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

Understanding SeLoger.com and Why This Data Matters

SeLoger.com stands as one of France's most prominent real estate platforms, serving millions of property seekers and thousands of real estate agencies across the country. Established as a trusted marketplace for buying, selling, and renting properties, SeLoger offers comprehensive listings that span from Parisian apartments to countryside villas, providing detailed information that goes far beyond basic property specs.

The platform's significance in the French real estate ecosystem cannot be overstated. It aggregates listings from professional agencies, individual sellers, and property developers, creating a comprehensive view of the market. Each listing contains rich data including energy performance certificates (DPE), detailed floor plans, neighborhood statistics, and pricing trends—information that is mandated by French real estate regulations and provides unparalleled transparency.

For real estate professionals, investors, market analysts, and property technology companies, accessing this structured data at scale opens numerous possibilities. However, manually collecting information from thousands of property listings would be practically impossible. The SeLoger.com Property Details Scraper transforms this challenge into an automated solution, delivering clean, structured data that's immediately ready for analysis, integration, or business intelligence applications.

What This Scraper Does and Who Benefits

The SeLoger.com Property Details Scraper is specifically designed to extract comprehensive information from individual property listing pages on SeLoger.com. Unlike simple data collection tools, this scraper captures the complete dataset that SeLoger provides for each property, including technical specifications, legal documents, energy certifications, multimedia assets, and seller contact information.

The scraper excels at handling the complex structure of French real estate listings, which include mandatory disclosures like energy performance ratings (DPE and GES), condominium charges, property tax information, and detailed location data. It preserves the hierarchical organization of property features, handles multiple image galleries, and captures both structured data fields and descriptive text content.

This tool serves diverse professional audiences effectively. Real estate agencies can monitor competitor pricing and market positioning across different neighborhoods. Property investors gain access to detailed analytics for identifying undervalued properties or emerging market trends. Market research firms can build comprehensive databases tracking pricing evolution, energy efficiency trends, and geographic distribution of property types. Property technology startups can integrate this data into valuation models, recommendation engines, or market intelligence platforms.

Understanding Input Requirements and Configuration

The scraper accepts property detail page URLs from SeLoger.com. These are the specific pages displaying complete information about individual properties, not search results or category pages.

Here's a practical example of properly formatted input:

{
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  },
  "urls": [
    "https://www.seloger.com/annonces/achat/appartement/paris-17eme-75/champerret-berthier/256305261.htm"
  ]
}

Example Screenshot:

Input Configuration Explained:

The proxy object is crucial for reliable data collection. SeLoger.com, like most major real estate platforms, implements bot detection mechanisms. Using residential proxies (RESIDENTIAL proxy group) makes your scraping activity appear as normal user behavior, significantly reducing the likelihood of being blocked or rate-limited.

The apifyProxyCountry parameter allows you to specify which country's proxy network to use. While "US" works in most cases, selecting "FR" (France) often provides faster response times and may yield better results when scraping French websites, as it appears more natural to the platform's systems.

The urls array accepts multiple property listing URLs, enabling batch scraping of dozens or hundreds of properties in a single run. Each URL should point directly to a property detail page, ensuring the scraper can access the complete dataset. You can collect these URLs manually by browsing SeLoger.com, or programmatically by first scraping search results pages.

Important considerations: Make sure URLs are complete and correctly formatted. Query parameters (the part after ?) are generally safe to include but not required. The scraper processes each URL sequentially, extracting all available data before moving to the next property.

Comprehensive Output Structure and Data Fields Explained

The scraper returns data in JSON format, with each property represented as a comprehensive object containing all available information organized into logical categories. Understanding these fields and their business applications is essential for maximizing data value.

Brand and Identification:

The brand field identifies the real estate agency or platform listing the property, useful for tracking which agencies are most active in specific markets or property types. The id provides a unique identifier for each listing, essential for deduplication, tracking price changes over time, or building relational databases that connect properties to other datasets.

Title and Metadata:

Title contains the property headline as it appears on the listing, typically including key features like property type, location, and size. This field is valuable for natural language processing and keyword analysis. Metadata captures structured information about the listing itself, such as publication date, last update timestamp, listing status, and view counts—data that helps assess listing freshness and market interest.

Location Information:

Location provides detailed geographic data including full address, postal code, city, district, and coordinates. French real estate is highly location-dependent, with prices varying dramatically between arrondissements in Paris or neighborhoods in other cities. This granular location data enables sophisticated geographic analysis, heat mapping of property values, and proximity calculations to amenities, transport, or schools.

