Flippa Scraper

Extract digital asset listings from Flippa.com — the marketplace for buying and selling websites, ecommerce stores, SaaS products, mobile apps, domains, and online businesses. This scraper returns clean, structured data including price, revenue, profit, traffic, verification, seller details, and industry — all in one run.

Perfect for deal sourcing, due diligence, market research, competitor monitoring, and building your own acquisition opportunity feed.

What it does

• Scrapes Flippa search results from a URL or from structured filter fields
• Returns complete listing data: financials, traffic, verification, seller, and listing metadata
• Works without cookies or proxies — fast, reliable, low cost
• Supports all major property types: websites, ecommerce stores, SaaS, iOS/Android apps, domains, newsletters, digital products
• Handles Flippa's pagination automatically up to 10,000 results per query

Input

Option A — Paste a Flippa URL (easiest)

Set Flippa Search URL to any Flippa search page URL, e.g.:

https://flippa.com/search?filter[property_type][]=ecommerce_store&filter[status]=open
https://flippa.com/search?filter[property_type][]=saas&filter[price][min]=10000
https://flippa.com/search?search[query]=shopify

Filters in the URL are mapped directly to Flippa's API.

Option B — Use structured filters

Leave Flippa Search URL empty and configure any combination of:

Field	Description
Property Type	website, ecommerce_store, saas, ios_app, android_app, domain, newsletter, digital_product, content, service
Status	open, under_offer, closed
Sale Method	auction, classified
Price Min / Max	Asking price range in USD
Revenue Min	Minimum monthly revenue in USD
Profit Min	Minimum monthly profit in USD
Verified Revenue Only	Only listings with Flippa-verified revenue
Verified Traffic Only	Only listings with Flippa-verified traffic
Search Query	Keyword search (e.g. "shopify", "blog", "saas")
Sort Order	Newest, oldest, highest price, lowest price, highest revenue, highest profit
Max Items	Maximum number of listings to return (default 50)

Output

Each listing is a single JSON record with the following fields (empty fields are omitted to keep the output clean):

Field	Description
id	Flippa listing ID
title	Listing title
url	Full Flippa listing URL
property_name	Property / brand name
property_type	Type of asset (website, saas, app, etc.)
industry	Industry / niche
hostname	Primary hostname of the property
external_url	External URL of the property
summary	Seller's short description
price	Current / display price in USD
buy_it_now_price	Buy-it-now price (auctions)
sale_method	auction or classified
status	Listing status
bid_count	Number of bids (auctions)
reserve_met	Whether auction reserve has been met
revenue_per_month	Monthly revenue in USD
profit_per_month	Monthly profit in USD
average_revenue	Average monthly revenue
average_profit	Average monthly profit
revenue_multiple	Price ÷ annualized revenue
profit_multiple	Price ÷ annualized profit
page_views_per_month	Monthly page views
uniques_per_month	Monthly unique visitors
app_downloads_per_month	Monthly downloads (apps)
has_verified_revenue	Revenue verified by Flippa
has_verified_traffic	Traffic verified by Flippa
established_at	When the property was established
age_years	Age of the property in years
starts_at	Listing start time
ends_at	Listing end time
seller_location	Country of the seller
super_seller	Seller is a Flippa Super Seller
turnkey_listing	Tagged as turnkey
confidential	Listing is marked confidential
revenue_sources	Revenue source tags
image_url	Listing thumbnail URL
scraped_at	UTC timestamp when scraped

Sample output

{
  "id": "12294434",
  "title": "Profitable Shopify auto parts business",
  "url": "https://flippa.com/12294434-profitable-shopify-auto-parts-business",
  "property_name": "247 Car Spares",
  "property_type": "ecommerce_store",
  "industry": "automotive",
  "hostname": "247carspares.com",
  "price": 400000,
  "sale_method": "classified",
  "status": "open",
  "revenue_per_month": 18669,
  "profit_per_month": 8849,
  "revenue_multiple": 1.78,
  "profit_multiple": 3.77,
  "uniques_per_month": 1000,
  "established_at": "2021-01-01T00:00:00+11:00",
  "age_years": 5.28,
  "seller_location": "India",
  "image_url": "https://static2.flippa.com/thumbnail2x_68a5a412.png",
  "scraped_at": "2026-04-13T11:22:33Z"
}

FAQ

Do I need a Flippa account or API key? No. The scraper works against Flippa's public catalog — no login, cookies, or authentication.

Does it need a proxy? No. The scraper runs without proxies in most cases and handles rate limits automatically with retries and backoff.

Can I scrape sold listings? No. Flippa does not expose sold listings through its public API, so this scraper only returns active listings (open, under offer, closed).

How many listings can I get per run? Flippa caps each search at 10,000 results. If you need more, split your query using narrower filters (e.g. price ranges).

How fresh is the data? Every run pulls live data directly from Flippa, so the data is as current as Flippa's marketplace.

Which property types are supported? All of them: websites, ecommerce stores (Shopify, WooCommerce, etc.), SaaS, iOS and Android apps, domains, newsletters, digital products, content sites, and services.

Can I filter by category or niche? Yes — use the Search Query field or paste a Flippa URL with the category filter already applied.

What happens if a listing has missing data? Missing fields are omitted from the record entirely — no empty or null values pollute the dataset.

Why does an auction listing's price sometimes exceed my priceMax filter? Flippa's filter[price][max] is applied against the listing's asking / buy-it-now price, not the current bid price. Auctions that were inside the filter range at listing time can rise above it as bidding progresses — the scraper faithfully returns Flippa's current price in the price field, and the original asking price in buy_it_now_price. If you only want listings whose current price is inside a band, combine saleMethod: "classified" with your price filters.

Why does a record's property_type sometimes differ from the category I filtered by? Flippa's API accepts high-level category slugs for filtering (e.g. newsletter, ecommerce_store) but returns the platform / sub-type in each record's property_type field (e.g. beehiiv for a newsletter hosted on Beehiiv, shopify for a Shopify store). The filter still targets the category correctly; the output field just carries more granular platform information. If you need the high-level category for grouping, dedupe by the filter you passed in rather than by the response field.

Which status values actually return listings? Only open. Flippa's public API suppresses under_offer and closed listings entirely — querying those returns zero records. The schema still exposes them for completeness, but do not expect data back.

Which propertyType values are populated right now? ecommerce_store, saas, ios_app, android_app, domain, newsletter, service, and website all return listings. digital_product and content are valid enum values but currently return zero records — Flippa has them enabled in the filter set even though no active listings exist. The scraper handles this correctly (returns an empty dataset and exits 0).

Use cases

• Flip hunters: find under-priced listings by filtering on profit multiple and verified revenue
• Content investors: monitor the newsletter, content, and blog categories for deal flow
• SaaS acquirers: track SaaS listings filtered by MRR and age
• App buyers: scan iOS and Android app listings with verified downloads
• Market researchers: analyze pricing and multiples across industries
• Agencies: build acquisition target feeds for clients

Notes

• Pricing is configured in the Apify UI (pay-per-event or pay-per-result).
• The scraper logs progress per page and retries automatically on transient errors and rate limits.
• The daily Apify test run uses maxItems=5 against the default ecommerce search — verify it in the actor's Monitoring tab.