Flippa Marketplace Scraper

The Flippa deal-finding and market monitoring API — not just a scraper.

Scrape Flippa.com listings with ROI scoring, undervaluation detection, price-drop tracking, sold-listing research, direct URL enrichment, and automatic export to Slack, Airtable, Notion, Google Sheets, and any webhook.

Built for acquisition investors, deal teams, brokers, and anyone who wants Flippa's data piped into their own workflow.

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Why this actor vs. the alternatives

Feature	This actor
ROI score (0–100) with transparent formula	✅
Undervaluation flagging with per-type benchmarks	✅
Price-drop tracking across runs	✅
Sold listings research	✅
Direct URL enrichment (enrich specific listings)	✅
Mixed inputs: search filters + individual URLs in one run	✅
Confidence score (how complete is each listing's data)	✅
Flagged reasons per listing (why it was flagged)	✅
Normalized enums for type, sale method, monetization	✅
Output modes: Full / ETL / Alerts-only	✅
Native Slack, Airtable, Notion, Google Sheets, webhook	✅
Summary stats record per run	✅
Trust/badge indicators (verified, editor's choice, managed)	✅
Auction/offer state fields	✅
Traffic, domain age, seller rating	✅ (with detail pages)

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What data is extracted

Core fields (every listing)

Field	Description
url	Direct link to the listing
title	Listing headline
description	Business description excerpt
askingPrice	Asking price (e.g. "USD $118,000")
monthlyProfit	Net monthly profit (e.g. "USD $3,956 p/mo")
monthlyRevenue	Monthly revenue when disclosed
profitMultiple	Valuation multiple (e.g. "3.4x Profit")
revenueMultiple	Revenue multiple (e.g. "1.2x Revenue")
propertyType	Normalized enum: SaaS, Ecommerce, Amazon FBA, Content / Blog, Affiliate, Newsletter, Domain, App, Marketplace, Directory, Services, Forum / Community
monetizationType	How the business makes money
category	Industry/niche
listingAge	Age of the business
saleMethod	Normalized enum: Auction, Buy It Now, Classified
isVerified	Verified listing badge
isEditorChoice	Editor's Choice badge
isManagedByFlippa	Managed by Flippa badge
isSold	true if from Flippa's sold listings section
scrapedAt	ISO timestamp

ROI & analysis fields (when roiScoring is enabled)

Field	Description
roiScore	0–100. Higher = faster payback. 100 = under 0yr payback, 0 = 5yr+ payback
paybackYears	Asking price ÷ annual profit. Years to recoup investment
isUndervalued	true if payback is below the threshold for this business type
roiBenchmarkUsed	The payback threshold that determined isUndervalued
roiExplanation	Human-readable reason: e.g. "Payback 2.1yr vs 3.5yr benchmark for SaaS"
confidenceScore	0–100. How many of the 8 key fields (price, profit, type, category, etc.) are populated
flaggedReasons	Array of reasons this listing was flagged: undervalued, price_drop, new_listing, sold, low_confidence

Price tracking fields (when trackPriceDrops is enabled)

Field	Description
priceDropped	true if price is lower than when last seen
priceDrop	Dollar amount of the reduction
priceHistory	Full price history array: [{ price, priceNum, date }] — one entry per price change
firstSeenAt	ISO timestamp of when this listing was first scraped
lastSeenAt	ISO timestamp of when this listing was last seen in a run
relisted	true if this listing was previously marked as removed and has reappeared

Removal detection records (when trackPriceDrops is enabled)

At the end of each run, listings that were previously tracked but not seen in the current run are flagged. A record is pushed to the dataset with:

Field	Description
_isRemoval	true — use this to identify removal event records
likelyRemoved	true
removedAt	ISO timestamp of when removal was detected
lastSeenAt	When it was last seen before disappearing
firstSeenAt	When it was first seen
askingPrice	Last known asking price
priceHistory	Full price history up to removal
flaggedReasons	["likely_removed"]

Detail page fields (when scrapeDetailPages is enabled)