Descriptions:

Description contains the main property description written by the seller or agent. Main_description typically focuses on the property's key selling points and layout. Area_description provides context about the neighborhood, local amenities, transport links, and area characteristics. Extended_info_description includes additional details about building history, recent renovations, or special features. These text fields are goldmines for sentiment analysis, feature extraction, and understanding how properties are marketed.

Hard Facts and Features:

Hard_facts contains quantifiable property characteristics: total surface area (in square meters), number of rooms (pièces), bedrooms, bathrooms, floor level, total building floors, and construction year. In French real estate, these metrics follow specific definitions—for example, "pièces" includes living rooms and bedrooms but excludes kitchens and bathrooms unless they meet certain size requirements.

Features array lists property amenities and characteristics such as balcony, terrace, parking spaces, cellar (cave), elevator, separate WC, equipped kitchen, fireplace, swimming pool, and security features. Each feature may include additional details like size or quantity. This structured data enables precise filtering and comparative analysis across properties.

Energy Performance:

Energy contains critical information about the property's energy efficiency, mandatory in French real estate since 2006. This includes the DPE (Diagnostic de Performance Énergétique) rating from A to G, indicating energy consumption, and the GES (Gaz à Effet de Serre) rating showing greenhouse gas emissions. These ratings significantly impact property value and buyer interest, as poor energy performance implies higher utility costs and upcoming renovation requirements due to evolving French regulations.

Pricing Information:

Price includes the asking price, currency, price per square meter, condominium charges (charges de copropriété), property tax (taxe foncière), and any price reductions or negotiation history. French property listings must disclose both the net seller price and total fees (FAI - Frais d'Agence Inclus). Price_comparison provides market context by showing average prices for similar properties in the area, helping buyers and analysts assess whether a listing is competitively priced.

Visual and Document Assets:

Gallery contains arrays of image URLs showcasing the property from multiple angles, including exterior shots, each room, common areas, and neighborhood views. Documents includes links to mandatory legal documents such as energy certificates, condominium regulations, asbestos reports, and property surveys. Enriched_media may contain virtual tours, 3D floor plans, or video walkthroughs—increasingly common in premium listings.

Financial Tools and Services:

Mortgage provides information about financing options, monthly payment calculators, and partner banks offering loans. This data reflects the financial accessibility of the property and typical buyer profiles. Partner_ad indicates if the listing is promoted through paid partnerships, affecting its visibility in search results.

Contact and Lead Generation:

Contact includes the seller or agency contact information, phone numbers, email addresses, and business hours. Seller_lead_link provides the URL for initiating contact or requesting additional information, valuable for understanding lead generation flows or building automated inquiry systems.

Market Intelligence:

Statistics aggregates market data for the property's location, including average prices per square meter, recent transaction volumes, typical time on market, and price evolution trends. This contextual data transforms individual listings into market intelligence, enabling comparative analysis and investment decision support.

Key Property Identifier:

Key serves as an internal reference code used by SeLoger's system, useful for API integration or cross-referencing with other SeLoger services.

Here's an example of how this data appears:

