Seloger Property Search Scraper

SeLoger.com Property Search Scraper: Extract French Real Estate Market Data

Understanding SeLoger.com and the Value of Its Data

SeLoger.com stands as one of France's most trusted and widely-used real estate platforms, connecting millions of property seekers with sellers, agents, and developers across the country. Launched in 1992, the platform has evolved into a comprehensive marketplace covering residential sales, rentals, and new developments throughout France and Monaco.

What makes SeLoger.com particularly valuable is its extensive coverage of the French property market. The platform aggregates listings from thousands of real estate agencies, individual sellers, and property developers, providing a near-complete picture of available properties in any given region. From Parisian apartments to Provençal villas, coastal properties to mountain chalets, SeLoger.com captures the diversity and dynamism of French real estate.

For property investors, real estate professionals, and market analysts, this data represents critical intelligence. Understanding pricing trends, feature preferences, geographic hotspots, and inventory levels informs strategic decisions worth millions of euros. However, manually reviewing hundreds or thousands of property listings to extract meaningful patterns is practically impossible. The SeLoger.com Property Search Scraper automates this process, transforming scattered listing pages into structured, analyzable datasets that reveal market insights previously accessible only to major real estate networks.

Core Functionality and Target Users

The SeLoger.com Property Search Scraper efficiently extracts detailed information from property search result pages on the platform. Unlike basic scrapers that capture only surface-level data, this tool delves deep into each listing to retrieve comprehensive property details, seller information, location data, and visual assets.

The scraper handles SeLoger.com's complex page structure, including dynamic content loading and various listing formats. It captures data from multiple transaction types—sales, auctions, and compulsory auctions—and various property categories including houses, apartments, land, commercial properties, and new developments. The tool respects pagination, automatically navigating through search results to collect the specified number of listings per URL.

This scraper serves diverse professional needs across the real estate ecosystem. Property investors use it to identify undervalued opportunities, track price movements, and analyze market supply in target regions. Real estate agencies leverage the data for competitive analysis, understanding how their listings compare to market averages in pricing, features, and presentation. Property developers monitor demand patterns, popular features, and pricing trends to inform new project planning.

Market research firms and financial analysts utilize the scraper to generate comprehensive market reports, tracking regional variations, seasonal trends, and the impact of economic factors on property values. PropTech companies integrate this data into their platforms, offering enhanced search capabilities, price prediction models, or automated valuation tools. Even individual property buyers can use the data to make informed decisions, understanding fair market values before negotiating purchases.

Input Configuration and Parameters

The scraper accepts SeLoger.com search result URLs as primary input. These URLs are generated when you perform a property search on the platform using filters like location, property type, transaction type, price range, and other criteria. The URL structure captures all your search parameters, allowing the scraper to extract exactly the subset of properties you're interested in.

Here's a detailed breakdown of the input configuration:

{
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  },
  "max_items_per_url": 20,
  "ignore_url_failures": true,
  "urls": [
    "https://www.seloger.com/classified-search?distributionTypes=Buy,Buy_Auction,Compulsory_Auction&estateTypes=House,Apartment&locations=AD08FR31096&order=Default&m=homepage_new_search_classified_search_result"
  ]
}

Example Screenshot:

Proxy Configuration: The proxy object ensures reliable data collection. Using residential proxies (RESIDENTIAL) makes your requests appear as normal user traffic, significantly reducing the risk of detection or blocking. While you can select different proxy countries, using French (FR) or European proxies typically provides better performance and more accurate results when scraping French real estate sites.

Max Items Per URL: The max_items_per_url parameter controls how many property listings to extract from each search URL. Setting this to 20 means the scraper will collect up to 20 properties from the search results. You can adjust this based on your needs—use smaller numbers for quick samples or larger numbers (50-100+) for comprehensive market analysis. Keep in mind that higher numbers increase execution time and computational costs.

Ignore URL Failures: When ignore_url_failures is set to true, the scraper continues processing even if some URLs fail to load. This is particularly useful when scraping multiple search URLs—one problematic URL won't halt your entire data collection. If you need to ensure every URL processes successfully, set this to false to receive error notifications.

URLs Array: Include one or more SeLoger.com search URLs. The example URL shows a search for houses and apartments available for purchase (including auctions) in a specific French location. You can generate these URLs by:

1. Visiting SeLoger.com
2. Using the search filters to define your criteria (location, property type, price range, etc.)
3. Copying the resulting URL from your browser's address bar
4. Pasting it into the urls array

You can include multiple search URLs to scrape different regions, property types, or price ranges in a single run. For example, you might include separate URLs for Paris apartments, Lyon houses, and Marseille commercial properties to build a comprehensive multi-city dataset.

