⚖️ FTC Enforcement Actions Scraper — Antitrust, consumer-protection, and Section 5 cases — straight from FTC.gov

Scrape the Federal Trade Commission Cases & Proceedings library — antitrust merger challenges, consumer-protection cases, Section 5 (unfair or deceptive practices) actions, and FTC Act matters. Each row is one FTC case page, parsed into structured JSON.

One actor. One token. Regulator-direct data delivered in structured JSON.

Why This Actor

• No seat licence. Westlaw and LexisNexis keep FTC matters behind general-purpose legal subscriptions. This actor is pay-per-record.
• Regulator-direct. Read straight from ftc.gov on demand — no intermediary index, no end-of-day refresh lag.
• Keyword + date filtering. Search the case index by keyword and narrow by filing date.
• Press releases linked. Related FTC press-release titles are surfaced per case.

Feature	This Actor ⚖️	LexisNexis	Westlaw	Cornell LII
Pricing model	Pay-per-result (cents per record)	Per-seat license $5K-30K/yr	Per-seat license $10K-25K/yr	Per-seat license $10K-30K/yr
Real-time freshness	Read live from ftc.gov per run	End-of-day refresh	Hourly refresh	Hourly refresh
Data source	Direct from regulator	Mixed proprietary + scraped	Mixed proprietary + scraped	Mixed proprietary + scraped
API access	REST + webhooks built in	Add-on; extra licence	Add-on; extra licence	Limited
Setup time	5 minutes (token + run)	Procurement + onboarding	Procurement + onboarding	Procurement + onboarding

What You Get

Every dataset row contains exactly these fields, populated wherever the FTC case page provides them:

Field	Description
case_url	Canonical ftc.gov case page URL
title	Case title as published
list_title	Title as it appears in the case index
long_title	Full caption (e.g. "In the Matter of …, Respondents.")
case_status	FTC case status (e.g. Pending, Closed)
matter_number	FTC matter number
docket_number	Docket number, when the matter has one
federal_court	Federal court, for cases filed in court
filing_date	Date published on the case page (YYYY-MM-DD)
press_releases	List of related FTC press-release titles
description	Short case description
summary	Case Summary body text (up to 2,000 characters)
source	Always ftc.gov

Fields the FTC page does not publish come back as null — the schema is stable across runs, so it is safe to load into Snowflake, BigQuery, or Postgres without re-mapping.

Use Cases

• M&A antitrust counsel — track FTC merger challenges and the conduct theories being litigated.
• Compliance officers — build a precedent library of FTC consumer-protection actions in your industry.
• Plaintiff law firms — source FTC matters as predicate for follow-on private actions.
• Investors — monitor FTC enforcement risk against portfolio companies.
• Journalists and academics — build a beat-feed or an empirical enforcement dataset.

Quick Start

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("nexgendata/ftc-enforcement-actions-scraper").call(run_input={
    "query": "",
    "maxCases": 10,
})

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

curl -X POST "https://api.apify.com/v2/acts/nexgendata~ftc-enforcement-actions-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"maxCases": 10}'

Input

Input	Meaning
query	Optional keyword searched against the FTC case index. Leave blank for the most recent cases.
dateFrom / dateTo	Optional inclusive YYYY-MM-DD filters on the case's published date.
maxCases	Maximum rows to return (1–500). One case = one row.

Pricing

This actor uses pay-per-event pricing on Apify:

• FTC case record — $0.05 per row pushed to the dataset (primary event).
• Actor start — $0.00005 per run, charged per GB of memory, minimum one event.

Nothing else is charged. If the run returns 0 rows — because your keyword or date range matched nothing — no result events are charged, and the run's status message explains why. If ftc.gov is unreachable or returns a bot-check page, the run fails with a status message naming the cause rather than finishing green and empty.

Sister Actors in the NexGenData Fleet

Use case	Actor
CFPB consumer complaints in financial services	cfpb-consumer-complaints-scraper
Federal court dockets via CourtListener	courtlistener-federal-docket-scraper
EPA enforcement and environmental violations	epa-echo-enforcement-scraper
Federal Register rule filings	federal-register-rules-scraper
SEC 8-K material events	sec-form-8k-material-events-scraper
LDA lobbying disclosure filings	lda-lobbying-disclosure-scraper

Browse the full catalog at https://apify.com/nexgendata?fpr=2ayu9b.

FAQ

Q: Is this legal? A: Yes. FTC enforcement actions and consent decrees are public records.

Q: How fresh is the data? A: The actor reads ftc.gov at run time, so it reflects the site as published.

Q: Can I filter by case type? A: Not as a dedicated field — use query (for example merger, privacy, COPPA) to search the index.

Q: Are settlement amounts and penalties extracted as fields? A: No. Monetary terms appear inside summary and description free text where the FTC publishes them; they are not parsed into numeric fields.

Q: Do you cover state-AG actions? A: No — this actor is FTC only.

Q: What's historical coverage? A: The FTC's online case database goes back to the 1990s; older matters carry summary metadata only.

About NexGenData

NexGenData publishes 200+ buyer-intent Apify actors covering SEC filings, federal regulatory data (EPA, FTC, CFPB, FEC, IRS 990, FAA), private-market intelligence, stock screeners, B2B lead generation, and competitive intelligence. All actors are pay-per-result with no seat licences and no minimum commitments.

Browse the full catalog at https://apify.com/nexgendata?fpr=2ayu9b.