We extract product catalogues, CMR pricing tiers, seller intelligence, and stock depth from Falabella. Delivered as clean JSON, CSV, or Parquet to your warehouse.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Product Listings objects from falabella.com. All fields typed and schema-versioned.
"sku": "12345678", "title": "Zapatillas Urbanas Hombre", "brand": "Nike", "regular_price": 69990.0, "cmr_price": 59990.0, "in_stock": true, "is_falabella_retail": true
| # | sku | title | brand | category | sub_category | regular_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promotions objects from falabella.com. All fields typed and schema-versioned.
"sku": "12345678", "base_price": 69990.0, "internet_price": 64990.0, "cmr_price": 59990.0, "discount_pct": 14, "promotion_tag": "Cyber Monday", "currency": "CLP"
| # | sku | base_price | internet_price | cmr_price | discount_abs | discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seller & Marketplace objects from falabella.com. All fields typed and schema-versioned.
"seller_id": "S-9821", "seller_name": "Deportes Sparta", "seller_rating": 4.6, "fulfillment_type": "Falabella Delivery", "official_store": true, "total_products": 1450, "dispatch_time": "48 hours"
| # | seller_id | seller_name | seller_rating | fulfillment_type | dispatch_time | return_policy |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from falabella.com. All fields typed and schema-versioned.
"review_id": "REV-48291", "sku": "12345678", "rating": 5, "review_date": "2023-10-14", "verified_buyer": true, "recommended": true, "helpful_votes": 12
| # | review_id | sku | rating | reviewer_name | review_date | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search & Category objects from falabella.com. All fields typed and schema-versioned.
"keyword": "zapatillas", "position": 3, "sku": "12345678", "brand": "Nike", "current_price": 59990.0, "is_sponsored": false, "scraped_at": "2023-11-01T10:00:00Z"
| # | keyword | category_path | position | sku | title | brand |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Falabella scraper handles the complexities of LATAM's largest retailer: multi-tier pricing, third-party sellers, dynamic React payloads, and variant stock matrices.
Capture titles, descriptions, specifications, size charts, and high-resolution image URLs across all fashion and home categories.
Monitor multi-tiered pricing including regular prices, internet prices, and exclusive CMR cardholder discounts.
Track third-party sellers, fulfillment methods, seller ratings, and official store designations across the Falabella network.
Extract exact stock availability per size and colour variant, mapping parent-child SKU relationships accurately.
Scrape data across falabella.com, falabella.com.co, and falabella.com.pe using a unified normalisation schema.
Capture flash sales, Cyber Monday tags, and bank-specific promotional banners applied to individual SKUs.
Extract customer sentiment, star ratings, and verified purchase text to analyse product performance.
Monitor organic and sponsored product placements for specific keywords within Falabella search results.
Detect out-of-stock events and restocks at the variant level with high-frequency polling.
Extract estimated delivery windows, click-and-collect availability, and shipping costs per region.
Brief in. Clean data out.
Provide target categories, brands, or search terms. We map the required data fields and delivery frequency.
We configure Playwright spiders, proxy routing for LATAM regions, and anti-bot circumvention for Falabella.
We run sample extractions to verify price accuracy, variant mapping, and null-rate thresholds.
Structured JSON, CSV, or Parquet files pushed directly to your S3 bucket or Snowflake instance.
Extracting LATAM retail data requires bypassing region blocks and rendering complex React applications.
Falabella relies heavily on client-side rendering. We use Playwright to execute JavaScript and wait for network idle to ensure price and stock payloads load fully before extraction.
Accessing Falabella from outside South America often triggers blocklists. We route requests through residential IPs in Chile, Colombia, and Peru to bypass geo-restrictions.
Prices change based on user region and CMR card status. Our crawlers intercept backend API responses to capture all price tiers simultaneously without relying solely on DOM parsing.
We rotate TLS fingerprints and manage session cookies to mimic legitimate user behaviour, bypassing web application firewalls that protect the Falabella catalogue.
Fashion items have complex size and colour matrices. We iterate through variant selectors to capture stock status and price differences for every specific SKU combination.
Retailers track Falabella's internet and CMR prices to adjust their own pricing algorithms and maintain market competitiveness.
Fashion brands monitor third-party sellers on the Falabella marketplace to detect unauthorised distributors or MAP violations.
Merchandising teams analyse category depth, brand representation, and out-of-stock rates to inform procurement strategies.
Aggregators track seller performance, fulfillment types, and review scores to identify top-performing merchants across LATAM.
Product teams extract review text and ratings to understand customer feedback on specific fashion lines or electronic devices.
Marketing teams monitor how Falabella deploys discount tags and bank promotions during peak retail events like Cyber Monday.
"Falabella dictates retail pricing trends across LATAM, but extracting that data requires navigating complex single-page applications and geo-blocks."
Building an in-house scraper for Falabella means fighting constant DOM changes, managing LATAM proxy pools, and handling heavy React payloads. DataFlirt removes this operational burden. We deliver structured, normalised catalogue data directly to your warehouse, allowing your engineering team to focus on analytics rather than pipeline maintenance.
Everything supported by our falabella.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.
We handle Falabella's React frontend by orchestrating headless browsers, ensuring all dynamic pricing and stock XHR requests complete before parsing.
Our proxy pools are geographically targeted to Chile, Colombia, and Peru, ensuring high success rates and avoiding regional content blocks.
Every pipeline run passes through strict validation checks to ensure price fields, variant mappings, and seller data meet defined quality thresholds.
Data delivered to where your team already works — no new tooling required.
About falabella.com scraping, legality, and pipeline operations.
Ask us directly →Scraping public catalogue data from Falabella is generally permissible under standard web scraping legal frameworks. We do not extract personal data or bypass authentication walls.
Yes. Our crawlers capture all visible price tiers, including standard retail, internet-only, and CMR cardholder prices.
Yes. We support falabella.com (Chile), falabella.com.co (Colombia), and falabella.com.pe (Peru) using normalised schemas.
We iterate through the product configuration matrix, extracting specific stock status and price for every size and colour combination.
Yes. We extract seller names, fulfillment methods, ratings, and identify whether a product is sold directly by Falabella or a third party.
We configure pipelines based on your requirements, ranging from weekly catalogue sweeps to high-frequency hourly polling for specific high-value SKUs.
Our selector strategies use multiple fallbacks and API interception. If a structural change breaks extraction, our monitoring catches the anomaly and our engineers deploy a fix within hours.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need to monitor competitor pricing across LATAM or extract the full fashion catalogue, we build and maintain the infrastructure. Tell us your requirements.