Complete Output Structure and Field Definitions

The scraper returns JSON data with each property as an object containing detailed fields. Understanding field purposes enables effective analysis and application.

Listing Identification

ID: Unique alphanumeric identifier of the listing on SeLoger. Purpose: Database indexing, tracking specific listings over time, avoiding duplicates, linking to detail pages.

Legacy ID: Older numeric identifier of the same listing. Purpose: Matching records with historical datasets and older SeLoger URLs.

Listing URL: Direct link to the full listing on SeLoger. Purpose: Accessing complete details, sharing opportunities with clients, verification of scraped data.

Portal: Source portal of the listing (seloger). Purpose: Identifying the data source when merging datasets from multiple portals.

Status: Publication status of the listing (e.g., Published). Purpose: Filtering active listings.

Title: Listing title with property type and sale condition. Purpose: Quick preview and listing summaries.

Property Type: Human-readable property type (e.g., Appartement). Purpose: Display in reports and dashboards.

Property Type Code: Standardized property type code (e.g., APARTMENT). Purpose: Segmenting the market by property category.

Transaction: Type of transaction (e.g., BUY). Purpose: Separating sales from rentals and other deal types.

Product Type: Listing product category (e.g., project for new-build programs). Purpose: Distinguishing new-build projects from resale listings.

Advertiser Type: Type of publisher (e.g., PROFESSIONAL). Purpose: Separating professional advertisers from private sellers.

Description

Headline: Short headline summarizing the property. Purpose: Quick preview and keyword analysis.

Description: Description text of the listing (may be truncated by the source). Purpose: Extracting extra details (energy rating, delivery date, outdoor space, financing), keyword and sentiment analysis.

Pricing and Size

Price: Asking price as a number. Purpose: Price comparison, market valuation, budget filtering.

Price Text: Price exactly as displayed on the listing. Purpose: Display and verification against the website.

Price Per M2 Text: Price per square meter as displayed. Purpose: Quick benchmarking of value across properties and districts.

Currency: Currency of the listed price. Purpose: Correct financial interpretation when merging datasets from multiple markets.

Area M2: Main living area in square meters. Purpose: Price-per-m² analysis, size-based filtering.

Plot Area M2: Plot/land area in square meters (null if not applicable). Purpose: Valuing houses and land plots.

Rooms: Total number of rooms. Purpose: Matching properties to buyer requirements.

Bedrooms: Number of bedrooms. Purpose: Household size targeting and filtering.

Attributes: Flexible list of property characteristics, each with type, label, value, and display_value (e.g., rooms, bedrooms, living space, floor, energy certificate, building state). Purpose: Capturing all property features in one field without fixed columns, as available attributes vary between listings.

Location

Country: Country of the property. Purpose: Geographic segmentation and multi-market analysis.

Region: Administrative region (e.g., Ile-de-France). Purpose: Regional market comparison.

Province: Department/province of the property (e.g., Paris). Purpose: Province-level statistics and filtering.

City: City or arrondissement of the property. Purpose: City-level market analysis and lead targeting.

District: Neighborhood/district within the city. Purpose: Micro-market analysis and price comparison between districts.

Zip Code: Postal code of the property. Purpose: Geographic grouping and postcode-level analysis.

Is Address Published: Whether the exact address is displayed on the listing. Purpose: Assessing location precision.

Transport: List of nearby public transport grouped by type (METRO, TRAM, BUS), each with line names. Purpose: Evaluating accessibility and commuting convenience.

Flags

Flags: Object of listing status indicators: is_new (new listing/build), is_exclusive (exclusive mandate), has_brokerage_fee (agency fee applies), has_3d_visit (3D virtual visit available). Purpose: Filtering by listing characteristics and assessing listing quality.

Agency / Advertiser

Agency ID: Identifier of the advertiser account on SeLoger. Purpose: Grouping listings by agency, competitor tracking.

Agency Name: Name of the agency publishing the listing. Purpose: Lead generation, competitor analysis, market share evaluation.

Agency Type: Publisher category (e.g., AGENCY). Purpose: Separating agencies from other publishers.

Is Private Owner: Whether the seller is a private individual. Purpose: Separating private sellers from professionals.

