Amazon DE Sellers Leads Scraper : Multi-Niche Lead Sourcing

Amazon DE Seller Scraper — Extract Sellers, Products & VAT Data

Amazon DE Sellers Leads Scraper : Multi-Niche Lead Sourcing extracts third-party seller leads, product data, and business contact details (VAT number, trade-register number, address, phone, email) directly from Amazon.de search and product pages. Queue a batch of keyword and category niches in one run, or fall back to a single keyword search. Every response returns typed, normalized JSON — no HTML, no selectors, no parsing required. Sellers found under more than one queued niche are automatically flagged, so cross-category sourcing and lead-gen teams see coverage, not isolated rows.

🧭 What is Amazon DE Sellers Leads Scraper?

Amazon DE Sellers Leads Scraper : Multi-Niche Lead Sourcing is an Apify Actor that turns Amazon.de search results into a structured list of third-party seller leads. It walks from a search or product page to the seller's public profile and business/Impressum page, pulling out product data, seller ratings, and legal business details in one pass. No Amazon account or login is required — every page it reads is public.

• 🏪 Scrape sellers — seller ID, public profile URL, lifetime/1-year/3-month rating and review counts, seller description
• 📦 Scrape products — title, price, list price, rating, review count, image, breadcrumb category
• 🧾 Scrape business & contact details — legal name, business type, trade-register number, VAT number, phone, email, address (when Amazon discloses them)
• 🧺 Queue several niches (searchQueries) in one run, or use a single legacy keyword + category pair
• 🌐 Export as JSON or CSV — no proxy management, Apify Proxy (residential, pinned to Germany) is handled automatically

📊 What data does Amazon DE Sellers Leads Scraper collect?

Every output row combines a seller, the product it was found on, and that seller's public business details — plus, in batch runs, which queued niche it came from.

Data Type	Key Fields	JSON Field Names
Sellers	seller ID, seller profile URL, lifetime/1-year/3-month rating & review counts, seller description	seller_id, seller_page_url, rating_lifetime, reviews_lifetime, rating_1_year, reviews_1_year, rating_3_months, reviews_3_months, about_seller
Products	title, price, list price, currency, rating, review count, image, breadcrumb category	product_name, price, list_price, currency, product_rating, product_review_count, image_url, category
Business & contact details	legal business name, business type, trade-register number, VAT number, phone, email, address	business_name, business_type, registration_number, vat_number, phone_number, email, business_address, country_code
Niche coverage (batch runs)	which queued niche a row came from, how many queued niches that seller has been confirmed under	sourceKeyword, sourceCategory, sellerAppearsInQueries, sellerCategories

Need more Amazon.de data?

If you need pricing history or buy-box ownership rather than seller leads, the same publisher's Amazon Price Tracker (seller and buy box data) and Amazon Product Details Scraper (buy box, stock and price changes) cover that ground. For plain product search results without the seller/business lookup, see Amazon Search Scraper (by price, brand, rating filters).

🆚 How does Amazon DE Sellers Leads Scraper differ from the official Amazon API?

Amazon's official APIs are not built to look up a third-party competitor's business details — they are scoped to your own catalogue or your own seller account. As of 2026-08-15: the Product Advertising API (PA-API) requires 10 qualifying affiliate sales in a trailing 30-day window to gain and keep access, and Amazon has announced it retires on April 30, 2026 in favor of the Creators API, which carries the same 10-sale requirement (Velantio, checked 2026-08-15). The Selling Partner API (SP-API) only returns data for the authenticated seller's own account (orders, listings, payments) — it has no endpoint for another seller's VAT number, trade-register number, or Impressum address — and Amazon introduced a $1,400/year subscription plus usage-based fees for third-party developers starting January 31, 2026 (ppc.land, checked 2026-08-15).

Feature	Amazon Official APIs (PA-API / SP-API)	Amazon DE Sellers Leads Scraper
Access requirement	PA-API: 10 qualifying sales in a rolling 30-day window; SP-API: authorized seller/developer account	No approval process — supply a keyword, category, or URL and run
Third-party seller business info (VAT, registration number, address)	Not exposed by either API — SP-API only returns your own account's data	Read directly off the seller's public Impressum/business page
Multi-niche batch search in one call	Not a built-in concept in either API	Native — queue keyword+category pairs in searchQueries, one shared lead budget
Fees for this use case	SP-API: $1,400/year + usage fees for third-party developers from 2026; PA-API: access gated by sales volume, not a direct fee	Apify's pay-per-event pricing, charged per row_result
Entity coverage	Product catalogue (PA-API) or your own account only (SP-API)	Product + seller + business/contact data for any seller Amazon.de surfaces in search

The official APIs are the right choice if you are managing your own Amazon seller account or building an affiliate storefront with your own catalogue. Amazon DE Sellers Leads Scraper is the right choice when you need business and contact details for other sellers on Amazon.de — something neither official API is designed to return.

