Web dev projects

Table of Content

Table of Content

Table of Content

Business buyout automation

Designed and implemented an automated scraping and data enrichment system to aggregate business-for-sale listings from platforms including Indiabizforsale, MergerDomo, and DealStream. The solution uses dedicated, fault-tolerant scrapers to handle real-world challenges such as inconsistent page structures, pagination, missing fields, and intermittent failures. Scraped data is streamed into an n8n-based backend, where it is normalized, validated, deduplicated, and enriched to extract high-value business attributes such as industry, deal size, location, and transaction type. The system produces a clean, structured dataset tailored to downstream requirements, enabling faster deal evaluation, improved data reliability, and elimination of manual research across multiple marketplaces.

Overview

This project focuses on automating the extraction, enrichment, and consolidation of business-for-sale listings from multiple marketplaces. Dedicated scrapers were built for platforms such as Indiabizforsale, MergerDomo, and DealStream to collect raw deal data and transform it into structured, high-value intelligence through an automated backend pipeline.

What Was Built

Three independent, production-grade web scrapers were developed to extract business listings, financial details, deal descriptions, and seller metadata from the target platforms. Each scraper was designed to handle real-world scraping challenges such as inconsistent HTML structures, pagination, dynamic content, missing fields, rate limits, and intermittent failures.

The scraped data is pushed into a centralized backend workflow powered by n8n, where it acts as the trigger for downstream automation and enrichment processes.

Backend Automation & Enrichment (n8n)

n8n serves as the orchestration layer that receives raw scraper outputs and processes them through multiple enrichment steps. These include data normalization, field validation, deduplication, categorization, and extraction of key business attributes such as industry, deal size, location, and transaction type.

Additional logic is applied to compute derived values and filter listings based on relevance, ensuring that only meaningful and actionable data is retained. The enriched output represents the final, high-signal dataset required for analysis, outreach, or downstream integrations.

System Flow

  1. Scrapers extract raw business-for-sale listings from Indiabizforsale, MergerDomo, and DealStream

  2. Data is validated and structured at the scraper level to handle inconsistencies and failures

  3. Scraped payloads trigger backend workflows in n8n

  4. n8n enriches, filters, and transforms the data based on business logic

  5. Final structured output is generated containing only the required, high-value fields

Impact & Value

The system eliminates manual monitoring and data collection from multiple deal platforms, providing a single, enriched source of truth for business-for-sale opportunities. It improves data reliability, reduces human effort, and enables faster evaluation of deals by delivering clean, structured, and context-rich information ready for use in analytics, lead generation, or investment workflows.

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