Company Acquisitions & M&A Tracker: Deal Data

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Acquisitions and mergers. Each record has the acquirer, target, deal value, payment type, and date. Every deal is matched across the outlets that reported it, with both sides resolved to canonical companies, so you get one row per deal instead of one per article. Set your filters, run it, and pay only for the records you get back. No API key, no signup, no sales call.

Use it for acquisitions data, M&A data, mergers and acquisitions API, deal data, company acquisition signals.

What you get

Every record carries all of the below. The table view shows the columns that scan best; the full record is in the JSON, CSV, and Excel exports.

• Acquirer and target. both sides come as a full company: name, domain, description, LinkedIn URL and handle, HQ city and country, industry group, industry sub-tags, verticals, employee count, founded year, and business model.
• Deal. amount in USD, the original currency and amount as reported, payment type, whether it was a merger, announced date, closing date, and the date we first saw it.

Results export to JSON, CSV, or Excel, or stream straight to your database via the Apify API.

Common use cases

• Sales and prospecting. Find accounts that just raised, and reach them while the news is fresh.
• Market research. Track acquisitions by industry, country, and date.
• Data enrichment. Add acquisitions to your CRM or warehouse.
• Deal sourcing. Scan new activity, for investors and corp dev teams.

Filters

Input	Description
maxItems	Max records (default 100)
cursor	Advanced: resume from a previous run's NEXT_CURSOR to paginate ahead
since	Only records on or after this date (YYYY-MM-DD), e.g. 2026-01-01. ISO-8601 timestamps also work. This is what makes the Actor a feed rather than an export: schedule it daily with since set to the day before, and each run returns only what is new.
countries	Filter by company HQ country. Select several to cover a whole region in one run instead of one run per country. About a quarter of companies have no HQ country on record, so add "Not disclosed" to keep those deals in.
industryGroups	Filter by industry group (LinkedIn-style labels, exact match). Select several to cover related industries in one run. About a fifth of companies have no industry on record, so add "unknown" to keep those deals in.
naicsCode	Filter by NAICS 2022 code. Matches the code and everything beneath it, so picking a sector like Manufacturing (31-33) returns every manufacturer under it. Pick "Not classified" for companies we could not classify.
verticals	Filter by high-level sector (AI, fintech, climate, etc.). Broader than industry group; matches any company mapped to the selected vertical. Pick "unknown" for companies with no sector on record. They are excluded from any other sector filter.
minAmountUsd	Minimum amount in USD.
maxAmountUsd	Maximum amount in USD.
paymentType	Filter by acquisition payment type.
isMerger	Show only mergers.

Leave everything empty to get the newest records first, or narrow by the filters above. One run fetches up to Max records for you, so there is no paging to do by hand.

Run it on a schedule

Most people want acquisitions as they happen rather than one export. Set your filters, save the run as a task, and schedule it daily. Set since to the day before and each run returns only what is new, so you pay for new records instead of re-fetching the same ones.

That is the difference between a one-off list and a live feed, and it is the way this Actor is meant to be used. Apify's own Schedules run the task for you; every run appends to its own dataset, and you can send each one onward with an integration to Slack, Google Sheets, a webhook, or your warehouse.

If a run ever stops early, at a charge limit for example, it saves a NEXT_CURSOR in its key-value store. Pass that back as cursor to pick up exactly where it stopped. It is a resume point, not something you need for normal use.

