We extract furniture listings, upholstery variants, pricing signals, store availability, and collection metadata from Havertys. 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 Product Listings objects from havertys.com. All fields typed and schema-versioned.
"sku": "3100-4502", "title": "Concord Sofa", "category": "Living Room", "collection_name": "Concord", "base_price": 1299.99, "currency": "USD", "dimensions": "88W x 39D x 38H", "weight": "145 lbs"
| # | sku | title | category | sub_category | collection_name | base_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Upholstery & Variants objects from havertys.com. All fields typed and schema-versioned.
"variant_id": "3100-4502-BLU", "parent_sku": "3100-4502", "fabric_name": "Navy Velvet", "fabric_grade": "Grade C", "colour_family": "Blue", "price_modifier": 150.0, "stock_status": "Made to Order", "lead_time_weeks": 8
| # | variant_id | parent_sku | fabric_name | fabric_grade | colour_family | finish_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Availability objects from havertys.com. All fields typed and schema-versioned.
"store_id": "HV-042", "store_name": "Atlanta Buckhead", "zip_code": "30305", "sku": "3100-4502", "in_stock": true, "floor_model_available": true, "pickup_available": true, "next_delivery_date": "2026-05-15"
| # | store_id | store_name | zip_code | sku | in_stock | floor_model_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Promotions objects from havertys.com. All fields typed and schema-versioned.
"sku": "3100-4502", "base_price": 1299.99, "sale_price": 1099.99, "clearance_flag": false, "discount_pct": 15, "promotion_text": "Spring Seating Sale", "top_drawer_delivery_fee": 199.99, "price_timestamp": "2026-05-12T10:00:00Z"
| # | sku | base_price | sale_price | clearance_flag | discount_pct | promotion_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Specifications & Care objects from havertys.com. All fields typed and schema-versioned.
"sku": "3100-4502", "width_inches": 88.0, "depth_inches": 39.0, "height_inches": 38.0, "seat_height_inches": 21.0, "assembly_required": false, "frame_construction": "Kiln-dried hardwood", "cushion_fill": "High-density foam with down blend"
| # | sku | width_inches | depth_inches | height_inches | seat_height_inches | assembly_required |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Havertys scraper handles complex furniture data structures: variant matrices for upholstery, unstructured dimension strings, and location-based inventory checks.
Extract living room, dining room, bedroom, and home office categories. Capture titles, descriptions, collections, and primary imagery.
Map the complete matrix of fabric grades, colours, and wood finishes. Capture price modifiers and lead times for made-to-order items.
Convert unstructured text dimensions into structured, queryable numeric fields for width, depth, height, and weight.
Simulate local sessions using zip codes to extract accurate store-level stock, floor model availability, and delivery dates.
Monitor base prices, sale events, clearance markdowns, and Top Drawer Delivery fee variations across regions.
Extract URLs for primary product photos, alternate angles, lifestyle shots, and specific fabric swatch images.
Maintain relationships between items in the same furniture collection to enable basket analysis and complete room pricing.
Capture dynamic lead times based on stock status, distinguishing between quick-ship items and custom upholstery orders.
Run pipelines at daily or weekly cadences. We maintain a hash index and only push records with modified fields.
Brief in. Clean data out.
Provide target categories, specific collections, or zip codes for inventory tracking. We map the required schema.
We configure crawlers to handle Havertys pagination, variant hydration, and location-based session management.
We test dimension parsing logic, variant price accuracy, and null-rates across the sample dataset.
Clean JSON, CSV, or Parquet delivered to your S3 bucket or data warehouse on the agreed schedule.
Furniture retail sites present unique scraping challenges, primarily around variant explosion and unstructured specifications.
A single Havertys sofa might have 50+ fabric options across different price grades. Our Playwright integration systematically triggers these variants to capture accurate price modifiers and swatch images without missing combinations.
Furniture dimensions are often displayed as raw text strings. Our pipeline includes post-processing logic to parse these strings into structured numeric fields (width_inches, depth_inches), enabling immediate analysis in your warehouse.
Havertys delivery dates and store inventory depend on the user's location. We manage session cookies and inject specific zip codes to extract accurate, localised availability data across multiple target regions.
Retail sites frequently update their front-end architecture. We use multi-layer fallback chains for our selectors, ensuring that a minor layout change on the Havertys product page does not break your data feed.
Rather than dumping the entire catalogue every day, our differential extraction engine compares current data against the last run, delivering only the items where price, stock, or variants have changed.
Furniture retailers track Havertys base pricing, promotional events, and clearance markdowns to maintain competitive positioning.
Merchandising teams analyse Havertys collections and material offerings to identify gaps in their own product lines.
Regional competitors monitor Havertys store stock and delivery lead times across specific zip codes to optimise local advertising.
Industry analysts track the introduction of new fabric grades, colours, and wood finishes to forecast interior design trends.
Computer vision and AI design platforms use structured dimension data and high-resolution imagery to train room-planning models.
Pricing teams analyse the lifecycle of Havertys products from full price to final clearance to model optimal markdown strategies.
"Havertys presents a complex data extraction challenge: every sofa exists in a matrix of fabric grades, finishes, and localised delivery timelines."
Extracting furniture catalogues requires more than simple HTTP requests. You must handle complex variant matrices, parse unstructured dimension strings into structured numeric fields, and simulate local store sessions to capture accurate inventory data. DataFlirt manages this complexity so your team receives clean, ready-to-query data.
Everything supported by our havertys.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 orchestrates the crawl while Playwright handles the complex JavaScript rendering required to expose all upholstery variants and dynamic pricing.
We route requests through US residential proxies to maintain high success rates and avoid automated blocking mechanisms.
Pipelines are deployed on Kubernetes and scheduled via Apache Airflow, ensuring reliable execution and immediate alerting on schema drift.
Data delivered to where your team already works — no new tooling required.
About havertys.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product, pricing, and store data is generally permissible. DataFlirt extracts only public, non-authenticated catalogue data and does not interact with user accounts or checkout flows. Clients should review applicable terms of service and consult legal counsel.
We use Playwright to systematically interact with the product page DOM, selecting each available fabric grade and colour to capture the specific price modifier, swatch image, and lead time associated with that variant.
Yes. You provide a list of target zip codes, and our pipeline manages regional sessions to extract accurate store-level stock, floor model availability, and local delivery dates for those specific areas.
Havertys often lists dimensions as text strings (e.g., '88W x 39D x 38H'). Our post-processing layer uses regex parsing to split these strings into strict numeric columns for width, depth, and height, making the data immediately queryable.
Pipelines can be configured to run daily or weekly. For promotional events, we can increase the frequency to capture flash sales or clearance markdowns as they happen.
Our base engagements typically cover the full catalogue extraction on a weekly schedule. Pricing scales based on the frequency of extraction and the number of local zip codes required for inventory tracking.
Yes. We offer a sample extraction of a specific category (e.g., Living Room Sofas) so you can evaluate the schema structure, dimension parsing accuracy, and variant completeness before proceeding.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop wrestling with unstructured furniture data and complex variant matrices. Tell us your target categories and local zip codes, and we will build the pipeline.