[
  {
  "brand": "seloger",
  "id": "258AA8631CJV",
  "title": null,
  "metadata": {
    "legacy_id": "256305261",
    "creation_date": "2025-12-11T16:07:00Z",
    "update_date": "2025-12-11T16:11:06.386Z",
    "status": {
      "status": true,
      "enrichments": {
        "contact_settings": false,
        "geo": false,
        "intermediary": false,
        "media": false,
        "online_id": false
      }
    },
    "is_new_build_project": false
  },
  "location": {
    "address": {
      "country": "FRA",
      "city": "Paris 17ème",
      "zip_code": "75017",
      "district": "Champerret-Berthier"
    },
    "is_address_published": true,
    "geometry": {
      "type": "Point",
      "coordinates": [
        2.29114,
        48.88388
      ]
    },
    "transport": {
      "closest_lines": [
        {
          "type": "METRO",
          "lines": [
            {
              "name": "3",
              "color": "#827a04"
            }
          ]
        },
        {
          "type": "BUS",
          "lines": [
            {
              "name": "43",
              "color": "#ed1b2a"
            },
            {
              "name": "84",
              "color": "#d282be"
            },
            {
              "name": "92",
              "color": "#ffbe02"
            },
            {
              "name": "93",
              "color": "#77c695"
            },
            {
              "name": "163",
              "color": "#dc9609"
            },
            {
              "name": "164",
              "color": "#a0006e"
            },
            {
              "name": "341",
              "color": "#ffbe02"
            }
          ]
        }
      ]
    }
  },
  "description": {
    "description": "Exclusivité. Rue Guersant. 3 pièces de 70,19 m² au 3ème étage avec ascenseur dans résidence récente de bon standing. Entrée, salon avec cuisine ouverte de 30 m², deux chambres, salle de bains, wc séparés. Cave et parking en sous-sol. Côté cour. A rafraîchir. Accès par la rue Guersant et par le square Bayen.",
    "texts": [
      {
        "text": "Exclusivité. Rue Guersant. 3 pièces de 70,19 m² au 3ème étage avec ascenseur dans résidence récente de bon standing. Entrée, salon avec cuisine ouverte de 30 m², deux chambres, salle de bains, wc séparés. Cave et parking en sous-sol. Côté cour. A rafraîchir. Accès par la rue Guersant et par le square Bayen."
      }
    ],
    "headline": "Square Bayen"
  },
  "hard_facts": null,
  "energy": {
    "features": [
      {
        "type": "yearOfConstruction",
        "label": "Année de construction",
        "value": "1977"
      },
      {
        "type": "state",
        "label": "État",
        "value": "Rénovation nécessaire"
      },
      {
        "type": "heatingSystem",
        "label": "Type de chauffage",
        "value": "Chauffage au sol"
      }
    ],
    "certificates": [
      {
        "key": "22abeae9-9e17-4a78-96de-74831ca4f0ab",
        "features": [
          {
            "type": "nameOfCertificate",
            "label": "Diagnostic réalisé",
            "value": "Après le 1er juillet 2021"
          }
        ],
        "scales": [
          {
            "key": "c55d23ea-dbaf-4318-93a2-fa87184b9147",
            "efficiency_class": {
              "index": 3,
              "rating": "D"
            },
            "values": [
              {
                "value": "217 kWh/m².an",
                "label": "Consommation (énergie primaire)"
              },
              {
                "value": "7 kg CO₂/m².an",
                "label": "Émissions"
              }
            ],
            "name": "Diagnostic de performance énergétique (DPE)",
            "segments": [
              {
                "label": "A",
                "value": ""
              },
              {
                "label": "B",
                "value": ""
              },
              {
                "label": "C",
                "value": ""
              },
              {
                "label": "D",
                "value": ""
              },
              {
                "label": "E",
                "value": ""
              },
              {
                "label": "F",
                "value": "Passoire énergétique"
              },
              {
                "label": "G",
                "value": "Passoire énergétique"
              }
            ],
            "type": "FR_ENERGY_AFTER_2021",
            "aria_label": "EfficiencyClass : D avec une plage allant de A à G .La consommation d'énergie est undefined kWhEP/m².an kilowattheures par mètre carré.",
            "display_unhappy_house_icon": false
          },
          {
            "key": "b77c81dd-28b0-46f4-af82-387c60c1bc22",
            "efficiency_class": {
              "index": 1,
              "rating": "B"
            },
            "values": [
              {
                "value": "7 kg CO₂/m².an",
                "label": "Émissions"
              }
            ],
            "name": "Indice d'émission de gaz à effet de serre (GES)",
            "segments": [
              {
                "label": "A",
                "value": ""
              },
              {
                "label": "B",
                "value": ""
              },
              {
                "label": "C",
                "value": ""
              },
              {
                "label": "D",
                "value": ""
              },
              {
                "label": "E",
                "value": ""
              },
              {
                "label": "F",
                "value": ""
              },
              {
                "label": "G",
                "value": ""
              }
            ],
            "type": "FR_GHG_AFTER_2021",
            "aria_label": "EfficiencyClass : B avec une plage allant de A à G .La consommation d'énergie est undefined kWhEP/m².an kilowattheures par mètre carré.",
            "display_unhappy_house_icon": false
          }
        ]