Example output

{
  "id": "019fdf47-1f66-7308-bd76-ddc0e2d8754c",
  "acquirer": {
    "id": "019df869-68ec-7e7c-958b-eb38d3451164",
    "name": "BioMarin",
    "domain": "biomarin.com",
    "description": "Biopharmaceutical innovation for serious diseases.",
    "linkedinUrl": "https://www.linkedin.com/company/biomarin",
    "hqCity": "San Rafael",
    "hqCountry": {
      "code": "US",
      "name": "United States"
    },
    "industryGroup": "Biotechnology Research",
    "naicsCode": "5417",
    "naicsLevel": 4,
    "industrySubTags": [
      "biotechnology"
    ],
    "verticals": [
      "healthcare"
    ],
    "employeeCountBucket": "1001-5000",
    "foundedYear": 1997
  },
  "target": {
    "id": "019df869-6834-7304-b77e-a9fbece4b10a",
    "name": "Amicus Therapeutics",
    "domain": "amicusrx.com",
    "description": "Rare disease drug development company.",
    "linkedinUrl": "https://www.linkedin.com/company/amicus-therapeutics",
    "hqCity": "Philadelphia",
    "hqCountry": {
      "code": "US",
      "name": "United States"
    },
    "employeeCountBucket": "201-500",
    "foundedYear": 2002
  },
  "dealAmountUsd": null,
  "dealAmountOriginalCurrency": null,
  "paymentType": "undisclosed",
  "isMerger": false,
  "announcedAt": "2026-08-08",
  "closingAt": "2026-04-27",
  "discoveredAt": "2026-08-08T02:50:08.090Z"
}

What it costs

You pay per record returned, $0.07 each, dropping to $0.06 on higher Apify plans. Nothing is charged for a run that returns nothing, and filters that match no records cost you nothing at all.

Records	Cost
10	$0.70
100	$7.00
1,000	$70.00
10,000	$700.00

Set Max records to cap any single run, so a run can never cost more than you intended.

What this Actor does not cover

It tracks acquisitions for companies that raise, get acquired, or hire — venture-backed and growth companies, worldwide. It is not a general business directory: local service businesses, restaurants, airports, and similar establishments are not in here. If you need every business in a city, this is the wrong tool.

FAQ

What data does this actor return?

Acquisitions and mergers. Each record has the acquirer, target, deal value, payment type, and date. Fields: Acquirer, Target, Deal (USD), Payment, Announced, Merger, Target country, Target industry, Target NAICS, Target employees, Acquirer LinkedIn. Each one is matched to a canonical company.

Is this a Crunchbase, PitchBook, or Coresignal alternative?

Yes. It is a self-serve, API-first alternative to Crunchbase, PitchBook, Coresignal, and Harmonic, with no annual contract and no sales call.

How fresh is the data?

Most records are available the same day they are announced. Across the last 30 days, the median gap between a public announcement and the record being available was under one day.

Can I monitor acquisitions on a schedule?

Yes. Save your filters as a task and use Apify's scheduler to run it daily or weekly. Each run stores a NEXT_CURSOR. Pass it to the next run to pick up where the last one stopped, so you only pay for records you have not seen yet.

Some records have an empty field. Can I still get those?

Yes. Not every announcement states every detail, and where a value was never disclosed the field is left empty rather than guessed. Filters that can be empty offer a Not disclosed option (HQ country and industry, plus funding round where it applies). Select it to include those records instead of dropping them from a filtered run.

How is the data deduplicated?

Each real-world event is matched across every outlet that reported it and resolved to one canonical company (and investors), so you never get the same round or deal twice.

How do I get the next batch of records?

Each run saves a NEXT_CURSOR to its key-value store. Pass it as the cursor input on the next run to continue where you left off. For new records over time, use the since filter.

Is there a free way to try it?

Free Apify accounts get a one-time sample of 50 records from this Actor, so you can see the shape and quality of the data before paying. It is per Actor, it does not reset, and it is meant for evaluation rather than for collecting a dataset.

Beyond the sample this Actor is for paid Apify plans, where you pay only for the records you get back.

Terms of use

Records returned by this Actor are licensed for use inside your own products and workflows. Building on the data is encouraged. Reselling, redistributing or republishing the records as data, in raw or substantially raw form, is not permitted, and neither is systematic extraction to reconstruct the dataset.

Full terms: datahyena.com/terms

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