We extract product listings, pricing signals, size availability, and review sentiment from Eloquii. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery.
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 eloquii.com. All fields typed and schema-versioned.
"product_id": "12345", "title": "Puff Sleeve Midi Dress", "category": "Dresses", "sub_category": "Midi Dresses", "base_price": 119.95, "fabric_composition": "100% Cotton", "care_instructions": "Machine wash cold", "url": "https://www.eloquii.com/..."
| # | product_id | title | brand | category | sub_category | base_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Variants objects from eloquii.com. All fields typed and schema-versioned.
"sku": "12345-BLK-18", "product_id": "12345", "size": "18", "colour": "Black", "price": 119.95, "sale_price": 89.95, "discount_pct": 25, "in_stock": true, "is_clearance": false
| # | sku | product_id | size | colour | price | sale_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from eloquii.com. All fields typed and schema-versioned.
"review_id": "REV-9876", "product_id": "12345", "rating": 4.5, "fit_rating": "True to size", "length_rating": "Slightly long", "review_text": "Great dress for work.", "review_date": "2023-10-15", "helpful_votes": 12
| # | review_id | product_id | rating | fit_rating | length_rating | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fit & Sizing objects from eloquii.com. All fields typed and schema-versioned.
"product_id": "12345", "model_height": "5'10"", "model_size": "14", "fit_type": "Relaxed", "stretch_factor": "Low Stretch", "garment_length": "48 inches", "neckline": "V-Neck", "sleeve_type": "Puff Sleeve"
| # | product_id | model_height | model_size | fit_type | stretch_factor | garment_length |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category Search objects from eloquii.com. All fields typed and schema-versioned.
"keyword": "work dresses", "category_path": "Clothing > Dresses > Work Dresses", "position": 1, "product_id": "12345", "title": "Puff Sleeve Midi Dress", "price": 119.95, "rating": 4.5, "review_count": 34, "is_new": true
| # | keyword | category_path | position | product_id | title | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Eloquii scraper handles every layer of the platform: product listings, dynamic pricing, sizing availability, and the review corpus. Built with JavaScript rendering and session management.
Title, description, fabric composition, care instructions, and imagery. Scraped at the SKU level with parent-child variant mapping.
Capture base price, markdown price, promotional eligibility, and clearance status. Timestamped per crawl.
Extract model dimensions, fit type, stretch factor, and garment length measurements across the entire catalogue.
Full text, star ratings, fit feedback, and helpful vote counts. Paginated across all review pages.
Track stock availability per size and colour variant. Identify low-stock warnings and out-of-stock states.
Map the full site navigation hierarchy. Track product placement within specific collections like Bridal or Elements.
Monitor sitewide banners, discount codes, and flash sale windows. Useful for competitive pricing models.
Extract CDN URLs for all product images. Map specific image assets to their corresponding colour variants.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences.
Brief in. Clean data out.
Provide category URLs or specific product collections. We design the extraction schema tailored to apparel matrices.
We configure Scrapy crawlers, proxy rotation, and session management for eloquii.com.
Schema validation, null-rate checks, and variant mapping verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or data warehouse on an agreed cadence.
Retail sites invest heavily in scraping detection and dynamic content. Here is how we stay resilient.
Retail sites employ aggressive bot mitigation. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management. Trained on real user behaviour patterns.
Eloquii relies on React for dynamic client-side hydration. We run full Playwright browser sessions to trigger lazy-loaded images and dynamic inventory state. Captures data that headless HTTP clients miss.
Apparel requires strict parent-child SKU mapping. We normalise the matrix of sizes 14-28 against available colours, ensuring accurate price and stock representation for every specific permutation.
Retail DOM structures change frequently during promotional events. Our strategy uses multiple fallback chains per field. Layout updates do not break your data pipeline.
For large catalogues, we maintain a hash index of last-seen values. Subsequent runs only push diffs. Reduces compute cost and downstream processing load.
Retailers monitor Eloquii pricing, markdown cadences, and clearance strategies to optimise their own promotional calendars.
Merchandising teams analyse category depth, colour distribution, and size availability to inform inventory procurement.
Track new arrivals and category saturation. Identify whitespace in the plus-size apparel market.
Machine learning teams use product descriptions, fabric data, and imagery to train recommendation engines and styling algorithms.
Correlate review velocity and stock depletion rates to identify trending silhouettes and fabrics.
Extract fit feedback from reviews to understand sizing consistency and material quality perception.
"Eloquii holds critical sizing and fit data for the plus-size apparel market, but extracting it requires navigating dynamic inventory states and complex product variants."
Most retail scraping attempts fail at the variant level. Accurately mapping 15 sizes across 6 colours requires handling dynamic React hydration and localised inventory APIs. DataFlirt manages this infrastructure so your analytics teams receive normalised, warehouse-ready data without writing a single line of scraper code.
Everything supported by our eloquii.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 and retry logic. Playwright handles JavaScript rendering and interaction flows. Combined via custom middleware.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents pool contamination.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state stored in managed PostgreSQL.
Data delivered to where your team already works — no new tooling required.
About eloquii.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under US and UK law. DataFlirt targets only public product, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions, and request timing modelled on human behaviour. We monitor for blocking events and rotate IP pools automatically.
Daily catalogue refreshes complete within a 2-4 hour window. High-priority SKUs can be tracked at hourly intervals for stock depletion signals.
Yes. Our pipelines iterate through all available variant combinations on the product page. Each size and colour permutation is exported as a distinct record.
Yes. We extract the base price, current sale price, and any visible promotional text or discount codes applied to the listing.
Our smallest packages start at a defined category list with weekly delivery. For continuous sitewide monitoring, we price based on volume and delivery frequency.
Yes. We provide a sample run of up to 200 products during the scoping process. You can validate schema fit and data quality before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous price monitoring across all variants. We scope, build, and operate the pipeline. Tell us what you need.