      }
    ],
    "has_scales": true
  },
  "key": {
    "keys": [
      {
        "label": "Identifiant",
        "value": "256305261"
      },
      {
        "label": "Référence annonce",
        "value": "86458781"
      }
    ]
  },
  "price": {
    "base": {
      "main": {
        "key": "82b661de-c1ac-4e56-8961-213ddc78627f",
        "label": {
          "main": "Prix du bien"
        },
        "value": {
          "main": {
            "value": "797 000 €",
            "aria_label": "797000 €"
          },
          "alt": {
            "value": "11 385,71 €/m²",
            "aria_label": "11385,71 euros par mètre carré"
          }
        }
      },
      "type": "SALE"
    },
    "components": [
      {
        "key": "441b180c-1905-495c-8d19-8417a73afb2b",
        "type": "PRIMARY",
        "units": [
          {
            "key": "65ab7615-596a-4306-8d94-7ecee49a21d5",
            "main": {
              "price": {
                "key": "34b1fe42-4ae5-49b0-82d7-6705c22629a0",
                "label": {
                  "main": "Prix du bien",
                  "alt": "honoraires inclus"
                },
                "value": {
                  "main": {
                    "value": "797 000 €",
                    "aria_label": "797000 €"
                  },
                  "alt": {
                    "value": "11 385,71 €/m²",
                    "aria_label": "11385,71 euros par mètre carré"
                  }
                },
                "highlighted": true
              },
              "message": {
                "type": "INFO",
                "value": "Les honoraires sont à la charge de l'acquéreur"
              }
            },
            "details": [
              {
                "key": "d576d353-2f4f-46f4-b7b5-0cd10f98665a",
                "label": "Inclus",
                "prices": [
                  {
                    "key": "61fdcf0d-abde-4f25-b58b-03525ccaadf6",
                    "label": {
                      "main": "Prix hors honoraires"
                    },
                    "value": {
                      "main": {
                        "value": "770 000 €",
                        "aria_label": "770000 €"
                      }
                    }
                  },
                  {
                    "key": "680224db-2fd5-4205-8c4f-f3aa19c5745f",
                    "label": {
                      "main": "Honoraires TTC à la charge de l'acquéreur (3,51% du prix du bien hors honoraires)"
                    },
                    "value": {
                      "main": {
                        "value": "27 000 €",
                        "aria_label": "27000 €"
                      }
                    }
                  }
                ]
              }
            ]
          },
          {
            "key": "dba7e584-69e5-406e-838f-8b7effc489bc",
            "main": {
              "price": {
                "key": "d124ff6c-8c5e-4d6b-b72c-490fb7f58519",
                "label": {
                  "main": "Frais de notaires estimés"
                },
                "value": {
                  "main": {
                    "value": "63 760 €",
                    "aria_label": "63760 €"
                  }
                },
                "info": {
                  "value": "Les frais de notaire représentent environ 8% du prix du bien dans l'ancien et 3% dans le neuf. Le montant estimé est donné à titre indicatif."
                }
              }
            }
          },
          {
            "key": "8419f9dd-63c5-4924-97b7-bb3dec3e9369",
            "main": {
              "price": {
                "key": "3ca5dd43-3730-42bf-bc9d-909e9b5b41b4",
                "label": {
                  "main": "Montant estimé du projet"
                },
                "value": {
                  "main": {
                    "value": "860 760 €",
                    "aria_label": "860760 €"
                  }
                },
                "highlighted": true
              }
            }
          }
        ]
      }
    ],
    "layout": "FRENCH_SALE",
    "breakdown": {
      "groups": [
        {
          "key": "c8ee4490-fee2-4651-a361-90e70f8fa9cc",
          "label": {
            "main": "Prix du bien",
            "alt": "honoraires inclus"
          },
          "value": {
            "main": {
              "value": "797 000 €",
              "aria_label": "797000 €"
            },
            "alt": {
              "value": "11 385,71 €/m²",
              "aria_label": "11385,71 euros par mètre carré"
            }
          },
          "color_type": "MAIN_PRICE",
          "highlighted": true,
          "items": [
            {
              "key": "6b26b197-5513-4786-85ff-1b58e5283c4a",
              "label": {
                "main": "Prix hors honoraires"
              },
              "value": {
                "main": {
                  "value": "770 000 €",
                  "aria_label": "770000 €"
                }
              },
              "highlighted": false
            },
            {
              "key": "aef13098-c012-4f43-b5c1-51c2b82b4d90",
              "label": {
                "main": "Honoraires TTC à la charge de l'acquéreur",
                "alt": "(3,51% du prix du bien hors honoraires)"
              },
              "value": {
                "main": {
                  "value": "27 000 €",
                  "aria_label": "27000 €"
                }
              },
              "highlighted": false
            }
          ]
        },
        {
          "key": "0227926f-4e09-49a8-a099-c21a545c10d7",
          "label": {
            "main": "Frais de notaire estimés (8%)"
          },
          "value": {
            "main": {
              "value": "63 760 €",
              "aria_label": "63760 €"
            }
          },
          "color_type": "NOTARY_FEE",
          "info_box": "Les frais de notaire représentent environ 8% du prix du bien dans l'ancien et 3% dans le neuf. Le montant estimé est donné à titre indicatif.",