Field	Description
yearEstablished	Year the business was founded
sellerRating	Seller reputation score
monthlyVisitors	Monthly traffic when disclosed
annualOrganicTraffic	Annual organic visits when disclosed
domainAge	Age of the domain (e.g. "7 years")
offersCount	Number of active offers
bidsCount	Number of bids (auction listings)
daysRemaining	Days left in auction or listing window
annualRevenue	Annual revenue figure when disclosed

Summary record (end of every run)

Field	Description
_isSummary	true — use this to filter out summary records
totalScraped	Total listings saved this run
undervaluedCount	Undervalued listings count
priceDropCount	Price-drop listings count
likelyRemovedCount	Listings not seen this run, newly flagged as likely removed
avgAskingPrice	Average asking price across saved listings
avgPaybackYears	Average payback period
avgConfidenceScore	Average data completeness score
typeBreakdown	Count by normalized property type
flagBreakdown	Count by each flag reason
outputMode	Which output mode was used
runCompletedAt	ISO timestamp

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ROI score explained

roiScore = max(0, min(100, round(100 - (paybackYears / 5) * 100)))

• 100 = 0 years payback (extremely underpriced)
• 60 = 2 years payback (strong deal)
• 30 = 3.5 years payback (fair market for SaaS)
• 0 = 5+ years payback (expensive)

The roiBenchmarkUsed field shows the exact threshold used for isUndervalued, and roiExplanation gives a plain-English explanation for every listing.

Per-type defaults:

Type	Default benchmark
SaaS	3.5 years
Ecommerce / FBA	2.5 years
Content / Blog / Affiliate / Newsletter	3.0 years
Other	3.0 years

All thresholds are configurable in the actor input.

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Example output

{
  "url": "https://flippa.com/12283554",
  "title": "GovTech SaaS — 96% margins, $29.9K revenue, evergreen webinar funnel",
  "description": "$29.9K revenue, 96% margins, custom GovTech SaaS with 1M+ B2G contact database",
  "askingPrice": "USD $114,999",
  "monthlyProfit": "USD $2,396 p/mo",
  "monthlyRevenue": null,
  "profitMultiple": "3.4x Profit",
  "revenueMultiple": "3.3x Revenue",
  "propertyType": "SaaS",
  "monetizationType": "Services & Subscriptions",
  "category": "Business",
  "listingAge": "5 years",
  "saleMethod": "Buy It Now",
  "isVerified": true,
  "isEditorChoice": false,
  "isManagedByFlippa": false,
  "isSold": false,
  "roiScore": 20,
  "paybackYears": 4.0,
  "isUndervalued": false,
  "roiBenchmarkUsed": 3.5,
  "roiExplanation": "Payback 4.0yr vs 3.5yr benchmark for SaaS",
  "confidenceScore": 87,
  "flaggedReasons": [],
  "priceDropped": false,
  "priceDrop": null,
  "firstSeenAt": "2026-03-20T09:00:00.000Z",
  "scrapedAt": "2026-04-02T04:00:00.000Z"
}

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Input options

Inputs & Filters

Parameter	Type	Default	Description
listingUrls	Array	[]	Individual Flippa listing URLs or IDs to enrich directly. Can be mixed with category filters in the same run
outputMode	Enum	full	full = all fields, etl = nulls stripped, alerts = only flagged listings
propertyType	Array	[]	Filter by: website, fba, ios_app, android_app, domain, business, newsletter
siteType	Array	[]	Filter by: saas, ecommerce, content, blog, dropship, affiliate, etc.
minPrice	Integer	—	Minimum asking price (USD)
maxPrice	Integer	—	Maximum asking price (USD)
minMonthlyProfit	Integer	—	Minimum monthly profit (USD)
maxMonthlyProfit	Integer	—	Maximum monthly profit (USD)
minRoiScore	Integer	—	Minimum ROI score 0–100
titleKeywords	Array	[]	Only return listings whose title contains any of these keywords
descriptionKeywords	Array	[]	Only return listings whose description contains any of these keywords
maxResults	Integer	50	Maximum total listings to save (up to 1,000)

