We extract residential and commercial listings, price history, agency details, and geospatial data from Avito. Delivered as clean JSON, CSV, or Parquet to S3 or ClickHouse on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Property Listings objects from avito.ru. All fields typed and schema-versioned.
"listing_id": "2849103847", "title": "2-к. квартира, 64 м², 7/14 эт.", "price": 14500000.0, "area_total": 64.0, "floor": 7, "rooms": 2, "published_at": "2026-05-12T08:14:00Z"
| # | listing_id | url | title | property_type | deal_type | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Location & Geo objects from avito.ru. All fields typed and schema-versioned.
"listing_id": "2849103847", "city": "Moscow", "district": "Danilovsky", "street": "Avtozavodskaya ulitsa", "geo_lat": 55.7042, "geo_lon": 37.6481, "nearest_metro": "Avtozavodskaya", "metro_distance_min": 5
| # | listing_id | region | city | district | street | house_number |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seller & Agency objects from avito.ru. All fields typed and schema-versioned.
"seller_id": "84729103", "seller_name": "Alexander", "seller_type": "agency", "agency_name": "Samolet Plus", "rating": 4.8, "phone_number": "+79991234567", "is_verified": true
| # | seller_id | seller_name | seller_type | agency_name | profile_url | joined_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Building Specs objects from avito.ru. All fields typed and schema-versioned.
"listing_id": "2849103847", "building_type": "Monolithic", "year_built": 2018, "ceiling_height": 2.9, "parking_type": "Underground", "elevator_passenger": 2, "heating_type": "Central"
| # | listing_id | building_type | year_built | ceiling_height | parking_type | elevator_passenger |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search & SERP objects from avito.ru. All fields typed and schema-versioned.
"keyword": "1 bedroom apartment", "geo_filter": "Moscow", "position": 3, "listing_id": "2849103847", "is_promoted": true, "promotion_type": "xl_promo", "price": 14500000.0
| # | keyword | category_filter | geo_filter | position | listing_id | is_promoted |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Avito scraper navigates Qrator anti-bot protection, dynamic pagination, and regional proxy requirements to extract complete property and seller datasets reliably.
Extract area, floor, year built, ceiling height, and all granular specs Avito surfaces for residential and commercial listings.
Capture current price, price per square meter, and historical price adjustments visible on the listing page.
Retrieve precise latitude and longitude coordinates, nearest metro stations, and calculated walking times.
Automate the network interactions required to reveal and parse seller contact numbers from image or API payloads.
Filter out brokers and track agency inventory by extracting seller type flags and verified agency names.
Extract structural details including panel vs brick construction, parking availability, and elevator counts.
Identify paid, VIP, and highlighted listings to understand competitor advertising spend and visibility.
Target Moscow, St. Petersburg, and all federal subjects using localized RU proxy pools to bypass geo-restrictions.
Track delisting events, price drops, and new inventory in real time with hash-based change detection.
Brief in. Clean data out.
Provide target regions, property types, or seller profiles. We map the extraction schema together.
We configure Scrapy crawlers, RU residential proxies, and Qrator bypass logic for avito.ru.
Schema validation, missing value checks, and geo-coordinate verification before production launch.
JSON, CSV, or Parquet pushed to your S3 bucket, ClickHouse, or Postgres instance on schedule.
Avito employs aggressive rate limiting and bot mitigation. We handle the network complexity so you receive clean data.
Avito uses Qrator for DDoS and bot mitigation. Our infrastructure mimics legitimate TLS fingerprints and solves JavaScript challenges natively to maintain high success rates.
Avito aggressively geo-blocks non-CIS IPs. We route all requests through premium Russian residential proxy pools to maintain access and avoid immediate CAPTCHAs.
Contact numbers are masked as images or require API triggers. We execute the required XHR requests and run payload parsing to extract raw digits reliably.
Avito frequently alters its DOM structure. We extract data directly from embedded Next.js state objects, ensuring schema stability even during frontend redesigns.
Search results cap at 100 pages. We use geographic grid-search and micro-filtering to extract deep catalogue inventory without hitting pagination walls.
Train automated valuation models (AVMs) using historical price per square meter and location features.
Identify undervalued properties, distressed sales, and high-yield rental opportunities across regions.
Track competitor listing volume, time-on-market, and price reduction strategies.
Analyze housing density, development trends, and infrastructure proximity metrics.
Extract private seller phone numbers for direct outreach and brokerage acquisition.
Measure average days-on-market and listing velocity by district and property class.
"Avito holds the definitive pulse of the Russian real estate market, but extracting it requires navigating aggressive geo-blocking and anti-bot systems."
Building an in-house Avito crawler means fighting Qrator blocks, managing RU proxy pools, and handling constant DOM changes. DataFlirt abstracts this entirely. We deliver clean, normalised property records directly to your warehouse, allowing your analysts to focus on market trends rather than infrastructure maintenance.
Everything supported by our avito.ru scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Instead of fragile DOM parsing, we target Avito's internal JSON hydration state, ensuring schema stability even when CSS classes change.
We route traffic through RU-based residential IPs using custom TLS profiles that match local mobile and desktop browser signatures.
Pipelines run on Kubernetes clusters, pushing normalised Parquet files directly to S3 or ClickHouse for immediate analytical querying.
Data delivered to where your team already works — no new tooling required.
About avito.ru scraping, legality, and pipeline operations.
Ask us directly →Yes. We trigger the necessary network requests to reveal and parse phone numbers. This operates at a lower concurrency to respect rate limits and avoid account flags.
Avito is strictly focused on the Russian market. We use localized RU residential proxies to ensure reliable access to all regional subdomains without triggering geo-blocks.
We programmatically divide large regions into smaller geographic bounding boxes or apply granular price and area filters to extract the entire inventory sequentially.
Yes. The extracted data includes seller type flags, allowing you to filter out brokers and target direct owners exclusively.
For targeted regions or specific search filters, we configure pipelines to poll at sub-hourly intervals, delivering new listings via Webhook immediately.
We capture data from the moment the pipeline is active. We also extract the publication date and visible price history present on active listings.
Yes. The pipeline supports all Avito Nedvizhimost sub-categories, including commercial, land, short-term rentals, and new developments.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop fighting proxies and rate limits. Define your target regions and property types, and let DataFlirt stream structured records to your warehouse.