          "highlighted": true
        }
      ],
      "total_project_costs": {
        "key": "ef88818e-78c0-4ab4-91de-7afd498f4ee8",
        "label": {
          "main": "Montant estimé du projet"
        },
        "value": {
          "main": {
            "value": "860 760 €",
            "aria_label": "860760 €"
          }
        }
      },
      "message": {
        "type": "INFO",
        "value": "Les honoraires sont à la charge de l'acquéreur"
      },
      "bar": [
        {
          "key": "c8ee4490-fee2-4651-a361-90e70f8fa9cc",
          "color_type": "MAIN_PRICE",
          "percentage": 0.9259
        },
        {
          "key": "0227926f-4e09-49a8-a099-c21a545c10d7",
          "color_type": "NOTARY_FEE",
          "percentage": 0.0741
        }
      ]
    }
  },
  "features": {
    "preview": [
      {
        "icon": "floors",
        "value": "3ème étage"
      },
      {
        "icon": "elevator",
        "value": "Ascenseur"
      },
      {
        "value": "Cave",
        "icon": "cellar"
      },
      {
        "icon": "parking-lots",
        "value": "Parking"
      },
      {
        "icon": "toilet-amenities",
        "value": "1 WC"
      },
      {
        "icon": "balcony",
        "value": "Pas de balcon"
      },
      {
        "icon": "Orientation",
        "value": "Exposition: nord, ouest"
      },
      {
        "value": "Sans vis-à-vis",
        "icon": "with-view"
      }
    ],
    "details": {
      "categories": [
        {
          "elements": [
            {
              "icon": "Orientation",
              "value": "Exposition: nord, ouest"
            },
            {
              "icon": "furnished",
              "value": "Non meublé"
            },
            {
              "icon": "floors",
              "value": "3ème étage"
            }
          ],
          "title": "Informations générales"
        },
        {
          "elements": [
            {
              "icon": "barrier-free",
              "value": "Non accessible aux personnes à mobilité réduite"
            },
            {
              "icon": "elevator",
              "value": "Ascenseur"
            }
          ],
          "title": "Accessibilité"
        },
        {
          "elements": [
            {
              "icon": "bathroom-amenities",
              "value": "1 salle de bain"
            },
            {
              "icon": "toilet-amenities",
              "value": "1 WC"
            },
            {
              "icon": "bedroom",
              "value": "2 chambres"
            },
            {
              "value": "Cave",
              "icon": "cellar"
            },
            {
              "icon": "separateEntrance",
              "value": "Entrée séparée"
            }
          ],
          "title": "Intérieur"
        },
        {
          "elements": [
            {
              "icon": "balcony",
              "value": "Pas de balcon"
            },
            {
              "value": "Sans vis-à-vis",
              "icon": "with-view"
            },
            {
              "icon": "parking-lots",
              "value": "Parking"
            }
          ],
          "title": "Extérieur"
        },
        {
          "elements": [
            {
              "icon": "intercom",
              "value": "Interphone"
            },
            {
              "value": "Digicode",
              "icon": "digital-lock"
            }
          ],
          "title": "Sécurité et services"
        }
      ]
    }
  },
  "gallery": {
    "images": [
      {
        "key": "a29fd766-972c-4f43-bcc6-da63de691ba9",
        "url": "https://mms.seloger.com/a/2/9/f/a29fd766-972c-4f43-bcc6-da63de691ba9.jpg?ci_seal=70cd8b1697acdb7e7a230ea2e239cada1accd691",
        "alt": "Appartement à vendre 797 000 € 3 pièces 2 chambres 70 m² 3ème étage Champerret-Berthier Paris 17ème 75017",
        "classification": {
          "name": "KITCHEN",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "b262aa75-ea7c-408f-9bef-fda22571bb58",
        "url": "https://mms.seloger.com/b/2/6/2/b262aa75-ea7c-408f-9bef-fda22571bb58.jpg?ci_seal=612267bc9ec90111e57b1adfe7f50a3cb21aa057",
        "classification": {
          "name": "KITCHEN",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "a4f271d9-320b-4924-94b0-61de890b55b9",
        "url": "https://mms.seloger.com/a/4/f/2/a4f271d9-320b-4924-94b0-61de890b55b9.jpg?ci_seal=99ac5b3e369c3e6ab2b77f2f5dce5cee5206a17f",
        "classification": {
          "name": "COURTYARD",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "f26fa22a-d5f3-40c0-87e0-3e611d6eddf4",
        "url": "https://mms.seloger.com/f/2/6/f/f26fa22a-d5f3-40c0-87e0-3e611d6eddf4.jpg?ci_seal=9fbeabdb26b84031fbab52634d156a357d02f2c4",
        "classification": {
          "name": "EMPTY_ROOM",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "281b4cea-775d-40d5-99fb-3aeab4d8f4f2",
        "url": "https://mms.seloger.com/2/8/1/b/281b4cea-775d-40d5-99fb-3aeab4d8f4f2.jpg?ci_seal=38c804817d0922492e18326eddeb6a724a798ee2",
        "classification": {
          "name": "EMPTY_ROOM",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "cbd1c61d-ad02-4ca4-b2e7-b65b41063ee5",
        "url": "https://mms.seloger.com/c/b/d/1/cbd1c61d-ad02-4ca4-b2e7-b65b41063ee5.jpg?ci_seal=987732cce23e498d7900e35726dc2204564a6c73",
        "classification": {
          "name": "HALLWAY",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "11c044cc-eb3b-45e9-96d3-0026bdfd91ba",
        "url": "https://mms.seloger.com/1/1/c/0/11c044cc-eb3b-45e9-96d3-0026bdfd91ba.jpg?ci_seal=dff48de4b49b1e7782e35bd1f5af26bcfba5939e",
        "classification": {
          "name": "KITCHEN",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "b2322968-9272-43e2-82af-2158bd09d84b",
        "url": "https://mms.seloger.com/b/2/3/2/b2322968-9272-43e2-82af-2158bd09d84b.jpg?ci_seal=7b662d05d332b18cda8b437c59d1bb2bfe89c936",
        "classification": {
