Kleinanzeigen Deal Finder – Underpriced Ads & Price Drops

Monitor Kleinanzeigen.de (ex eBay Kleinanzeigen) searches and get only the new listings since your last run – each one scored against the market median of comparable ads. The actor flags deals (e.g. 25% below market and fresh), price drops and suspiciously cheap bait ads, so resellers and flippers see bargains minutes after they are posted. Search by keyword, city/PLZ + radius, category and price – or paste search URLs. Export JSON/CSV/Excel or push alerts via webhooks.

What data can you extract?

Field	Example
isDeal, dealScore	true, 41 (% below median)
price, medianPrice, percentBelowMarket	140, 239, 41
medianBasis, medianSampleSize	variant:128gb, 37
condition, intent, variantKey	normal, offer, 128gb
priceDropped, previousPrice, priceDropPercent	true, 180, 22
suspiciousTooCheap	false
title, url, location, zipCode	iPhone 13 128GB, …, 10115 Mitte
postedAt, listingAgeHours	2026-10-15T18:51Z, 0.3
sellerType, shippingAvailable, imageUrl	private, true, …
description, allImages, attributes (details)	full text, photos, Marke/Modell/Zustand

Plus every field of the Kleinanzeigen Scraper (same engine).

How deals are scored

• The median only uses clean offers: no TOP ads, no "Suche" (wanted) ads, no defective / for-parts / accessory listings.
• Listings are clustered by variant (e.g. 128 GB vs 256 GB) and compared like-for-like; the lowest/highest 10% are trimmed.
• Strict title match keeps only titles containing every search word (Kleinanzeigen's search is fuzzy) and ignores keyword stuffing like "kein iPhone 13".
• More than 75% below median = suspiciousTooCheap, never a deal.

How to use

1. Enter keywords (e.g. iphone 13 pro, rolex submariner) plus optional location, radius, category and price range – or paste search URLs.
2. Set the deal threshold (default 25%) and max listing age (default 6 h).
3. Create an Apify Schedule (e.g. every 10 minutes) and add a webhook / Make / Zapier / n8n flow to get alerts for isDeal = true.

{
  "searchQueries": ["iphone 13 pro"],
  "location": "Berlin",
  "radiusKm": 50,
  "dealThresholdPercent": 25,
  "maxListingAgeHours": 6,
  "dealsOnly": true
}

Output example

Real item from a test run:

{
  "id": "3541976963",
  "title": "Iphone13 pro",
  "price": 85,
  "isVB": false,
  "medianPrice": 250,
  "percentBelowMarket": 66,
  "dealScore": 66,
  "isDeal": true,
  "medianBasis": "global",
  "medianSampleSize": 82,
  "suspiciousTooCheap": false,
  "intent": "offer",
  "condition": "normal",
  "variantKey": "",
  "priceDropped": false,
  "url": "https://www.kleinanzeigen.de/s-anzeige/iphone13-pro/3541976963-173-7888",
  "location": "15569 Woltersdorf",
  "zipCode": "15569",
  "postedAt": "2026-10-15T18:46:00+00:00",
  "listingAgeHours": 0.13,
  "sellerType": "private",
  "shippingAvailable": true,
  "isInitialRun": true,
  "priceTypeLabel": "Festpreis",
  "sellerId": "12345678"
}

Pricing

Pay per event: $0.002 per new listing, $0.05 per deal found, $0.005 per detail page (only with details on). Example: monitoring that yields 1,000 new listings with 20 deals costs about $2 + $1 = $3. Already-seen listings are never charged again. Use Only output deals & price drops to pay only for what matters.

Use cases

• Resellers & flippers: catch underpriced phones, consoles, watches, bikes, furniture first.
• Dealers & buyers: watch competitor prices and price drops.
• Market research: track the median price of a product over time.
• Arbitrage: spot regional price differences with location + radius.

Integrations

Apify API, webhooks, Make, Zapier, n8n, Google Sheets, Slack, e-mail.

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("ninhothedev/kleinanzeigen-deal-finder").call(run_input={"searchQueries": ["iphone 13 pro"], "location": "Berlin", "radiusKm": 50, "dealsOnly": True})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["title"], item["price"], item["url"])

FAQ

How does "new since last run" work? Seen IDs and prices are stored per search in a key-value store. If the actor cannot access a named store (limited permissions), a run behaves like a first run and returns all current listings.

Is it legal? Only public listing data is collected – no contact data. Use it in line with GDPR and the site terms.

eBay sold-price comparison? Best-effort only: eBay.de currently requires a login for sold-price searches, so these fields are usually empty.

Support? Open an issue on the actor page; every run writes a RUN_SUMMARY record.

Related actors

• Kleinanzeigen Scraper – bulk export of listings with full details.