Agency Profile URL: Link to the agency profile on SeLoger. Purpose: Exploring the agency's portfolio and details.

Agency Logo URL: Link to the agency logo image. Purpose: Branding in reports and dashboards.

Agency Address: Registered office address of the agency. Purpose: Geographic targeting and local outreach.

Agency Phone Numbers: List of contact phone numbers. Purpose: Direct outreach to the agency.

Agency Legal Information: List of label/value legal details (e.g., name, registered office, RCS, SIRET). Purpose: Business verification and company data enrichment.

Contact Name: Name of the contact person for the listing. Purpose: Personalized lead outreach.

Listing Dates

Created At: Date and time the listing was created (ISO 8601). Purpose: Measuring time on market, time-series analysis.

Updated At: Date and time the listing was last updated (ISO 8601). Purpose: Detecting changes and listing freshness.

Media

Image Count: Total number of images in the listing. Purpose: Evaluating listing quality and completeness.

Images By Category: Image count grouped by category (LIVING_ROOM, BEDROOM, KITCHEN, etc.). Purpose: Analyzing how thoroughly each area is documented.

Images: List of image objects with url, category, and alt text, in original order. Purpose: Downloading images, visual inspection, computer vision analysis.

Has Floorplans: Whether floor plans are available. Purpose: Assessing listing completeness.

Has Virtual Tour: Whether a virtual tour is available. Purpose: Identifying remote-viewing-ready listings.

Raw Data

Raw Data: Complete original JSON object of the listing as scraped, without modification. Purpose: Auditing, debugging, accessing fields not included in the cleaned output, and reprocessing without re-scraping.

Here's a representative example of the output data:

