    "metroTier": 1,
    "agentType": "solo_agent",
    "agentTypeLabel": "Solo Real Estate Agent",
    "agentTypeConfidence": "medium",
    "rating": 4.9,
    "reviewCount": 64,
    "reviewSentiment": {
        "label": "Positive",
        "score": 92,
        "topThemes": ["expertise", "communication", "negotiation"],
        "reviewsAnalysed": 10,
        "avgRating": 4.9,
        "snippets": {
            "positive": [
                "Jane was incredibly knowledgeable and negotiated $40k off our asking price...",
                "Smooth process from listing to close — she communicated with us every step..."
            ],
            "negative": []
        }
    },
    "hours": {
        "Monday": "9 am–6 pm",
        "Tuesday": "9 am–6 pm",
        "Wednesday": "9 am–6 pm",
        "Thursday": "9 am–6 pm",
        "Friday": "9 am–6 pm",
        "Saturday": "10 am–4 pm",
        "Sunday": "Closed"
    },
    "isOpenNow": true,
    "placeId": "0x89c2598ad12f1a8b:0x123abc456def7890",
    "mapsUrl": "https://www.google.com/maps/place/...",
    "scrapedAt": "2026-05-26T14:30:00.000Z",
    "searchTerm": "real estate agent",
    "searchLocation": "New York, USA"
}

How to use

1. Search terms — Enter categories like real estate agent, realtor, real estate broker, luxury real estate, commercial real estate, property management.
2. Locations — Enter cities or regions like New York, USA, London, UK, Toronto, Canada, Dubai, UAE.
3. Max results — Set how many places to return (up to 500).
4. Toggle enrichment — Enable or disable email extraction, social media, real-estate fields, and niche classification independently.

Input example

{
    "searchTerms": ["real estate agent", "luxury real estate"],
    "locations": ["New York, USA", "Los Angeles, USA"],
    "maxResults": 100,
    "minRating": 4.0,
    "enrichEmails": true,
    "enrichSocials": true,
    "enrichRealEstate": true,
    "enrichRealEstateNiche": true
}

Enrichment pipeline

The scraper runs a 3-phase enrichment pipeline for each agent:

1. Google Maps scraping

Extracts name, category, sub-category tags, address, phone, website, rating, reviews, hours, coordinates, and place ID directly from Google Maps search results.

2. Maps Overview enrichment (single Maps navigation)

• Brokerage — Detected from the agent's name (e.g. "Jane Doe — RE/MAX Realty") against a curated list of major US / UK / Australia / Canada brokerages.
• Specializations — Residential, commercial, luxury, investment, new construction, land, foreclosures, rentals, property management, first-time buyers, relocation, multi-family, waterfront, equestrian — inferred from Maps category + sub-category tags.
• Languages — Scanned from the Maps "About" attributes panel.
• Online booking / free valuation — Detected from action buttons on the Maps Overview tab.
• Metro area — Classified against a curated database of metros across USA, UK, India, UAE, Australia, and Canada with tier rankings (1-3).
• Review sentiment — Clicks the Reviews tab on Maps, extracts up to 10 reviews, and runs keyword-based sentiment analysis tuned for real-estate vocabulary (expertise, communication, negotiation, process, market care). Returns a label (Positive/Mixed/Negative), a 0-100 score, top themes, and representative snippets.

3. Website enrichment (single agent-website visit)

• Email — Visits the agent / brokerage website and extracts the best email using domain matching and scoring. Prefers role mailboxes like agent@, broker@, sales@, listings@, leasing@. Tries /contact as fallback. Filters out generic addresses (noreply, support, etc.).
• Social media — Extracts Instagram, Facebook, LinkedIn, and Twitter/X profile links.
• Brokerage (fallback) — If not detected from the name, scans the website for major brokerage names.
• Specializations (union) — Adds website signals on top of Maps-derived specializations.
• Property types — Single-family / condo / multi-family / land / commercial / industrial / etc.
• Designations — CRS, ABR, GRI, SRES, CCIM, SIOR, RENE, CLHMS, e-PRO, REALTOR® badge, and broker labels (Broker Associate, Managing Broker, Designated Broker).
• Languages (union) — Adds website signals on top of Maps-derived languages.
• Services — Buyer representation, seller representation, CMA / free home valuation, property management, investment consulting, relocation, staging, mortgage referrals, short sale / foreclosure, 1031 exchange, etc.
• Listing portals — Detects Zillow / Realtor.com / Redfin / Trulia / Compass / Rightmove / Zoopla / Bayut / PropertyFinder / realestate.com.au / realtor.ca links found on the agent's site.
• Online booking (fallback) — Calendly, Cal.com, Acuity, ShowingTime, ShowMojo, Rently, HubSpot Meetings, ChiliPiper, SavvyCal — plus native-form heuristic.
• Free home valuation (fallback) — "Free home valuation", "What's my home worth", "Free CMA", and other valuation CTAs.

Agent-type classification (pure compute)

After enrichment completes, the agent is classified as:

• solo_agent — single-agent listing on Maps
• team — team / group naming, or solo agent with high review volume
• brokerage_office — agency / brokerage office category
• unknown — insufficient signals

Use cases

• Real-estate-tech SaaS — Lead lists of agents by brokerage, specialization, and online presence (CRM, listing tools, CMA software, transaction management).
• Mortgage lenders & title companies — Find local agents / brokerages by metro and property type.
• Recruiting brokerages — Target solo agents not yet on top brokerage rosters; filter by review volume and specialization.
• Real-estate marketing agencies — Build outbound lists by metro, agent type, and online maturity (no booking tool, no CMA page, etc.).
• Investors — Find agents specialising in foreclosures, investment property, or multi-family.
• Market research — Analyze agent density, brokerage mix, designation prevalence, and sentiment by metro.

Proxy

This actor requires residential proxies to avoid Google Maps blocks. Apify residential proxy is configured by default. For best results, use the RESIDENTIAL proxy group.

Cost estimate

Each Google Maps search page processes up to ~20 results. With all enrichment enabled, each agent takes 20-40 seconds (one website visit per agent for emails, designations, services, listing-portal scan, booking/valuation fallback). A typical run of 100 results with full enrichment uses approximately 0.5-1.0 compute units on Apify.

Limitations

• Google Maps may return different results based on proxy location.
• Review sentiment analysis uses keyword matching (no LLM) — works best with 5+ reviews.
• Brokerage detection is name-driven first, then a website scan — small independent brokerages without national affiliation will read as null.
• Designation detection relies on the agent's website displaying the credentials in body text (NAR member directories aren't scraped).
• Metro area classification covers major metros in USA, UK, India, UAE, Australia, and Canada.