We extract product listings, technical specifications, local branch availability, and promotional pricing from moemax.de. Delivered as clean JSON, CSV, or Parquet to your data 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 moemax.de. All fields typed and schema-versioned.
"sku": "002528001201", "title": "Ecksofa in Grau", "brand": "Bessagi Home", "category": "Wohnzimmer", "price": 499.0, "currency": "EUR", "colour": "Grau", "material": "Textil"
| # | sku | title | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Promotions objects from moemax.de. All fields typed and schema-versioned.
"sku": "002528001201", "current_price": 499.0, "original_price": 699.0, "discount_pct": 28.6, "promotion_name": "Sale %", "online_exclusive": false, "vat_included": true
| # | sku | current_price | original_price | discount_pct | promotion_name | valid_until |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Store Availability objects from moemax.de. All fields typed and schema-versioned.
"sku": "002528001201", "store_id": "M01", "store_name": "Moemax Muenchen", "zip_code": "80331", "stock_level": 4, "pickup_available": true, "pickup_time_days": 1
| # | sku | store_id | store_name | zip_code | stock_level | pickup_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Specifications objects from moemax.de. All fields typed and schema-versioned.
"sku": "002528001201", "width_cm": 240.0, "height_cm": 85.0, "depth_cm": 160.0, "assembly_required": true, "material_primary": "Polyester", "max_load_kg": 300.0
| # | sku | width_cm | height_cm | depth_cm | weight_kg | material_primary |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Delivery & Logistics objects from moemax.de. All fields typed and schema-versioned.
"sku": "002528001201", "delivery_available": true, "delivery_cost": 49.9, "estimated_days_min": 14, "estimated_days_max": 21, "package_count": 3, "forwarding_agency": true
| # | sku | delivery_available | delivery_cost | estimated_days_min | estimated_days_max | supplier_direct |
|---|---|---|---|---|---|---|
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Our Moemax scraper targets the specific complexities of furniture retail data: local branch stock levels, detailed dimension attributes, and complex promotional pricing structures.
Extract every SKU across all categories. Capture titles, descriptions, image URLs, and brand associations.
Parse detailed dimensions, materials, care instructions, and energy efficiency classes into structured data types.
Iterate over local store IDs to capture precise stock levels, click-and-collect availability, and local display models.
Track base prices, discount percentages, Mia Card exclusive pricing, and time-limited promotional campaigns.
Capture delivery costs, estimated shipping windows, forwarding agency requirements, and package counts.
Link colour and size variations to parent products, ensuring all permutations are captured accurately.
Run continuous pipelines that only emit records when prices, stock levels, or delivery times change.
Bypass rate limits and IP blocks using residential proxy rotation and automated session management.
Convert irregular text descriptions and mixed dimension formats into clean, normalised numerical fields.
Brief in. Clean data out.
Specify target categories, required store locations for stock data, and delivery frequency.
We configure crawlers to handle Moemax pagination, cookie consent, and local store session states.
We monitor null rates for critical fields like price and dimensions before pushing to production.
Clean JSON, CSV, or Parquet delivered to your S3 bucket or data warehouse on schedule.
Furniture retail sites rely heavily on dynamic frontend rendering and location-based session states. We handle the infrastructure so you get clean data.
Moemax uses a modern frontend architecture where product details and stock levels load dynamically. We use Playwright to execute JavaScript, ensuring all asynchronous data is captured.
Extracting local stock requires setting and maintaining specific store cookies per request. Our pipeline manages these session states automatically across thousands of SKUs.
To avoid IP bans and ensure accurate regional pricing, we route all requests through high-quality German residential proxies with automated rotation.
Furniture dimensions often appear in unstructured text blocks. We parse and normalise width, height, and depth into structured numerical fields for immediate analysis.
Site updates can break selectors. We monitor extraction yields in real time and automatically alert our engineering team if field coverage drops below defined thresholds.
Furniture retailers track Moemax pricing and promotional campaigns to adjust their own pricing strategies dynamically.
Analysts monitor category expansion, material trends, and colour popularity within the European furniture market.
Suppliers and competitors analyse out-of-stock rates across local branches to identify supply chain vulnerabilities.
Publishers extract product catalogues to populate comparison sites with accurate pricing and delivery timelines.
Delivery networks analyse package counts, weights, and estimated delivery times to benchmark industry standards.
Marketplaces use structured specification data to enrich their own product listings and improve search filtering.
"Furniture retail data requires precision. Dimensions, local stock, and delivery timelines are critical signals that demand structured extraction."
Scraping Moemax requires managing local store cookies, executing JavaScript for dynamic pricing, and parsing unstructured technical specifications. DataFlirt manages these complexities, delivering clean, query-ready data directly to your warehouse.
Everything supported by our moemax.de 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 the orchestration and deduplication, while Playwright executes JavaScript to render dynamic stock and pricing widgets.
We use German residential proxies to bypass regional blocks and ensure accurate local pricing and availability data.
Pipelines run on AWS infrastructure, orchestrated by Airflow for reliable scheduling and automated retry logic.
Data delivered to where your team already works — no new tooling required.
About moemax.de scraping, legality, and pipeline operations.
Ask us directly →Yes. We configure the pipeline to iterate through specified branch IDs, setting the appropriate session cookies to capture local stock levels and click-and-collect availability.
Our scraper maps all available variants to the parent SKU, ensuring that pricing, stock, and image URLs are accurate for every specific permutation.
Yes. We extract the specification tables and parse unstructured text to provide clean numerical fields for dimensions and categorical fields for materials and energy classes.
We support daily, weekly, or custom schedules. For critical pricing and stock monitoring, we can configure high-frequency runs on a subset of target SKUs.
Yes. The pipeline extracts base prices, discounted prices, discount percentages, and specific campaign tags associated with the product.
Yes. We implement change detection diffing, meaning your delivery payload can be configured to only include records where pricing or stock status has changed since the last run.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop managing proxies and fixing broken selectors. Tell us your target categories and data requirements, and we will build and maintain the pipeline.