{
  "id": "26P5VQGJEEX6",
  "legacy_id": "285389187",
  "listing_url": "https://www.seloger.com/annonce/achat/ile-de-france/paris-75/paris-75000/26P5VQGJEEX6",
  "portal": "seloger",
  "status": "Published",
  "title": "Appartement à vendre • neuf",
  "property_type": "Appartement",
  "property_type_code": "APARTMENT",
  "transaction": "BUY",
  "product_type": "project",
  "advertiser_type": "PROFESSIONAL",
  "headline": "Charmant 2 pièces avec terrasse de 28.7 m² à Paris 14e",
  "description": "Découvrez ce charmant appartement de 2 pièces, idéalement situé au 6ème étage d'un immeuble moderne, qui vous séduira par son agencement pratique et ses généreux espaces extérieurs. Avec une surface habitable de 54,8 m² et un balcon de 28,7 m² orienté plein sud, vous profiterez d'une luminosité exceptionnelle tout au long de la journée. Ce bien est parfait pour les citadins en quête d'un cadre de vie agréable, alliant confort et praticité. Le quartier, animé et vivant, témoigne d'une belle dive...",
  "price": 874517,
  "price_text": "874 517 €",
  "price_per_m2_text": "14 600 €/m²",
  "currency": "EUR",
  "area_m2": 59.9,
  "plot_area_m2": null,
  "rooms": 2,
  "bedrooms": 1,
  "attributes": [
    {
      "type": "numberOfRooms",
      "label": "pièces",
      "value": "2",
      "display_value": "2 pièces"
    },
    {
      "type": "numberOfBedrooms",
      "label": "chambre",
      "value": "1",
      "display_value": "1 chambre"
    },
    {
      "type": "livingSpace",
      "label": "m²",
      "value": "59,9",
      "display_value": "59,9 m²"
    },
    {
      "type": "numberOfFloors",
      "label": "étage",
      "value": "6ème",
      "display_value": "6ème étage"
    }
  ],
  "country": "France",
  "region": "Ile-de-France",
  "province": "Paris",
  "city": "Paris 14ème arrondissement",
  "district": "Raspail-Montparnasse",
  "zip_code": "75014",
  "is_address_published": false,
  "transport": [],
  "flags": {
    "is_new": true,
    "is_exclusive": false,
    "has_brokerage_fee": false,
    "has_3d_visit": false
  },
  "agency_id": "RC-094529",
  "agency_name": "Les-programmes-neufs.fr",
  "agency_type": "AGENCY",
  "is_private_owner": false,
  "agency_profile_url": "https://www.seloger.com/professionnels-immobilier/7K3VnAaNcRSyTcLYMus4nr",
  "agency_logo_url": "https://cdnihddipa.cloudimg.io/3/4/3/6/34369eaf-9ae5-40b4-872b-65555f13e09f.jpg?ci_seal=24096a56362abad0f0463457d0f445ad99978584",
  "agency_address": "9 RUE THEODULE RIBOT, 75017 PARIS 17",
  "agency_phone_numbers": [
    "+33(0)980807009"
  ],
  "agency_legal_information": [
    {
      "label": "Name",
      "value": "GB THEODULE"
    },
    {
      "label": "Siège",
      "value": "9 RUE THEODULE RIBOT, 75017 PARIS 17"
    },
    {
      "label": "RCS",
      "value": "842027872"
    },
    {
      "label": "SIRET",
      "value": "84202787200014"
    }
  ],
  "contact_name": null,
  "created_at": "2026-11-09T08:21:00Z",
  "updated_at": "2026-11-09T08:26:14.132Z",
  "image_count": 6,
  "images_by_category": {
    "l_i_v_i_n_g__r_o_o_m": 1,
    "t_e_r_r_a_c_e": 1,
    "h_a_l_l_w_a_y": 1,
    "b_e_d_r_o_o_m": 1,
    "b_a_t_h_r_o_o_m": 1,
    "l_o_g_o": 1
  },
  "images": [
    {
      "url": "https://cdnihddipa.cloudimg.io/5/f/2/0/5f20bac2-3382-474c-b22e-913084364714.jpg?ci_seal=f35c0674a436ff1ec64d5ca3485bd1fc1bcf4d90",
      "category": "LIVING_ROOM",
      "alt": "Appartement à vendre • neuf 874 517 € 2 pièces 1 chambre 59,9 m² 6ème étage Paris 14ème arrondissement 75014"
    },
    {
      "url": "https://cdnihddipa.cloudimg.io/4/c/9/f/4c9fd121-4869-4698-842d-f138e8ff0349.jpg?ci_seal=8530be16827b61b6d05b2f5386733c5665b0a5b3",
      "category": "TERRACE",
      "alt": null
    },
    {
      "url": "https://cdnihddipa.cloudimg.io/c/f/b/c/cfbc8426-ffee-4d6d-9c67-512b5a74ec7a.jpg?ci_seal=be3c9fee479dfb8c219358892a2b190900b10a1c",
      "category": "HALLWAY",
      "alt": null
    },
    {
      "url": "https://cdnihddipa.cloudimg.io/1/4/1/1/1411d8a3-a951-446b-a9b5-541d99f667ea.jpg?ci_seal=22197475853ee67a2f99d12e8d38359be88a94a7",
      "category": "BEDROOM",
      "alt": null
    },
    {
      "url": "https://cdnihddipa.cloudimg.io/d/c/6/b/dc6bdc14-ca36-4a65-937b-d2ceccefe465.jpg?ci_seal=403488f1b9d7aa79061a2108514e7232c3fe0639",
      "category": "BATHROOM",
      "alt": null
    },
    {
      "url": "https://cdnihddipa.cloudimg.io/f/6/2/7/f6273cc3-faa3-4a4c-9504-4cc21a2239e4.jpg?ci_seal=1e6ce7479851769a07e12dc1bfdaa15eae58b8f4",
      "category": "LOGO",
      "alt": null
    }
  ],
  "has_floorplans": null,
  "has_virtual_tour": null,
  "raw_data": null,
  "from_url": "https://www.seloger.com/classified-search?distributionTypes=Buy,Buy_Auction,Compulsory_Auction&estateTypes=House,Apartment&locations=AD08FR31096&page=2&order=DateDesc"
}

Using the Scraper: Step-by-Step Guide

Start by accessing the SeLoger.com Property Search Scraper through the Apify platform. If you're new to Apify, create a free account to access the scraper and manage your data collection runs.

Before configuring your scraper, spend time on SeLoger.com defining your search criteria. Use the platform's filters to narrow down properties by location, price range, property type, size, and features. This focused approach yields more relevant data and reduces processing time. Once you've refined your search, copy the URL from your browser—this URL contains all your filter parameters encoded.

Configure your input JSON with the collected search URLs. Set max_items_per_url based on your needs—use 20-50 for quick market samples, 100-200 for neighborhood analysis, or higher numbers for comprehensive regional studies. Enable ignore_url_failures for robustness when scraping multiple searches.

Launch your scraping run and monitor its progress through the Apify console. Processing time varies with the number of items requested, but typically 100 properties take 5-10 minutes to scrape. The console displays real-time progress, showing how many properties have been successfully extracted.