          "name": "BATHROOM",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "0594e308-1088-468f-9dc4-dccf88a2733a",
        "url": "https://mms.seloger.com/0/5/9/4/0594e308-1088-468f-9dc4-dccf88a2733a.jpg?ci_seal=ee2d8b4dadffb90eac4b52191ba793ffb9fd984f",
        "classification": {
          "name": "BATHROOM",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "c812673e-8696-44ab-adcc-01c0e67b09a6",
        "url": "https://mms.seloger.com/c/8/1/2/c812673e-8696-44ab-adcc-01c0e67b09a6.jpg?ci_seal=26c8e8b5e5551890c994bba0a2850d255a97b82a",
        "classification": {
          "name": "COURTYARD",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "dc190822-5fee-4cef-899a-aafa3c77ec01",
        "url": "https://mms.seloger.com/d/c/1/9/dc190822-5fee-4cef-899a-aafa3c77ec01.jpg?ci_seal=4e4283e413a2d33f1cd6280d8736ea074eebbb80",
        "classification": {
          "name": "HALLWAY",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "9ae0ca79-b67a-4119-846c-0a2516925a10",
        "url": "https://mms.seloger.com/9/a/e/0/9ae0ca79-b67a-4119-846c-0a2516925a10.jpg?ci_seal=ffbdc286f5e5d902d2d8b3d2b0e3356338a9dc93",
        "classification": {
          "name": "EMPTY_ROOM",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "7d8d5cdf-ffc6-4b4f-b958-da95941c55f2",
        "url": "https://mms.seloger.com/7/d/8/d/7d8d5cdf-ffc6-4b4f-b958-da95941c55f2.jpg?ci_seal=5feb9e4e2a8c3b75acd38c0c14eebe4fb7360f9a",
        "classification": {
          "name": "EMPTY_ROOM",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "89d5cc5c-4e15-4873-862b-41687dc13b70",
        "url": "https://mms.seloger.com/8/9/d/5/89d5cc5c-4e15-4873-862b-41687dc13b70.jpg?ci_seal=87d3298dd6f0170180cad51f633f67b1837a2a2d",
        "classification": {
          "name": "EMPTY_ROOM",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      },
      {
        "key": "1b62bd8a-e8b1-4e35-b6c2-53dce7351091",
        "url": "https://mms.seloger.com/1/b/6/2/1b62bd8a-e8b1-4e35-b6c2-53dce7351091.jpg?ci_seal=67bfe3d23975823a7ba4da8b77cdb14fd4bbad5f",
        "classification": {
          "name": "EMPTY_ROOM",
          "version": "scene-classification-sagemaker-endpoint-live-1-3-10"
        }
      }
    ]
  },
  "documents": {
    "display": false,
    "files": []
  },
  "enriched_media": null,
  "mortgage": {
    "brand": "seloger",
    "id": "256305261",
    "federal_state_geo_id": "AD04FR5",
    "zip": "75017",
    "city": "Paris 17ème",
    "country": "FRA",
    "sub_type": "RESALE",
    "region": "Ile-de-France",
    "show_rent_label": false,
    "show_monthly_rate_label": true,
    "price": 797000,
    "prov": 3.51,
    "monthly_amount": 4185,
    "formatted_monthly_amount": "4 185"
  },
  "partner_ad": null,
  "seller_lead_link": null,
  "price_comparison": null,
  "main_description": null,
  "area_description": null,
  "extended_info_description": null,
  "statistics": {
    "published": "50 minutes en ligne",
    "views": "0 vue",
    "saves": "0 favori"
  },
  "contact": {
    "id": "258AA8631CJV",
    "legacy_id": "256305261",
    "brand": "seloger",
    "agency_id": "RC-015274",
    "static": {
      "phone_numbers": [
        "0603400729"
      ]
    },
    "sticky": {
      "phone_numbers": [
        "0603400729"
      ]
    },
    "contact_card": {
      "title": "AGENCE PEREIRE",
      "subtitle": "Agence professionnelle",
      "phone_numbers": [
        "0603400729"
      ],
      "is_private_owner": false,
      "agency_logo": {
        "logo_url": "https://mms.seloger.com/b/e/8/9/be893a73-f18d-4097-927d-e51de2102197.jpg?ci_seal=6404983378031c008dc471963e3bbde5b82fbd0a",
        "display": true
      },
      "contact_logo": {
        "logo_url": null,
        "display": false
      }
    },
    "contact_form": {
      "contact_card": {
        "title": "AGENCE PEREIRE",
        "subtitle": "Agence professionnelle",
        "phone_numbers": [
          "0603400729"
        ],
        "is_private_owner": false,
        "logo_url": "https://mms.seloger.com/b/e/8/9/be893a73-f18d-4097-927d-e51de2102197.jpg?ci_seal=6404983378031c008dc471963e3bbde5b82fbd0a"
      },
      "display_owner_flag": true,
      "subject_label": "Mon message",
      "should_send_lead_value": true
    },
    "mobile_phones": {
      "title": "AGENCE PEREIRE",
      "subtitle": "Agence professionnelle",
      "phone_numbers": [
        "0603400729"
      ],
      "logo_url": "https://mms.seloger.com/b/e/8/9/be893a73-f18d-4097-927d-e51de2102197.jpg?ci_seal=6404983378031c008dc471963e3bbde5b82fbd0a",
      "is_private_owner": false
    },
    "provider": {
      "intermediary_card": {
        "title": "AGENCE PEREIRE",
        "subtitle": "Agence professionnelle",
        "display": true,
        "logo_url": "https://mms.seloger.com/b/e/8/9/be893a73-f18d-4097-927d-e51de2102197.jpg?ci_seal=6404983378031c008dc471963e3bbde5b82fbd0a",
        "logo_href": "https://www.seloger.com/professionnels/agences-immobilieres/paris-17eme-arrondissement-75017/agence-87373/"
      },
      "contact_card": {
        "title": null,
        "subtitle": "Votre contact",
        "display": false,
        "logo_url": null
      },
      "website": "http://www.agencepereire.com/",
      "is_private_owner": false,
      "profile_url": "https://www.seloger.com/professionnels/agences-immobilieres/paris-17eme-arrondissement-75017/agence-87373/",
      "imprint_url": null,
      "fee_url": "https://www.agencepereire.com:443/segments/immo/catalog/images/manufacturers_bareme/253924.pdf",
      "agency_legal_informations": [
        "Société à responsabilité limitée (sans autre indication) FGD IMMOBILIER",
        "<b>Siège:</b> 217 Boulevard Pereire, 75017 Paris",
        "<b>RCS:</b> 418573119",
        "<b>SIRET:</b> 41857311900017"
      ],
      "publisher_type": "AGENCY",
      "display_links": true,
      "address": "217 boulevard Pereire, 75017 Paris",
      "phone_numbers": [
        "0603400729"
      ]
    },
    "confirmation_page": {
      "is_finance_offer_button_enabled": false
    }
  }
}
]

