Billiger Price Comparison Scraper

Extract complete product pricing intelligence from Billiger.de in a structured dataset. Collect product details, listing metadata, and shop-level offer information for market monitoring, catalog enrichment, and competitive analysis. Built for reliable large-scale collection with flexible search and URL-based workflows.

Features

• Search and direct URL collection — Run by keyword or target specific Billiger product/category URLs.
• Rich product coverage — Collect names, brand, category, GTIN, SKU, ratings, reviews, and media.
• Price intelligence — Capture lowest and highest prices, offer counts, and currency values.
• Shop offer breakdowns — Save seller-level offer rows with shipping and total price signals.
• Listing context metadata — Keep page-level context like source listing URL and source page number.

Use Cases

Price Monitoring

Track price movement for notebooks, phones, appliances, and other product groups in Germany. Build recurring snapshots to detect pricing trends over time.

Competitive Benchmarking

Compare seller-level offers, shipping impact, and total price positioning across multiple shops. Use the data to benchmark your own storefront strategy.

Catalog Enrichment

Populate internal catalogs with GTIN, category, image URL, and variant attributes. Improve feed quality for marketplaces, ads, and internal search.

Market Intelligence

Collect high-volume product pricing data and combine it with BI tools. Identify opportunities by product type, brand, and price band.

Input Parameters

Parameter	Type	Required	Default	Description
searchQuery	String	No	—	Keyword query used to discover products.
startUrl	String	No	—	A direct Billiger URL to start from (listing or product page).
startUrls	Array	No	—	Multiple start URLs in request-list format.
url	String	No	—	Alternate single start URL.
results_wanted	Integer	No	20	Maximum number of product records to save.
collectOffers	Boolean	No	true	Include per-shop offers with shipping and total prices.
proxyConfiguration	Object	No	Apify proxy preset	Proxy settings for resilient collection.

Output Data

Each dataset item can include the following fields:

Field	Type	Description
product_name	String	Product title shown on Billiger.
brand	String	Brand or manufacturer.
category	String	Product category label.
gtin	String	GTIN/EAN code when available.
sku	String	SKU or product code when available.
product_id	String	Billiger object identifier for the product tile.
object_type	String	Object type metadata from listing cards.
lowest_price	Number	Lowest listed price in EUR.
highest_price	Number	Highest listed price in EUR.
offer_count	Integer	Number of available offers.
rating	Number	Average rating score.
review_count	Integer	Number of reviews.
image_url	String	Product image URL.
short_description	String	Listing tile property summary.
description	String	Extended product description when available.
variant_count	Integer	Number of known variants in the product group.
variant_attributes	Array	Variant property/value summaries.
currency	String	Currency code, usually EUR.
product_url	String	Canonical product URL on Billiger.
source_listing_url	String	Listing URL used to discover the product.
source_page	Integer	Listing page number where the product appeared.
offers	Array	Shop-level offers with shop_name, shop_id, price, shipping_cost, total_price, offer_url, and product_variant_id.
scraped_at	String	ISO timestamp for extraction time.

Usage Examples

Basic Search Run

{
  "searchQuery": "laptop",
  "results_wanted": 20
}

Category Monitoring with Page Cap

{
  "startUrl": "https://www.billiger.de/show/kategorie/2303.htm?searchstring=laptop",
  "results_wanted": 60,
  "collectOffers": true
}

Fast Product Snapshot (No Offer Rows)

{
  "searchQuery": "iphone 15",
  "results_wanted": 30,
  "collectOffers": false
}

Sample Output

{
  "product_name": "Apple MacBook Air M4 2025",
  "brand": "Apple",
  "category": "Notebooks",
  "gtin": "0195949890123",
  "sku": null,
  "product_id": "110057",
  "object_type": "baseproduct",
  "lowest_price": 865.99,
  "highest_price": 1099,
  "offer_count": 1186,
  "rating": 4.7,
  "review_count": 81,
  "image_url": "https://cdn.billiger.com/dynimg/.../Apple-MacBook-Air-M4-2025.webp",
  "short_description": "macOS Sequoia (15.0) · Anzahl Prozessorkerne: 10 · HD-Standard: Retina",
  "description": "Leichtes Multimedia-Notebook mit Apple M4 Chip.",
  "variant_count": 9,
  "variant_attributes": [
    "Festplattenkapazität Gesamt: 256 GB",
    "Arbeitsspeicherkapazität: 16 GB"
  ],
  "currency": "EUR",
  "product_url": "https://www.billiger.de/baseproducts/110057-apple-macbook-air-m4-2025",
  "source_listing_url": "https://www.billiger.de/show/kategorie/2303.htm?searchstring=laptop",
  "source_page": 1,
  "offers": [
    {
      "shop_name": "ebay.de",
      "shop_id": "10992",
      "product_variant_id": "5213705085",
      "price": 865.99,
      "shipping_cost": 0,
      "total_price": 865.99,
      "offer_url": "https://www.billiger.de/redirect/..."
    }
  ],
  "scraped_at": "2026-03-05T12:00:00.000Z"
}

Tips for Best Results

Start with Practical Limits

• Use results_wanted: 20 for validation runs.
• Increase volume gradually once output quality is confirmed.

Keep Offer Collection Enabled for Pricing Analysis

• Enable collectOffers when shipping and seller-level comparisons matter.
• Disable it for faster runs focused on top-line product data.

Use Proxies for Consistent Throughput

• Residential proxy settings usually provide the most stable collection.
• For recurring schedules, keep proxy configuration consistent across runs.

Choose Focused Queries

• Specific terms like gaming laptop 16gb return cleaner datasets.
• Broad keywords can mix multiple product classes in one run.

Integrations

• Google Sheets — Build live pricing dashboards.
• Airtable — Create searchable product intelligence bases.
• Looker Studio / BI tools — Visualize trend lines and seller spreads.
• Webhooks — Trigger notifications when data arrives.
• Zapier / Make — Connect price data to business workflows.

Export Formats

• JSON — Programmatic pipelines and APIs.
• CSV — Spreadsheet analysis and quick audits.
• Excel — Business reports and operational sharing.
• XML — Legacy integrations.

Frequently Asked Questions

Can I run this actor with only a direct product URL?

Yes. Provide startUrl (or url) with a Billiger product URL and the actor will collect a detailed record for that product.

How many products can I collect in one run?

You can set any practical limit with results_wanted. For best reliability, scale gradually and tune maxPages to your use case.

Why are some fields empty for certain products?

Some listings do not expose every attribute (for example GTIN or SKU). Empty fields are expected when source data is missing.

Can I collect seller offers for every product?

Yes. Keep collectOffers enabled to include seller rows with price and shipping details.

Is this suitable for recurring monitoring?

Yes. This actor is designed for scheduled runs and comparative analysis across repeated snapshots.

Support

For issues or feature requests, use the actor issue channel in Apify Console.

Resources

• Apify Documentation
• Apify API Reference
• Apify Scheduling

Legal Notice

This actor is intended for legitimate data collection and analysis. You are responsible for complying with applicable laws, platform terms, and responsible usage practices.