ROI & Alerts

Parameter	Type	Default	Description
roiScoring	Boolean	true	Add ROI fields to every listing
onlyUndervalued	Boolean	false	Only save undervalued listings
undervaluedMultipleThreshold	Number	—	Global payback override — overrides all per-type thresholds
saasBenchmarkYears	Number	3.5	Payback threshold for SaaS
ecommerceBenchmarkYears	Number	2.5	Payback threshold for Ecommerce / FBA
contentBenchmarkYears	Number	3.0	Payback threshold for content, blog, affiliate, newsletter
defaultBenchmarkYears	Number	3.0	Fallback for all other types
onlyNewListings	Boolean	false	Skip listings seen in previous runs
includeSoldListings	Boolean	false	Also scrape sold listings (tagged isSold: true)
trackPriceDrops	Boolean	false	Detect and flag price reductions across runs
scrapeDetailPages	Boolean	false	Visit each listing page for traffic, domain age, seller rating, auction state

Integrations

Parameter	Type	Description
webhookUrl	String	POST to this URL at end of run (Zapier, Make, n8n)
slackWebhookUrl	String	Send formatted Block Kit report to Slack
airtableApiKey	String (secret)	Airtable Personal Access Token
airtableBaseId	String	Airtable Base ID
airtableTableName	String	Table name (default: Flippa Listings)
notionApiKey	String (secret)	Notion Internal Integration Token
notionDatabaseId	String	Notion database ID
googleServiceAccountJson	String (secret)	Google service account JSON key
googleSheetsId	String	Google Sheets spreadsheet ID
googleSheetName	String	Sheet tab name (default: Flippa Listings)

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Use cases

Deal sourcing Find undervalued businesses matching your acquisition criteria. Set siteType: ["saas"], maxPrice: 200000, onlyUndervalued: true.

Keyword targeting Use titleKeywords: ["AI", "recurring", "MRR"] to surface only businesses matching your thesis.

Undervalued alerts Schedule daily runs with onlyUndervalued: true + onlyNewListings: true + slackWebhookUrl. Get notified only when a new undervalued listing appears.

Price drop alerts Enable trackPriceDrops: true. Combine with outputMode: "alerts" to save only listings where something changed.

Enrich a shortlist Paste 10 listing URLs into listingUrls. Get a full structured dataset back in seconds — without manual browsing.

Sold listings research Enable includeSoldListings: true to see what actually transacted and at what prices. Useful for benchmarking current asks.

ETL pipeline Set outputMode: "etl" — every listing has null fields stripped, giving clean rows ready for Postgres, BigQuery, or Airtable without empty columns.

Acquisition watchlist Run on a schedule with onlyNewListings: true + trackPriceDrops: true. Build a persistent history of listings you're monitoring. Each listing accumulates a full priceHistory array across runs. Listings that disappear from Flippa are automatically flagged as likelyRemoved and pushed as removal-event records. Listings that reappear after removal are flagged as relisted — a strong signal of a motivated seller.

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Output modes

Mode	What gets saved	Best for
full	Every listing, all fields including nulls	Default, maximum data
etl	Every listing, null/empty fields removed	Databases, spreadsheets, Airtable
alerts	Only listings with at least one flaggedReason	Scheduled alert runs, Slack notifications

flaggedReasons values: undervalued, price_drop, relisted, new_listing, sold, low_confidence, likely_removed

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Direct listing URL mode

Instead of (or in addition to) category scraping, you can pass individual listing URLs:

{
  "listingUrls": [
    "https://flippa.com/12345678",
    "https://flippa.com/12283554",
    "11223344"
  ]
}

Bare IDs (numbers) are automatically expanded to full Flippa URLs. Each listing is fully extracted from its detail page and returns the same schema as a search-scraped listing — including ROI fields, confidence score, flagged reasons, and all trust/traffic indicators.

Mix with search filters in the same run: if you also set siteType: ["saas"], the actor will scrape the SaaS category AND enrich your direct URLs in one run.