Step-by-Step Guide to Using the Scraper

Begin by setting up your Apify account if you haven't already. Navigate to the SeLoger.com Property Details Scraper in the Apify Store. Before initiating your first scrape, identify the specific properties you want to extract data from. You can browse SeLoger.com using their search filters (location, price range, property type) to find relevant listings, then copy the URLs of individual property detail pages.

Prepare your input JSON with the collected URLs and configure proxy settings appropriately. For scraping French real estate data, residential proxies provide the most reliable results. If you're collecting data for a specific region, consider setting the proxy country to France for optimal performance and reduced latency.

When scraping large numbers of properties, organize your URLs strategically. Group them by location, property type, or price range to make the resulting dataset easier to analyze. Consider running test scrapes with small batches (10-20 URLs) first to verify output quality and identify any potential issues before processing hundreds of listings.

Launch the scraper through the Apify console and monitor the execution in real-time. Processing time varies based on the number of URLs and current platform load, but typically handles 30-50 property listings within 10-15 minutes. The console provides detailed logs showing which URLs are being processed and any errors encountered.

Once the scrape completes, review the results in the dataset preview to ensure data quality and completeness. Check that critical fields like price, location, and property specifications are populated correctly. Download your data in the format that best suits your needs: JSON for programmatic processing and database imports, CSV for spreadsheet analysis, or Excel for sharing with non-technical stakeholders.

