Acquire.com Scraper

Acquire.com Scraper extracts structured startup acquisition listings, helping analysts, investors, and researchers access financial metrics, company profiles, and deal insights from a leading acquisition marketplace. It simplifies business discovery and evaluation by delivering clean, analysis-ready data at scale.

     

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Introduction

This project collects publicly available startup listings and converts them into structured datasets suitable for research and analysis. It removes the friction of manual browsing and enables consistent access to acquisition-related business intelligence. It is designed for investors, analysts, brokers, and researchers who need reliable startup marketplace data.

Startup Acquisition Intelligence

• Collects publicly listed business acquisition data
• Normalizes financial, customer, and company metrics
• Supports multiple startup categories in one run
• Designed for analytics, valuation modeling, and research
• Outputs structured, machine-readable datasets

Features

Feature	Description
Business Listing Extraction	Collects complete public startup listings with structured fields.
Financial Metrics Capture	Extracts revenue, profit, and valuation-related data points.
Customer Metrics	Gathers ARR, customer counts, and growth indicators.
Company Profiles	Includes business model, tech stack, and growth opportunities.
Acquisition Insights	Captures selling reasons and financing information.
Multi-Category Support	Processes SaaS, AI, mobile apps, ecommerce, and more.

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What Data This Scraper Extracts

Field Name	Field Description
title	Listing page title of the business.
url	Direct link to the business listing.
header	Business category or listing type.
country	Country where the business operates.
price	Asking price of the business.
priceReasoning	Explanation behind the valuation or pricing logic.
performance	Revenue and profit performance metrics.
customerMetrics	Customer counts, ARR, churn, and growth indicators.
companyOverview	Business model, tech stack, and growth opportunities.
acquisitionDetails	Selling reasons and financing details.

---

Example Output

[
  {
    "title": "Acquire, the #1 Startup Acquisition Marketplace",
    "url": "https://app.acquire.com/startup/example",
    "header": "AI startup",
    "country": "United States",
    "price": "$895k",
    "priceReasoning": "Valuation-Backed pricing with negotiation room.",
    "performance": [
      {
        "title": "TTM revenue",
        "value": "$450k"
      },
      {
        "title": "TTM profit",
        "value": "$225k"
      }
    ],
    "customerMetrics": [
      {
        "title": "Customers",
        "value": "< 10"
      },
      {
        "title": "Annual recurring revenue",
        "value": "$0"
      }
    ],
    "companyOverview": [
      {
        "title": "Business model",
        "bulletList": ["B2B", "Licensing"]
      },
      {
        "title": "Tech stack",
        "bulletList": ["Wix", "Google Cloud"]
      }
    ],
    "acquisitionDetails": [
      {
        "title": "Selling reasoning",
        "bulletList": ["Financial gain", "New venture"]
      }
    ]
  }
]

---

Directory Structure Tree

Acquire.com Scraper/
├── src/
│   ├── main.py
│   ├── extractors/
│   │   ├── listings.py
│   │   ├── financials.py
│   │   └── company_profile.py
│   ├── utils/
│   │   ├── normalizer.py
│   │   └── validators.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── requirements.txt
└── README.md

---

Use Cases

• Investors use it to identify acquisition-ready startups so they can evaluate deals faster.
• Market analysts use it to track valuation trends across startup categories for research insights.
• Business brokers use it to aggregate listings so they can compare opportunities efficiently.
• Data scientists use it to build valuation models and predictive analytics.
• Entrepreneurs use it to analyze comparable exits before selling their business.

---

FAQs

Does this scraper access private listings? No. It only extracts publicly available startup listings and does not access private or gated data.

Can multiple business categories be processed together? Yes. Multiple business types can be included in a single run for broader market analysis.

Is the data suitable for financial modeling? Yes. Financial and customer metrics are normalized for analytics and valuation workflows.

What are the main limitations? Listings without public visibility or missing financial data will not be included.

---

Performance Benchmarks and Results

Primary Metric: Processes hundreds of public listings per run with consistent field coverage.

Reliability Metric: Maintains high success rates when collecting publicly available data.

Efficiency Metric: Optimized extraction minimizes redundant requests and processing time.

Quality Metric: Delivers structured, well-normalized datasets with strong field completeness.

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