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Setting up the deal alert workflow

1. Set these inputs:
   • onlyUndervalued: true
   • onlyNewListings: true
   • trackPriceDrops: true
   • outputMode: "alerts"
   • slackWebhookUrl or webhookUrl
2. Tune your benchmarks (e.g. saasBenchmarkYears: 3.0 for stricter SaaS deals)
3. Optionally add titleKeywords: ["recurring", "MRR", "B2B"] to narrow the niche
4. Go to Actors → Schedules in the Apify console and set it to run daily
5. You'll receive a Slack message only when a new undervalued or price-dropped listing appears

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Integrations

Webhook (n8n / Zapier / Make / custom)

Posts this payload at end of run:

{
  "source": "flippa-marketplace-scraper",
  "runId": "abc123",
  "timestamp": "2026-04-01T00:00:00.000Z",
  "totalScraped": 50,
  "count": 50,
  "listings": [ ... ]
}

• Zapier → "Webhooks by Zapier" → "Catch Hook"
• Make → "Webhooks" → "Custom webhook"
• n8n → "Webhook" trigger node

Slack

Get an Incoming Webhook URL at api.slack.com/messaging/webhooks. Each run sends a Block Kit formatted card with run stats and the top 5 deals by ROI score.

Airtable

1. Create a Personal Access Token at airtable.com/account with data.records:write scope
2. Create a table named Flippa Listings with these columns:

Column	Type
Title	Single line text
URL	URL
Asking Price	Single line text
Monthly Profit	Single line text
Monthly Revenue	Single line text
Profit Multiple	Single line text
Revenue Multiple	Single line text
Type	Single line text
Monetization	Single line text
Category	Single line text
Listing Age	Single line text
Sale Method	Single line text
Description	Long text
Scraped At	Single line text
ROI Score	Number
Payback (yrs)	Number
Undervalued	Checkbox
Confidence Score	Number
Price Dropped	Checkbox
Price Drop ($)	Number
Sold	Checkbox

3. Find your Base ID at airtable.com/developers/web/api/introduction

Notion

1. Go to notion.so/my-integrations → New integration → copy the Internal Integration Token
2. Create a database with matching properties (see Airtable table above for field names/types; use Select for Type, Monetization, Category, Sale Method)
3. Share the database with your integration (··· → Connections)
4. Copy the database ID from the URL

Google Sheets

1. Enable the Sheets API at console.cloud.google.com → create a Service Account → download JSON key
2. Share your sheet with the service account email (Editor access)
3. Paste the full JSON into googleServiceAccountJson
4. Copy the spreadsheet ID from the URL

The actor writes a header row on the first run, then appends rows on subsequent runs.

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Pricing

$0.01 per listing — flat rate, all features included.

• 50 listings = $0.50
• 500 listings = $5.00
• 1,000 listings = $10.00

Apify platform usage (compute + residential proxy bandwidth) is billed separately. Most runs of 50–200 listings cost under $0.50 in platform fees.

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Tips

• Leave all filters empty + set maxResults: 200 for a broad market sweep
• Combine siteType: ["saas"] + maxPrice: 100000 + minRoiScore: 50 to instantly surface fast-payback SaaS under $100K
• outputMode: "etl" is the cleanest option for piping data into databases — no empty columns
• Use listingUrls to enrich a specific shortlist without running a full category scrape
• Enable scrapeDetailPages only when you need traffic/domain/seller data — it roughly doubles run time
• trackPriceDrops is most useful on a recurring schedule — the first run just stores baseline prices
• Use confidenceScore to filter out listings where Flippa hides key data behind NDA: minConfidenceScore isn't an input filter yet, but you can post-filter in your downstream tool

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Notes

• Revenue and profit figures marked "Confidential" by sellers on Flippa are not accessible and are not scraped
• Residential proxies are required — Flippa blocks datacenter IPs on its listing routes
• Sold listing prices populate the askingPrice field (Flippa shows sale price in the same position)
• Flippa's site structure may change; if fields stop populating, leave a review and we'll update selectors
• The _isSummary: true record at the end of each dataset is a run-level stats row — filter it out in downstream tools if needed