We extract product listings, variant availability, marketplace seller pricing, and customer reviews from Otto.de. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery 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 otto.de. All fields typed and schema-versioned.
"sku": "84920184A", "title": "Adidas Originals Sneaker", "brand": "Adidas", "current_price": 89.99, "currency": "EUR", "discount_pct": 10, "colour": "White", "in_stock": true
| # | sku | title | brand | category | sub_category | base_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Variants objects from otto.de. All fields typed and schema-versioned.
"sku": "84920184A", "variant_id": "V918237", "colour": "White", "size": "42", "current_price": 89.99, "delivery_time": "2 to 3 workdays", "seller_name": "Otto", "shipping_cost": 2.95
| # | sku | variant_id | colour | size | base_price | current_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from otto.de. All fields typed and schema-versioned.
"review_id": "REV99281", "sku": "84920184A", "rating": 5, "title": "Great fit and quality", "text": "The sneakers fit perfectly and look exactly like the pictures.", "date": "2026-03-14", "verified_purchase": true, "helpful_votes": 12
| # | review_id | sku | rating | title | text | date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Complete list of extractable fields for Seller Intelligence objects from otto.de. All fields typed and schema-versioned.
"seller_id": "SEL4492", "seller_name": "SneakerWorld GmbH", "rating": 4.8, "review_count": 1420, "products_count": 350, "return_policy": "30 days free returns", "legal_name": "SneakerWorld Retail GmbH", "shipping_methods": "Hermes, DHL"
| # | seller_id | seller_name | rating | review_count | products_count | return_policy |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Search Results objects from otto.de. All fields typed and schema-versioned.
"keyword": "white sneakers", "position": 3, "sku": "84920184A", "sponsored": false, "title": "Adidas Originals Sneaker", "price": 89.99, "rating": 4.6, "review_count": 312
| # | keyword | position | sku | title | price | brand |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our infrastructure extracts the full Otto.de catalogue: fashion variants, home appliance specifications, marketplace seller offers, and dynamic pricing.
Title, brand, category, description, specifications, and images extracted across fashion, living, and electronics categories.
Extract all colour and size combinations per product, mapping base SKUs to their respective child variants.
Identify third-party sellers on Otto.de, capturing seller ratings, review counts, and shipping policies.
Track base price, current price, discount percentages, and shipping costs timestamped per crawl.
Capture estimated delivery windows, stock availability, and specific shipping carrier information.
Extract customer ratings, review text, verified purchase flags, and specific fit feedback for apparel.
Monitor keyword positions, distinguishing between organic results and sponsored placements.
Extract structured technical specifications and EU energy efficiency classes for home appliances.
Run extractions at daily or weekly intervals with change detection to capture pricing shifts.
Brief in. Clean data out.
Provide category URLs, brand names, or keyword sets. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for Otto.de.
Schema validation, null-rate checks, and data normalisation before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or data warehouse on agreed cadence.
Otto.de employs strict rate limiting and fingerprinting. We handle the infrastructure complexity so you receive clean data.
We route requests through German residential IPs to match expected geographic behaviour, preventing IP blocks and rate limits.
Otto.de relies on client-side rendering for variant pricing and availability. We use headless browsers to execute JavaScript and capture accurate DOM states.
We iterate through size and colour selectors to expose specific pricing and stock levels that are hidden in the initial page load.
Our extraction logic uses multiple fallback chains per field, ensuring data flows even when Otto.de updates its frontend framework.
Every run emits structured logs. We monitor for null-rate spikes and schema drift, addressing issues before they impact your warehouse.
Retailers monitor Otto.de pricing and discount strategies to adjust their own marketplace positioning.
Brands track how their products are presented, priced, and reviewed by third-party sellers on the Otto marketplace.
Merchandising teams analyse category depth, variant availability, and out-of-stock rates to identify market gaps.
Aggregators evaluate third-party seller performance, tracking rating velocity and catalogue size.
Product teams extract customer reviews to understand fit issues, material quality, and overall sentiment.
Agencies track keyword rankings and sponsored placements to optimise visibility for their brand clients.
"Otto.de represents the core of German e-commerce. Extracting accurate variant and marketplace data requires continuous infrastructure maintenance."
Building an internal scraper for Otto.de means fighting bot protection and complex DOM structures. DataFlirt provides a managed extraction pipeline with residential proxies and headless browsers. Your engineering team gets structured warehouse data without the operational overhead.
Everything supported by our otto.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 manages crawl orchestration and retry logic. Playwright handles JavaScript execution and interaction flows required for variant hydration.
We maintain pools of German residential ISP proxies. Rotation happens per request to prevent IP bans and ensure consistent access to Otto.de.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management, ensuring data is delivered on your precise cadence.
Data delivered to where your team already works — no new tooling required.
About otto.de scraping, legality, and pipeline operations.
Ask us directly →Yes. We iterate through the colour and size selectors on Otto.de product pages to capture the specific price, stock status, and delivery time for every variant combination.
Yes. Otto.de operates as a marketplace. We extract the seller name, seller rating, and specific shipping policies for every offer on a product page.
We use German residential proxies and headless Playwright browsers to mimic normal user behaviour, avoiding the rate limits that block standard datacenter IPs.
Yes. We configure pipelines to run at daily intervals, using change detection to only push records where pricing or availability has shifted.
Yes. We paginate through the review sections to capture star ratings, text, date, and verified purchase indicators.
We deliver data in JSON, CSV, XLS, and Parquet. We can push directly to AWS S3, BigQuery, Snowflake, or trigger webhooks for immediate processing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a category extraction or daily price monitoring across thousands of variants, we scope, build, and operate the pipeline. Tell us what you need.