Once complete, review your dataset in the Apify interface. Check that properties match your expected criteria and that key fields like location and price are populated correctly. Download your data in JSON format for programmatic analysis, CSV for spreadsheet work, or Excel for easy sharing with non-technical stakeholders.

For recurring analysis, set up scheduled runs to automatically scrape your target searches daily or weekly. This automated approach builds time-series datasets that reveal market trends, price movements, and inventory changes. Scheduled runs are particularly valuable for tracking specific neighborhoods where you're considering investment or monitoring competitor listings.

When errors occur, consult the run log for details. Common issues include outdated search URLs (if SeLoger.com changes its URL structure) or temporary platform outages. The scraper includes retry logic for transient failures, but persistent errors may require updating your search URLs or adjusting proxy settings.

Practical Applications and Market Intelligence

The structured property data from SeLoger.com enables powerful analysis across numerous real estate applications. Property investors use the data to identify undervalued opportunities by comparing similar properties across neighborhoods, detecting listings priced below market averages. By tracking listing durations and price adjustments, investors gauge seller motivation and negotiation opportunities.

Real estate agencies leverage competitor analysis to optimize their own listings. By examining how competing properties are priced, described, and photographed, agencies improve their marketing strategies. The data reveals which features command price premiums, how description length affects engagement, and which presentation styles generate the most views and favorites.

Market researchers build comprehensive regional reports by aggregating thousands of listings. Analysis of price per square meter across districts identifies emerging neighborhoods before they become mainstream. Tracking new listing volumes reveals supply patterns, while monitoring sold properties indicates demand strength. This intelligence informs development projects, investment strategies, and market entry decisions.

PropTech applications integrate SeLoger.com data to enhance their platforms. Automated valuation models (AVMs) use the comprehensive property features and prices to estimate property values. Search platforms combine SeLoger.com data with other sources to offer users more complete market coverage. Price prediction models use historical listing data to forecast future property values.

For price benchmarking, the combination of hard facts and asking prices provides concrete market references. Real estate professionals compare their properties against recent comparable sales (comps) based on location, size, features, and condition. Buyers use the data to determine fair offers, while sellers set realistic asking prices that reflect current market conditions.

Urban planning and policy analysis benefit from understanding property market dynamics. Geographic distribution of property types, price gradients from city centers, and availability of affordable housing all inform planning decisions. Researchers analyze how infrastructure projects, zoning changes, or economic shifts impact local property markets.

Maximizing Data Value and Best Practices

To extract maximum insight from SeLoger.com data, implement systematic collection and analysis practices. Schedule regular scraping runs to build longitudinal datasets that reveal temporal patterns. Weekly scraping captures most market changes while avoiding excessive data redundancy. For fast-moving markets like Paris, daily scraping may be warranted.

Enrich your SeLoger.com data with complementary sources. Combine it with demographic data from INSEE (France's statistics office) to understand population characteristics of different neighborhoods. Integrate transport data to calculate commute times. Add school ratings, crime statistics, or amenity locations to build comprehensive neighborhood profiles that explain price variations.

Implement data quality validation in your analysis pipeline. Check that prices are within reasonable ranges, surface areas are positive, and coordinates fall within France. Identify and handle outliers—luxury properties or unique listings that might skew average calculations. Track missing fields to understand data completeness and adjust your analysis accordingly.

Store historical data systematically to enable trend analysis. Track individual properties through their lifecycle—initial listing, price adjustments, status changes, and final sale or withdrawal. This temporal perspective reveals market dynamics invisible in snapshot data, such as average time on market, proportion of properties that reduce prices, and seasonal demand patterns.

Respect the platform by implementing reasonable scraping rates. While the scraper handles technical aspects of polite data collection, avoid requesting excessive data unnecessarily. Focus your searches to capture relevant properties rather than scraping the entire SeLoger.com database. This sustainable approach ensures continued access to this valuable resource.

Consider the legal and ethical dimensions of property data usage. While publicly listed properties are generally fair game for market analysis, be thoughtful about republishing detailed listings or contacting property owners directly. When using the data commercially, ensure compliance with French data protection regulations and SeLoger.com's terms of service.

Conclusion

The SeLoger.com Property Search Scraper transforms France's leading property platform into a powerful source of structured market intelligence. Whether you're analyzing investment opportunities, conducting competitive research, building PropTech applications, or studying urban real estate dynamics, this tool provides the comprehensive, accurate data you need. Start leveraging French real estate data today and gain the market insights that drive informed property decisions.