Automate Web Research with Power Platform: AI-Powered Google Search Scraper

Introduction

In today’s data-driven world, extracting valuable insights from the web can be crucial for research, competitive analysis, and business intelligence. To streamline this process, I have built a Google Search Scraper solution using Microsoft Power Platform, integrating various components like Power Automate, Power Automate Desktop (RPA), AI Builder, Canvas App, and Dataverse.

This blog will walk you through the architecture, implementation, and benefits of this solution, which automates the extraction of search results, generates AI-powered summaries, and provides a user-friendly interface.

Solution Overview

The solution takes an Excel file containing search keywords as input, scrapes Google search results using Power Automate Desktop (RPA), and stores the results in Dataverse. Then, using AI Builder, it generates a short 100-word summary for the extracted data. The end users interact with the solution via a Canvas App, providing an intuitive UI for managing searches and viewing results.

Key Components Used:

• Canvas App: Frontend interface for users to upload files, track progress, and view results.
• Dataverse: Stores excel imports history, keywords, and extracted search results (Title, Description, Link, AI Summary).
• Cloud Flow 1: Extracts keywords from the uploaded Excel file and triggers the scraping process.
• Cloud Flow 2: Orchestrates RPA-based web scraping, processes results, generates AI summaries, and updates the database.
• Power Automate Desktop (RPA): Automates Google search execution and data extraction.
• AI Builder: Generates concise summaries from search results.
• Status Tracking: The system updates search status in Dataverse as “In Progress,” “Failed,” or “Completed.”

Implementation Details

Step 1: Uploading Keywords via Canvas App

Users upload an Excel file containing search keywords using the Canvas App. The app stores the upload history in Dataverse, and a cloud flow is triggered to extract keywords.

Step 2: Triggering RPA for Web Scraping

A Power Automate Cloud Flow picks up the extracted keywords and triggers a Power Automate Desktop process. This RPA flow launches a browser session, performs a Google search for each keyword, and systematically extracts relevant search results. To ensure high-quality and meaningful data, the RPA process captures only the top 3 organic search results—excluding ads and sponsored content. The extracted results, including Title, Description, and Link, are then formatted into a structured JSON payload, which is sent back to the cloud flow for further processing.

Step 3: Storing Results in Dataverse

Once the data is scraped, it is stored in Dataverse, maintaining a structured format with keyword-wise search results.

Step 4: AI-Powered Summarization

Using AI Builder, the extracted search results are processed to create a concise 100-word summary, making it easier for users to get insights at a glance.

Step 5: Updating Status

To enhance visibility into the process, a status column is added to the upload table in Dataverse. The system updates the status as:

• Pending – When the keywords are imported but the web scraping is not started yet.
• In Progress – When scraping is ongoing.
• Completed – Once results are successfully stored.
• Failed – If any error occurs during the process.

Step 6: Viewing Results in Canvas App

Once the process is complete, users can access the summarized search results via the Canvas App, which provides a user-friendly display of extracted data.

Real-World Business Use Cases

This solution can be applied across various industries to automate web research and improve decision-making:

1. Market Research & Competitive Analysis – Businesses can leverage this tool to monitor competitors, track industry trends, and analyze customer sentiment.
2. Lead Generation – Sales and marketing teams can extract company details and potential leads by searching for relevant business keywords.
3. Content Research for Blogging & SEO – Content creators can quickly gather information for blog posts, SEO strategies, and topic validation.
4. Academic & Legal Research – Researchers and legal professionals can extract insights from scholarly articles, case laws, and industry reports.
5. Investment & Financial Research – Investors can track stock market trends, company performance, and financial news in real time.

Success Story

A marketing agency integrated this solution to analyze customer sentiment on trending topics. By automating web searches and generating concise summaries, the agency reduced manual research time by 60% and improved campaign targeting effectiveness.

Demo Video

To see this solution in action, watch the demo video below:

Benefits of This Solution

✅ Automated Workflow: Eliminates manual searching and data entry.
✅ AI-Driven Insights: Summarizes large data sets into digestible insights.
✅ Scalability: Handles multiple searches efficiently.
✅ User-Friendly Interface: Canvas App provides easy access to results.
✅ Error Handling & Tracking: Status updates provide visibility into the process.

Get the Solution Package

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Frequently Asked Questions (FAQ)

Conclusion

By leveraging the Power Platform, we have created a robust, automated Google Search Scraper that simplifies web data extraction, enhances productivity, and provides AI-powered summaries. This solution can be further enhanced with Power BI for visual analytics or Power Virtual Agents for chatbot-driven insights.

If you’re looking to automate web data extraction in your organization, give this approach a try and explore the limitless possibilities with Microsoft Power Platform!

Have thoughts or questions? Drop them in the comments below!