Acquire.com Leads Scraper & Anonymous Listing Unmasker (Startup Contact Finder)

Find the real startup behind anonymous Acquire.com listings and export enriched lead data including company website URL, business description, emails, phone numbers, and social profiles.

This Apify actor is built for teams doing startup acquisition sourcing, acquisition deal sourcing, buyer-side research, private equity outreach, and competitive intelligence.

If you are searching for an Acquire.com scraper, Acquire.com lead generator, Acquire startup contact finder, Acquire.com listing unmasker, or a way to identify the company behind an anonymous Acquire listing, this actor is purpose-built for that workflow.

It is optimized for a simple outcome: turn an anonymous listing into a ranked shortlist of likely startups with evidence and contact paths.

What This Actor Does

This actor analyzes anonymous Acquire.com listings and returns structured, enriched dataset items for each listing, including:

• Acquire listing metadata (slug, url, headline, type, status, listed_at)
• Candidate matches for the likely real startup behind the listing (shortlist format)
• Company website URL
• Company description
• Contact details (emails, phones, socials) when available
• Match reason and confidence score (0-100 style ranking)

In short: it turns anonymous marketplace listings into usable startup leads for outreach and research.

Why Use This (And Who It Is For)

This actor is ideal for:

• Startup acquirers building a pipeline of targets from Acquire.com
• Acquisition advisors / brokers enriching listings before outreach
• Private equity / holdco operators sourcing small business and SaaS acquisition targets
• Analysts / researchers mapping anonymous listings to real companies
• Growth teams running founder outreach or partnership campaigns

Common use cases

• Build a list of recently listed Acquire startups and their real domains
• Export contact information for outbound email campaigns
• Monitor newly listed startups (listed_at_desc) for faster outreach
• Research older inventory (listed_at_asc) for overlooked opportunities
• Feed enriched data into a CRM, spreadsheet, or internal sourcing dashboard

Built for practical deal sourcing

This actor is especially useful when you need to move from anonymous teaser to actionable lead quickly:

• Shortlist likely companies instead of manually guessing from listing clues
• Prioritize using confidence scores before opening dozens of tabs
• Review the reasoning behind each candidate for faster analyst validation
• Route high-confidence matches to outbound or buyer-side teams

Why This Actor Ranks Better in Your Workflow

Many tools stop at scraping listing headlines. This actor is optimized for lead generation outcomes, not just raw scraping:

• It returns candidate company matches (not just the anonymous listing)
• It includes contact fields for outreach (emails, phones, socials)
• It includes reasoning + score so the output is explainable and easy to triage
• It supports simple, repeatable inputs for ops teams (maxItems, order)
• It outputs clean JSON that is easy to export to CSV / Excel / CRM

How It Works

1. The actor fetches Acquire.com listings using the selected sort order.
2. It enriches each listing with likely startup candidates, confidence scores, and reasoning.
3. It collects available contact paths like emails, phones, and social profiles.
4. It stores enriched JSON items in the dataset for export or integration.

The actor input is intentionally minimal so non-technical users can run it quickly.

Quick Start (Apify)

1. Open the actor and click Try for free.
2. Set maxItems and choose order.
3. Run the actor.
4. Open the Dataset tab and export results (JSON / CSV / Excel).
5. Filter by candidate score / reasoning to prioritize outreach.

Important

• The actor input supports only maxItems and order.
• If order is not set, the actor defaults to listed_at_desc (newest first).
• No extra technical configuration is required in actor input beyond maxItems and order.
• No Acquire.com session export or account cookies are required as actor input.

Input

This actor supports only 2 input fields. maxItems is required and order is optional:

Parameter	Type	Required	Description
maxItems	Integer	Yes	Maximum number of startup listings to return.
order	String	No	Listing date sort order: listed_at_desc (newest first) or listed_at_asc (oldest first). Defaults to listed_at_desc.

Example input (Newest first)

{
  "maxItems": 100,
  "order": "listed_at_desc"
}

Example input (Oldest first)

{
  "maxItems": 250,
  "order": "listed_at_asc"
}

Output (Dataset)

The actor stores enriched JSON items directly in the dataset. Each item contains the original listing plus a candidates array with likely matched startups and contact details.

This raw-output approach is ideal if you want to preserve the full evidence payload for downstream scoring, QA, or CRM enrichment workflows.