For ongoing market monitoring, set up scheduled runs to automatically scrape new listings daily or weekly. This creates a time-series dataset that reveals pricing trends, inventory changes, and market dynamics over time. The scheduler can be configured to run during off-peak hours to ensure optimal performance.

When troubleshooting issues, check the activity log for specific error messages. Common problems include incorrectly formatted URLs (ensure they point to property detail pages, not search results), expired listings (properties that have been sold or removed), or temporary platform unavailability. The scraper includes retry logic for transient failures, but persistent errors may require URL verification or proxy configuration adjustment.

Practical Applications and Business Value

The comprehensive nature of this dataset enables powerful applications across real estate and property technology sectors. Real estate agencies can conduct competitive intelligence by monitoring competitor listings, pricing strategies, and market positioning. By tracking how quickly properties sell at different price points, agencies optimize their own pricing recommendations and identify market sweet spots.

Property investors leverage this data for deal sourcing and valuation modeling. By analyzing price per square meter across neighborhoods, comparing energy ratings with asking prices, and tracking listing duration, investors identify undervalued properties or emerging investment opportunities. The energy performance data is particularly valuable in France, where upcoming regulations will require minimum DPE ratings, potentially forcing price adjustments on poorly-rated properties.

Market research firms build comprehensive databases tracking French real estate trends. Time-series analysis of property prices, inventory levels, and feature preferences reveals seasonal patterns, demographic shifts, and regional development impacts. The detailed location data enables micro-market analysis, identifying specific streets or districts experiencing rapid appreciation or declining interest.

Property technology companies integrate this data into valuation algorithms, recommendation engines, and market prediction models. Machine learning models trained on historical SeLoger data can predict property values, estimate time to sale, or suggest optimal listing prices. The rich feature set and mandatory energy ratings provide excellent training data for property classification and automated valuation models.

Urban planners and policy researchers utilize aggregated data to understand housing stock characteristics, energy efficiency distribution, and affordability patterns across regions. The mandatory energy ratings provide unique insights into building stock quality and renovation needs, informing policy decisions about energy transition and housing improvement programs.

Financial institutions use property data for risk assessment, market sizing, and product development. Understanding the distribution of property values, typical financing needs, and geographic concentration helps banks optimize mortgage products and assess portfolio exposure.

Maximizing Value and Ensuring Sustainable Use

To extract maximum value from this scraper, establish a systematic data collection strategy rather than ad-hoc scraping. The French real estate market exhibits strong seasonal patterns, with activity peaking in spring and fall. Regular weekly scraping captures these dynamics and builds a rich historical database for trend analysis.

Implement data enrichment processes that combine SeLoger data with additional sources. Cross-reference properties with government databases like DVF (Demandes de Valeurs Foncières) that publish actual transaction prices, revealing the gap between asking prices and sold prices. Integrate with geographic databases to add proximity data for schools, metro stations, parks, and amenities that influence property values.

Establish robust data quality checks in your processing pipeline. Verify that mandatory fields like energy ratings and property size are present, as their absence may indicate scraping errors or incomplete listings. Validate price ranges against known market values to catch anomalies. Check coordinate accuracy by confirming that latitude/longitude positions fall within the stated city or district.

Store historical data systematically to enable longitudinal analysis. Track individual listings over time to monitor price changes, status updates, and time on market. This temporal dimension reveals seller behavior, market liquidity, and pricing strategy effectiveness. Properties that remain listed for extended periods with multiple price reductions indicate overpricing or market weakness.

Respect the platform and French data protection regulations by implementing reasonable usage patterns. Avoid excessive concurrent requests that could strain SeLoger's infrastructure. Be aware that French real estate data may be subject to GDPR considerations, particularly regarding seller contact information. Use the data responsibly and ensure compliance with applicable regulations.

Consider geographic segmentation in your scraping strategy. The French real estate market varies dramatically between Paris, major metropolitan areas, and rural regions. Tailor your data collection to focus on markets relevant to your business objectives, whether that's luxury Parisian apartments, coastal vacation properties, or countryside homes.

Develop alerting systems that notify you when properties matching specific criteria appear or when significant market changes occur. For example, alert on luxury properties below market average, newly listed properties in target neighborhoods, or unusual pricing patterns that might indicate distressed sales or exceptional opportunities.

Conclusion

The SeLoger.com Property Details Scraper transforms France's leading real estate platform into a structured, analyzable dataset that powers informed decision-making across the property sector. Whether you're conducting market research, sourcing investment opportunities, developing proptech solutions, or analyzing market trends, this tool provides the comprehensive, accurate data you need to succeed in the dynamic French real estate market. Start extracting insights today and gain the competitive advantage that data-driven intelligence provides.