Empire Flippers Scraper — Businesses for Sale & Sold Deals

What it does

Online businesses listed on Empire Flippers — For Sale, Pending Sold and Sold — with asking price, monthly and annual multiple, average monthly profit, revenue and expenses, and the 12-month P&L and traffic series. Fill rates are published per listing status, because a Sold listing and a For Sale listing carry very different amounts of data.

{
  "listing_number": 97317,
  "title": "$29.8K Per Month eCommerce Business in the Art Niche",
  "status": "For Sale",
  "price": 215015,
  "currency": "USD",
  "avg_monthly_net_profit": 8532,
  "avg_monthly_revenue": 29773,
  "monthly_multiple": 25,
  "annual_multiple": 2.1,
  "profit_margin_pct": 29,
  "niches": ["Art", "Apparel & Accessories", "Lifestyle"],
  "monetizations": ["eCommerce", "Amazon FBM"],
  "business_age_years": 12.3,
  "monthly_financials": [
    { "month": "2025-09", "net_profit": 126.91, "revenue": 30745.77, "expenses": 30618.86 }
  ],
  "monthly_traffic": [
    {
      "month": "2025-09",
      "page_views": 179668,
      "unique_users": 26406,
      "traffic_channels": [
        { "channel": "Paid Social", "unique_users": 13871, "page_views": 105005, "users_pct": 52.53 }
      ]
    }
  ],
  "url": "https://empireflippers.com/listing/97317/"
}

Why this one

Use cases

• Build a valuation comparables set from Sold deals, by niche and monetization, with the multiple and monthly profit each one was listed at.
• Watch new For Sale listings by niche, price or profit with `sortBy: newest` on a schedule, and diff by `listing_id`.
• Study asking multiples by monetization model — Amazon FBA, SaaS, content, eCommerce — across 2,674 sold listings.
• Load the 12-month P&L series into a spreadsheet with `outputType: monthlyMetrics` to compare revenue and margin trajectories.
• Screen Amazon businesses by SKU count, TACoS and COGS where the listing publishes them.

Input

Every field has a default, and the defaults are deliberately small so a first run is cheap enough to inspect before you commit to a sweep. This table mirrors the Actor's own input schema field for field.

Output and fill rates

A field being in the schema is not the same as it having a value. The percentages below were counted on real runs; the sample sizes are in Measurements. Anything not listed here is not promised.

Every key is always present. A field that exists but is empty comes back as explicit null, so a parser never has to guess.

Datasets

Different record types go to different datasets, so the main table never carries columns that are blank on most rows.

Pricing

Pay per delivered result. Charges are applied as each row is produced rather than in a lump at the end, so an aborted run bills only for what it actually gave you.

Measurements

Each figure is shown with the method that produced it. A benchmark without a method is a marketing claim wearing a number's clothes.

What it will not do

Stated plainly so you can judge fit before spending anything.

• The Actor documents a Sold row's `price` as the final asking price. Treat it as an asking figure: nothing in the output is labelled as the price the business changed hands at.
• Anything Empire Flippers keeps behind Unlock and its NDA — the business URL, the detailed P&L, access to the seller — is out of reach, because reaching it requires an account and an accepted agreement.
• The monthly traffic series was filled on 74.9% of 2,877 listings and traffic channels on 4.8%; for For Sale listings both were 36.7% of 180.
• Model-specific fields are empty for other models: MRR was filled on 34.4% and churn on 40.6% of the 64 SaaS listings, and on about 1% of the catalogue. They are delivered as null, never omitted.
• The tech stack needs one extra request per listing and was found on 16.7% of 30 For Sale listings sampled and 0 of 20 Sold ones.
• No rate limit appeared at 50 requests in about a minute. That shows the limit is not reached at that pace, not that none exists.
• A keyword shaped like a URL or HTML makes the origin firewall answer with a fixed HTTP 403, so such keywords are rejected as an input error before any request is made.

Privacy

• Empire Flippers keeps sellers anonymous: none of the 145 data paths in the source identifies a seller, and 0 of 2,877 listings exposed a personal contact on 23 September 2026.
• As a safeguard, any email that looks personal and any phone number in free text is redacted unless `includePrivateSellerContact` is set to true. Business role mailboxes such as support@ are kept.
• The seller interview link, present on 32.3% of listings, is a public video Empire Flippers itself publishes.
• Removal requests: privacy@actorstack.dev

See also the data removal process.

Guides for this Actor

• Scrape Empire FlippersThe whole Empire Flippers catalogue — For Sale, Pending Sold and Sold — in fifteen requests, which filters actually narrow the result, and how much of each row is filled depending on its status.