Otto.de Product Scraper

Extract product data from Otto.de quickly and reliably for research, monitoring, and market analysis. Collect structured product records including names, prices, ratings, availability, images, and URLs. Built for production-scale runs with stable pagination and clean output.

Features

• Fast Production Runs — Optimized internal crawl settings for high-throughput data collection.
• Reliable Product Coverage — Automatically navigates Otto.de listing pages to gather broad result sets.
• Rich Product Records — Collects pricing, brand, rating, review count, availability, and product metadata.
• Duplicate Protection — Avoids duplicate product records during larger runs.
• Flexible Start Options — Start from a specific Otto.de page or from a search query.
• Clean Dataset Output — Delivers normalized data ready for BI tools and automation workflows.

Use Cases

Price Monitoring

Track product prices and discount movement across categories. Use repeated runs to build price history for trend analysis and alerts.

Competitor and Assortment Research

Measure brand presence, product mix, and offer distribution in relevant categories. Use the dataset to benchmark assortment strategy and market positioning.

E-commerce Intelligence

Collect structured product data for dashboards and reporting. Combine outputs with your internal data for deeper commercial insights.

Catalog Enrichment

Use Otto product attributes as reference data to enrich your own product database. Improve completeness for titles, brands, and pricing context.

Workflow Automation

Feed data into no-code or API workflows for downstream processing. Automate reporting, syncing, and decision-support pipelines.

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Input Parameters

Parameter	Type	Required	Default	Description
startUrl	String	No	""	Otto.de start page URL. If provided, this is used first.
searchQuery	String	No	"shirt"	Search term used when startUrl is empty.
collectDetails	Boolean	No	true	Prioritizes richer product records with complete fields when available.
results_wanted	Integer	No	100	Maximum number of products to collect.
max_pages	Integer	No	20	Maximum number of listing pages to process.
proxyConfiguration	Object	No	{"useApifyProxy": false, "apifyProxyGroups": ["RESIDENTIAL"]}	Proxy settings for reliability and anti-blocking support.

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Output Data

Each dataset item contains:

Field	Type	Description
name	String	Product title.
brand	String	Brand name.
price	String	Current price value.
original_price	String	Previous or comparison price when available.
rating	Number	Average customer rating.
review_count	Number	Number of customer reviews.
availability	String	Product availability text.
image_url	String	Product image URL.
product_url	String	Product detail page URL.
url	String	Canonical source URL for the record.
article_number	String	Product/article identifier when available.
variation_id	String	Variation identifier when available.
data_quality	String	Record completeness marker (rich or basic).
source	String	Origin marker for the extracted record.

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Usage Examples

Basic Search Run

Collect products from a standard search query:

{
    "searchQuery": "shirt",
    "results_wanted": 100
}

Start From Specific URL

Use a known Otto search or category URL:

{
    "startUrl": "https://www.otto.de/suche/sneaker/?o=0&l=gp&c=",
    "results_wanted": 200,
    "max_pages": 15
}

High-Volume Collection

Collect a larger dataset for analysis:

{
    "searchQuery": "herren t-shirt",
    "results_wanted": 1000,
    "max_pages": 50,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

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Sample Output

{
    "name": "Tommy Hilfiger Big & Tall T-Shirt BT-BRAND LOVE BIG HILFIGER Rundhals, normale Passform, Große Größen",
    "brand": "Tommy Hilfiger Big & Tall",
    "price": "28.99",
    "original_price": "39.90",
    "rating": 5,
    "review_count": 4,
    "availability": "lieferbar - in 1-2 Werktagen bei dir",
    "image_url": "https://i.otto.de/i/otto/470ac366-4969-5bae-9ee4-0a7124ccd145?$responsive_ft2$",
    "product_url": "https://www.otto.de/p/tommy-hilfiger-big-tall-t-shirt-bt-brand-love-big-hilfiger-rundhals-normale-passform-grosse-groessen-1975656957/",
    "url": "https://www.otto.de/p/tommy-hilfiger-big-tall-t-shirt-bt-brand-love-big-hilfiger-rundhals-normale-passform-grosse-groessen-1975656957/",
    "article_number": "59868001",
    "variation_id": "1975656958",
    "data_quality": "rich",
    "source": "listing"
}

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Tips for Best Results

Start With Focused Queries

• Use specific keywords to improve relevance.
• Begin with one category or intent per run.
• Expand query variants after validating output quality.

Balance Scale and Precision

• Use smaller results_wanted during testing.
• Increase max_pages for larger production runs.
• Schedule repeated runs for continuous monitoring.

Use Proxies for Reliability

• Enable residential proxy groups for larger collections.
• Keep proxy settings consistent across scheduled runs.
• Monitor failed requests and adjust run size if needed.

Validate Sample Records Early

• Check first items for field completeness.
• Confirm price, brand, and product_url are populated.
• Tune input scope before high-volume execution.

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Integrations

Connect your output with:

• Google Sheets — Build live price and catalog trackers.
• Airtable — Create searchable product intelligence bases.
• Slack — Send run summaries and alerts.
• Webhooks — Push records into custom endpoints.
• Make — Automate post-processing pipelines.
• Zapier — Trigger downstream business workflows.

Export Formats

• JSON — For APIs and backend systems.
• CSV — For spreadsheet analysis.
• Excel — For business reporting.
• XML — For system-to-system integrations.

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Frequently Asked Questions

How many products can I collect per run?

You can scale from small tests to large production runs. Practical volume depends on query scope, page limits, and reliability settings.

Can I scrape categories instead of search terms?

Yes. Provide a category or filtered listing URL in startUrl.

Why are some fields occasionally empty?

Some products may not expose every attribute at runtime. The actor still returns available fields in a consistent structure.

Is duplicate data prevented?

Yes. The actor includes deduplication safeguards so repeated product links are not pushed multiple times in one run.

Should I use proxies?

For small tests, direct requests may work. For large or scheduled runs, proxies are recommended for higher stability.

Can I automate this daily?

Yes. Use Apify schedules to run hourly, daily, or weekly based on your monitoring requirements.

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Support

For issues or feature requests, contact support through the Apify Console.

Resources

• Apify Documentation
• API Reference
• Scheduling Runs

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Legal Notice

This actor is designed for legitimate data collection purposes. Users are responsible for ensuring compliance with Otto.de terms of service and applicable laws. Use collected data responsibly and respect rate limits.