🎯 Why do developers and teams scrape Amazon.de seller data?

For sourcing and procurement teams

A buyer building a supplier list across several product lines — say yoga mats, resistance bands, and phone cases — queues all three as one searchQueries batch instead of launching three separate runs. Every lead is tagged with sourceKeyword/sourceCategory, so the resulting dataset can be filtered per niche immediately, and sellerAppearsInQueries surfaces sellers already active across more than one category — useful signal for a supplier who could fulfil a wider order.

For B2B sales and outreach teams

Agencies selling packaging, logistics, accounting, or marketing services to Amazon third-party sellers use business_name, vat_number, phone_number, and email (when disclosed) to build outreach lists segmented by product category. Because amazon_category narrows results to a specific vertical, a team selling to fashion sellers can pull a category-specific lead list without manually filtering a general Amazon export.

For market research and compliance teams

Impressum-style business data — legal name, trade-register number, VAT number, registered address — supports market-entry and seller-verification research at scale, across as many niches as fit in one searchQueries batch. Because the data is read straight from each seller's own public disclosure page, no assumptions or inference are involved in the business fields.

For developers building lead-gen and enrichment tools

Every row is typed JSON with stable field names (asin, seller_id, business_name, vat_number, and so on), so it slots directly into a CRM import, a lead-scoring pipeline, or an LLM-based enrichment step without an HTML-parsing layer in between. The dataset is available through the Apify API the moment each row is pushed, since results are streamed in real time as they're collected.

🚀 How to scrape Amazon.de sellers (step by step)

1. Open the Actor's page in the Apify Console (search "Amazon DE Sellers Leads Scraper : Multi-Niche Lead Sourcing" or use its direct listing link) and click Try for free or Run.
2. Provide at least one search path: a batch of niches in searchQueries (keyword:amazon_category per line), a single legacy keyword + amazon_category pair, or a list of Amazon.de URLs in startUrls. All three fields are individually optional, but the run produces zero results if none of them are filled.
3. Narrow results by choosing an amazon_category (15 supported categories) and a sort_by order — both apply to every queued niche in the same run.
4. Set maxResults (1–50,000) and start the run. This is the total lead budget shared across every queued niche, not a per-niche limit.
5. Once the run finishes, download results from the Dataset tab as JSON, CSV, or another Apify-supported export format, or pull them programmatically via the Apify API.

What to do when Amazon.de changes its structure

The Actor is maintained, and its output schema — field names and types — stays stable on the user's end even when Amazon.de's page markup changes underneath it. No specific fix turnaround is published; if extraction for a page pattern breaks, it's a maintenance issue on the Actor side, not something a run's input needs to work around.

⬇️ Input

All parameters are optional individually, but at least one search path (searchQueries, keyword + amazon_category, or startUrls) must be filled for the run to produce results.

Parameter	Required	Type	Description	Example Value
searchQueries	No	array (stringList)	One niche per line, keyword:amazon_category — e.g. yoga mat:sports. Every queued pair is searched in turn (shared run budget from maxResults), and every output row is tagged sourceKeyword/sourceCategory. amazon_category must be one of the 15 supported values. Leave empty to fall back to keyword + amazon_category below, treated as a 1-item batch.	["yoga mat:sports", "resistance bands:sports", "phone case:electronics"]
keyword	No	string	Legacy fallback, used only when searchQueries is empty — treated as a 1-item batch alongside amazon_category below.	"shirt"
amazon_category	No	string (enum)	Legacy fallback category paired with keyword. One of: fashion-womens, fashion-mens, fashion-kids, electronics, grocery, toys, sports, books, beauty, home-garden, automotive, pet-supplies, tools-garden, baby, health.	"fashion-womens"
sort_by	No	string (enum)	Amazon result ordering applied to every queued niche. One of: Featured, Best Sellers, Price: Low to High, Price: High to Low, Avg. Customer Review, Newest Arrivals, Relevance, Select....	"Featured"
maxResults	No	integer (min 1, max 50000)	Maximum unique seller leads to collect, shared across ALL queued niches combined — not per niche. Higher values may increase run time.	10
startUrls	No	array (requestListSources)	Amazon.de search or product URLs, processed directly instead of the queued niches/legacy keyword.	[]
proxyConfiguration	No	object (proxy editor)	Apify Proxy config. Defaults to residential, pinned to Germany, for reliable Amazon.de access.	{"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "DE"}