Output fields (top level)

• slug — Acquire listing identifier
• url — Acquire listing URL
• headline — Listing headline (e.g. "$45K MRR B2B SaaS")
• type — Listing type/category (e.g. SaaS)
• status — Listing status
• listed_at — Listing timestamp
• data — Raw listing metadata payload
• candidates — Matched real startup candidates (with website + contacts)

Many runs return a small ranked shortlist of candidates per listing, making review faster than broad fuzzy search results.

Candidate fields (inside candidates[])

• name — Company/startup name
• url — Company website URL
• description — Company description
• reason — Why the match was selected
• score — Match confidence score (helps prioritize review/outreach)
• emails — Public email addresses (if found)
• phones — Public phone numbers (if found)
• socials — Social profile URLs (if found)

Example output (shortened, with more listing + candidate fields)

{
  "slug": "nku2ldTQ.../4ZaK3nvi...",
  "url": "https://app.acquire.com/startup/nku2ldTQ.../4ZaK3nvi...",
  "headline": "All-in-One White-Label Agency SaaS — 5,000+ Customers, $717K TTM Revenue",
  "type": "SaaS",
  "status": "completed",
  "listed_at": "2026-02-26T03:46:03.569Z",
  "data": {
    "listingHeadline": "All-in-One White-Label Agency SaaS — 5,000+ Customers, $717K TTM Revenue",
    "askingPrice": "336000",
    "location": "United States",
    "customers": "251-500",
    "businessVerified": true,
    "financialKeywords": ["Bootstrapped"],
    "growthOpportunityHighlights": [
      "Focus on SEO",
      "Increase digital marketing",
      "Improve conversion rates"
    ],
    "highlights": [
      "Website",
      "Domain",
      "Customers",
      "Codebase"
    ],
    "insights": {
      "views": 25
    }
  },
  "candidates": [
    {
      "name": "AgencyBox",
      "url": "https://agencybox.com",
      "description": "A white-label platform and training program that helps entrepreneurs launch a digital agency by reselling vetted services.",
      "reason": "Matches the 'Agency in a Box' positioning, white-label service model, and listing signals such as niche and scale.",
      "score": 90,
      "emails": ["support@agencybox.com", "hello@agencybox.com"],
      "phones": ["+1 702 555 0142"],
      "socials": [
        "https://www.linkedin.com/company/agencybox",
        "https://x.com/agencybox"
      ]
    }
  ]
}

The exact fields inside data can vary by listing. Some listings include rich business details such as asking price, customer ranges, keywords, highlights, metrics snapshots, and growth notes.

SEO-Friendly Use Cases (What People Search For)

This actor is useful if you are looking for:

• Acquire.com scraper
• Acquire.com listings scraper
• Acquire startup leads scraper
• Acquire anonymous listing unmasker
• Startup contact finder for Acquire.com
• Acquire SaaS leads export
• acquisition lead generation from Acquire marketplace
• Startup acquisition sourcing automation
• Founder email finder for Acquire listings
• Acquire.com competitor research / deal flow enrichment
• ranked candidates for anonymous startup listings
• confidence score startup match finder
• Acquire listing reasoning and evidence enrichment

Tips for Better Results

• Use listed_at_desc to prioritize newly listed startups and contact them early.
• Use listed_at_asc to find older listings that may be less competitive.
• Start with a smaller maxItems batch to validate output formatting for your CRM.
• Export to CSV and filter by candidate score to prioritize high-confidence matches.
• Keep low-score candidates too if you do analyst review; reasoning can still surface useful signals.

Integrations & Workflows

Popular follow-up workflows:

• Export dataset to CSV / Excel for manual review
• Push records into a CRM (HubSpot, Pipedrive, Salesforce)
• Run a follow-up website contact enrichment or verification workflow
• Build a deal sourcing dashboard with scheduled runs

FAQ

Does this actor scrape Acquire.com directly?

Yes. It processes Acquire.com listings and returns enriched results with likely startup matches, confidence scores, reasoning, and contact details when available.

Can I sort by newest or oldest listings?

Yes. Use order:

• listed_at_desc = newest first
• listed_at_asc = oldest first

Are contact details always available?

No. Contact fields depend on what was found for each matched startup. Some listings may have websites but no public email/phone, while others include multiple contact channels.

How should I prioritize candidates?

Start with the highest score, then review the reason field to confirm the match logic. This gives you a quick, evidence-based review workflow instead of manual guesswork.

Legal & Disclaimer

• Use this actor responsibly and comply with applicable laws, platform terms, and outreach regulations.
• Contact information should be used for legitimate business purposes and in compliance with anti-spam and privacy laws.
• This actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Acquire.com.