Automated Case Study Scraping: Combining Code and AI

Build a reliable system to extract and analyze case studies from any company website by blending deterministic code with AI analysis

In this video walkthrough, we demonstrate how to create a robust system for automatically discovering and analyzing customer case studies from company websites, combining the predictability of code with the analytical power of AI.

We show how the system processes company websites through multiple sophisticated stages:

  • Initiates a broad search using SERPR API with carefully crafted Boolean search terms to capture various ways companies might label their success stories
  • Uses AI to intelligently categorize search results into individual case studies and hub pages
  • Employs web scraping to extract additional case studies from hub pages
  • Analyzes each case study to extract key information including company names, types of content, quantitative outcomes, and confidence scores
  • Combines results using code to ensure consistent, structured output that can feed into other workflows

The system demonstrates an elegant solution to a common challenge in business intelligence: how to blend deterministic code with non-deterministic AI to achieve reliable, consistent results. By using code to handle data structure and flow while leveraging AI for content analysis and categorization, we create a workflow that delivers clean, structured data about a company's successful customer relationships.Whether you're researching potential clients, analyzing competitors, or building your own market intelligence system, this walkthrough shows how to automatically gather valuable insights about a company's ideal customer profile through their published case studies.

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