Example input (multi-niche batch)

{
  "searchQueries": [
    "yoga mat:sports",
    "resistance bands:sports",
    "phone case:electronics"
  ],
  "maxResults": 100,
  "sort_by": "Featured",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "DE"
  }
}

Example input (single-niche / legacy, still supported)

{
  "keyword": "shirt",
  "amazon_category": "fashion-womens",
  "sort_by": "Featured",
  "maxResults": 10
}

Common pitfall: every searchQueries line must be exactly keyword:amazon_category with a category from the supported list — a line missing the colon, an empty half, or an unrecognized category is skipped with a warning in the run log, not an error. The same applies to the legacy fields: filling in only keyword OR only amazon_category (without the other, and without searchQueries/startUrls) produces zero results, since the legacy pair only counts as a valid 1-item batch when both are present.

⬆️ Output

Results are pushed to the dataset in real time, one row per collected seller lead, as typed JSON — no HTML, no selectors. Download as JSON, CSV, or any other Apify-supported dataset export format.

Scraped seller lead

{
  "asin": "B0CX8J9K2L",
  "product_name": "Premium Rutschfeste Yogamatte 6mm",
  "product_url": "https://www.amazon.de/dp/B0CX8J9K2L",
  "image_url": "https://m.media-amazon.com/images/I/71abc123XYZ.jpg",
  "price": 24.99,
  "currency": "EUR",
  "list_price": 29.99,
  "product_rating": 4.5,
  "product_review_count": 1832,
  "seller_id": "A1B2C3D4E5F6G7",
  "seller_page_url": "https://www.amazon.de/sp?ie=UTF8&seller=A1B2C3D4E5F6G7",
  "category": "Sport & Freizeit > Fitness > Yoga",
  "sourceKeyword": "yoga mat",
  "sourceCategory": "sports",
  "rating_lifetime": 4.6,
  "reviews_lifetime": 5210,
  "rating_1_year": 4.7,
  "reviews_1_year": 980,
  "rating_3_months": 4.8,
  "reviews_3_months": 214,
  "about_seller": "FitGear Handels GmbH is a specialist supplier of sports and fitness equipment...",
  "business_name": "FitGear Handels GmbH",
  "business_type": "Gesellschaft mit beschränkter Haftung (GmbH)",
  "registration_number": "HRB 123456",
  "vat_number": "DE123456789",
  "phone_number": "+49 30 12345678",
  "email": "kontakt@fitgear-handels.de",
  "business_address": "Musterstraße 12, 10115 Berlin",
  "country_code": "Germany",
  "sellerAppearsInQueries": 2,
  "sellerCategories": ["sports", "electronics"],
  "scraped_at": "2026-08-15T10:42:18.123456+00:00"
}

Every field the row-building code writes is listed above — nothing is trimmed for the dataset's default view. A few behaviors worth knowing:

• ⚠️ country_code is not an ISO country code — it holds whatever text sits in the last line of the seller's Impressum address block (as segmented by Amazon's own markup), which is typically the country name rather than a two-letter code.
• Business fields (business_name, business_type, registration_number, vat_number, phone_number, email, business_address, country_code, about_seller) come back null whenever the seller hasn't disclosed that field on their public profile — they are never guessed or inferred.
• list_price is only populated when it's genuinely higher than price (a strike-through/reference price); otherwise it's null.
• sourceKeyword, sourceCategory, sellerAppearsInQueries, and sellerCategories are null on every row when the run was driven by startUrls alone, since there is no queued-niche concept to tag in that mode.
• sellerAppearsInQueries is a running tally, not a final total computed after the run: each row shows how many queued niches that seller was confirmed under up to and including that row. Since rows are pushed the instant they're collected, the last row for a given seller_id in a run holds its most complete count.

Every pushed row is charged under the row_result event — the Actor does not push separate uncharged error or accounting rows to the dataset; a product with no identifiable seller, or a page that fails to load, is simply skipped and logged to the run log, not written as a row.

📈 How many results can you scrape with Amazon DE Sellers Leads Scraper?

maxResults accepts 1 to 50,000 unique seller leads, shared across every queued niche in the run — not a per-niche limit. Separately, searchQueries batches are capped at 25 queued niches per run in the Actor's own logic; entries beyond the 25th are dropped with a warning in the run log rather than erroring the run. For each niche, search-result pages are fetched until a page returns fewer than a full page of product tiles (end of results) or an internal ceiling of 200 search pages is reached, whichever comes first — so a run can return fewer leads than maxResults if a niche's real inventory runs out first.

🔌 Integrate Amazon DE Sellers Leads Scraper and automate your workflow

Amazon DE Sellers Leads Scraper works with any language or tool that can send an HTTP request, through the standard Apify API.

