We extract authenticated luxury listings, dynamic pricing, condition reports, and brand taxonomy from The RealReal. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake 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 Active Listings objects from therealreal.com. All fields typed and schema-versioned.
"listing_id": "TRR1948291", "brand": "Chanel", "title": "Vintage Classic Double Flap Bag", "category": "Women", "sub_category": "Handbags", "price": 6500.0, "condition": "Very Good", "authentication_status": "Authenticated", "size": "Medium"
| # | listing_id | brand | title | category | sub_category | price |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing & Discounts objects from therealreal.com. All fields typed and schema-versioned.
"listing_id": "TRR1948291", "current_price": 6500.0, "trr_estimated_retail": 8800.0, "discount_pct": 26, "final_sale": false, "coupon_eligible": true, "currency": "USD"
| # | listing_id | current_price | original_retail_price | trr_estimated_retail | discount_pct | price_drop_history |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Condition & Measurements objects from therealreal.com. All fields typed and schema-versioned.
"listing_id": "TRR1948291", "condition_grade": "Very Good", "condition_notes": "Faint scratches at hardware; minor creasing at exterior.", "measurements": "Shoulder Strap Drop: 9.5", Height: 6", Width: 10", Depth: 2.5"", "signs_of_wear": true, "fabric_content": "Lambskin Leather"
| # | listing_id | condition_grade | condition_notes | measurements | fit_notes | signs_of_wear |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Sold Inventory objects from therealreal.com. All fields typed and schema-versioned.
"listing_id": "TRR1837261", "brand": "Rolex", "title": "Submariner Date Watch", "sold_price": 12500.0, "listed_price": 13000.0, "days_on_market": 14, "sold_date": "2026-05-10T14:30:00Z", "condition": "Excellent"
| # | listing_id | brand | title | sold_price | listed_price | days_on_market |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Brand & Designer Data objects from therealreal.com. All fields typed and schema-versioned.
"designer_id": "DES0042", "designer_name": "Hermès", "average_price_point": 4200.0, "active_listing_count": 3412, "sold_listing_count": 18291, "top_selling_categories": "['Handbags', 'Accessories']", "trend_score": 94
| # | designer_id | designer_name | category_distribution | average_price_point | active_listing_count | sold_listing_count |
|---|---|---|---|---|---|---|
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Our scraper handles every layer of the luxury consignment platform: authenticated listings, dynamic markdown pricing, granular condition reports, and sold inventory tracking, with full anti-bot circumvention built in.
Title, brand, description, measurements, condition grades, and every metadata field The RealReal surfaces, scraped at the individual item level.
Extract precise condition grades, specific wear notes, and authentication guarantees critical for secondary market valuation.
Capture current price, estimated retail value, discount percentages, and final sale tags, timestamped per crawl.
Track items transitioning from active to sold state to calculate days on market and definitive clearing prices.
Extract the complete hierarchy of luxury designers, sub-brands, and collaborations across all apparel and accessory categories.
Capture waitlist counts and user interest metrics per item to gauge market demand for specific luxury pieces.
Structured extraction of garment measurements, sizing conversions, and fit notes normalised across categories.
Extract unwatermarked, high-resolution image URLs suitable for computer vision and authentication AI training.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences with change-detection diffing.
Brief in. Clean data out.
Provide designer names, category URLs, or specific item criteria. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and Datadome bypass for therealreal.com.
Schema validation, null-rate checks, price-outlier detection, and sample item reviews before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
The RealReal employs aggressive scraping detection to protect its proprietary pricing data. Here is how we stay resilient.
The RealReal uses advanced bot protection heuristics. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass Datadome blocks.
Category pages rely on complex JavaScript for infinite scrolling and dynamic image hydration. We run full Playwright browser sessions to trigger lazy-loads and capture complete product grids.
Measurement and specification tables differ wildly between watches, handbags, and apparel. Our extraction logic normalises these disparate DOM structures into a clean, unified schema.
For large designer catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, capturing price drops and sold status changes without full catalogue re-dumps.
Every run emits structured logs to our observability stack. We alert on null-rate spikes in critical fields like condition grades and respond before downstream systems are affected.
Secondary market platforms monitor clearing prices and markdowns to optimise their own consignment algorithms.
Fashion analysts track brand velocity, sell-through rates, and category demand to predict upcoming luxury trends.
Machine learning teams use high-resolution images and detailed condition notes to train computer vision models for luxury authentication.
Sustainability analysts track the lifecycle and depreciation curves of luxury goods across different designer tiers.
Other consignment and resale platforms track inventory overlap, discount cadences, and time-to-sale metrics.
Alternative asset funds appraise watches, handbags, and fine jewellery based on real-time secondary market pricing data.
"The RealReal holds the most comprehensive dataset of authenticated secondary market luxury pricing, but extracting it requires bypassing aggressive bot mitigation."
Most teams underestimate the investment required: reliable luxury consignment scraping requires residential proxies, full JavaScript rendering for infinite scroll, and daily selector maintenance for complex measurement tables. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our therealreal.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About therealreal.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law, reinforced by the hiQ v. LinkedIn ruling. DataFlirt targets only public product, pricing, and condition data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for block rate spikes in real time and trigger pool rotation automatically.
Yes. We track listing state changes from active to sold, allowing us to calculate exact days on market and capture the final clearing price before the listing is removed from public search.
The RealReal uses different specification tables for watches, handbags, and apparel. Our extraction logic normalises these disparate DOM structures into a clean, unified schema for easy database ingestion.
Yes, we capture the overall condition grade as well as the specific wear notes, alterations, and authenticity guarantees provided by their internal experts.
Pipelines can run at hourly cadences to catch flash sales and markdowns. Full catalogue refreshes typically complete within a 12-hour window depending on the requested category scope.
Yes. We provide a sample run of up to 500 listings as part of the pre-engagement scoping process so you can validate schema fit and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off designer catalogue dump or a continuous price-monitoring feed across 100K listings, we scope, build, and operate the pipeline. Tell us what you need.