REST API integration

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_API_TOKEN>")

run_input = {
    "searchQueries": ["yoga mat:sports", "phone case:electronics"],
    "maxResults": 100,
    "sort_by": "Featured",
}

run = client.actor("<YOUR_USERNAME>/amazon-de-sellers-leads-scraper-multi-niche-lead-sourcing").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["business_name"], item["email"], item["sourceKeyword"])

Works in Python, Node.js, Go, Ruby, or cURL against the same Apify API endpoints.

Automation platforms (n8n, Make, Zapier)

The Actor runs through Apify's own integration on each platform — add the Apify app/module, choose "Run Actor" as the action, and point it at this Actor's ID. Results land in your dataset and can be pulled into the next step of the workflow the same way as any other Apify Actor run.

⚖️ Is it legal to scrape Amazon.de seller data?

Yes — Amazon DE Sellers Leads Scraper only reads pages Amazon.de already serves publicly: search results, product pages, and each seller's own public profile and business-disclosure page. This is business and product data — legal business name, trade-register number, VAT number, product pricing — not personal profile data, so GDPR's personal-data framework does not attach to it. What does apply is Amazon's own Terms of Service, which govern automated access to the site, and database-rights law in jurisdictions that recognize it. Consult legal counsel for commercial use cases involving bulk collection of business or contact data, especially before using the extracted contact fields for outreach.

❓ Frequently asked questions

Does Amazon DE Sellers Leads Scraper work without an Amazon account?

Yes. It reads only public Amazon.de pages — no Amazon login or seller account is needed. You do need an Apify account and API token to run the Actor itself.

How often is the scraped data updated?

Every run fetches Amazon.de live — nothing is served from a cache. Re-run the Actor whenever you need current prices, ratings, or business details.

What happens if a product has no identifiable third-party seller?

Products sold directly by Amazon, or where the seller ID can't be located on the product page, are skipped — they don't produce a row and don't count against maxResults. This is expected behavior, not an error.

Can I scrape private seller information Amazon doesn't disclose?

No. Only what a seller has chosen to publish on their public profile or business-disclosure page is returned. When Amazon doesn't display a field (email, phone, VAT number, etc.) for a given seller, that field comes back null rather than a guess.

How am I charged for using this Actor?

Every dataset row is charged under the single row_result pay-per-event — there's no separate charge for search pages, retries, or skipped products. Check the Actor's Pricing tab in Apify Console for the current per-event rate.

Does Amazon DE Sellers Leads Scraper work for AI agent workflows and LLM pipelines?

Yes — it's callable as a standard HTTP endpoint through the Apify API by any agent framework. Every response is typed JSON with stable field names, so it can be passed directly into an LLM context window or a lead-enrichment pipeline without an HTML-parsing step.

How does Amazon DE Sellers Leads Scraper handle Amazon.de's anti-bot system?

It defaults to Apify's residential proxy pool pinned to Germany, escalating from no-proxy to datacenter to residential connection tiers on repeated failures. It performs a homepage warm-up request before scraping to establish session cookies, rotates user agents and adds randomized delays between requests, and checks every response against a set of known block/captcha signatures — including an Akamai Bot Manager proof-of-work interstitial (a small challenge-token page that returns HTTP 200 but carries no real content) confirmed live against Amazon.de on 2026-08-12 — so a disguised block page isn't mistaken for real data.

Does Amazon DE Sellers Leads Scraper return data in a format LLMs can use directly?

Yes. Typed, normalized JSON with stable field names — no HTML, no CSS selectors, no parsing step. Pass it directly into an LLM context window, index it into a vector store, or route it through an agent tool.

Can I use Amazon DE Sellers Leads Scraper without managing proxies?

Yes. Apify Proxy (residential, pinned to Germany) is configured by default; you only need to touch proxyConfiguration if you have a specific reason to change it.

What does sellerAppearsInQueries actually count, and can I trust the final number?

It's a running tally computed as the run progresses, not a value recalculated after the run finishes. Each row shows how many of the queued niches that seller has been confirmed under as of that row. Because rows are streamed to the dataset the instant they're collected, the last row for a given seller_id in the run is the one holding its most complete coverage count.

What happens when Amazon.de changes its page structure or blocks the scraper?

The Actor is maintained, and the output schema — field names and types — stays stable on your end even when Amazon.de's underlying markup changes. No specific repair turnaround is published.

💬 Your feedback

Found a bug, or a business field that's coming back empty when it shouldn't? We want to know. Open an issue through the Actor's Issues tab in Apify Console, or reach the developer directly through their Apify profile.