Automated Deep Research with ScrapeGraphAI and Google Sheets - n8n Workflow

• Market researchers needing automated, multi-angle data collection.


• Academics or consultants requiring structured literature reviews using an n8n workflow.


• Data analysts looking for advanced web scraping and data integration n8n templates.


• Users who need to trigger complex data pipelines via API and store findings in Google Sheets.

This sophisticated n8n workflow provides an end-to-end solution for automated deep research. When a request is sent to the webhook n8n trigger, the system dynamically generates targeted search queries based on the requested depth (basic, detailed, or comprehensive). The core value lies in its multi-source scraping capability, leveraging specialized ScrapeGraphAI n8n nodes to simultaneously gather general web insights, recent news, and academic papers. This ensures comprehensive data coverage. The findings are then merged, processed, and archived systematically into a designated Google Sheets document for historical tracking and immediate reporting. This powerful n8n workflow replaces hours of manual research with a single API call, offering highly scalable automation via n8n.

The process begins with the Research Request Webhook n8n trigger, which receives a POST request defining the research topic and parameters.

1. Configuration and Query Generation: The Research Configuration Processor Code n8n node takes the request payload, validates the inputs (like topic and depth), and programmatically generates a list of focused search queries (e.g., "topic market analysis," "topic academic papers").


2. Parallel Execution: The Split Search Queries n8n node iterates through each generated query. For every query, the Query Selector n8n node prepares the data for parallel collection.


3. Multi-Source Data Collection: Three parallel ScrapeGraphAI n8n nodes execute: one for general research findings (AI Research Scraper), one specifically targeting news (News Sources Scraper), and one for academic papers (Academic Sources Scraper). Each n8n node uses a detailed prompt to ensure the output is highly structured JSON.


4. Data Consolidation: The Merge Research Sources n8n node waits for all three scraping operations to finish and combines the data into a single stream.


5. Processing and Structuring: The Research Data Processor Code n8n node cleans, structures, and validates the aggregated research findings, preparing key fields like sessionId, query, and source summaries.


6. Archival and Response: Finally, the Research Data Storage Google Sheets n8n node appends the structured results to the defined spreadsheet, and the Research Complete Response n8n node sends a confirmation status back to the initiating system. This complete n8n workflow provides robust automation, leveraging the power of n8n templates for repeatable tasks.

1. Import the n8n template: Copy the provided JSON definition and import it directly into your n8n instance.


2. Set up Credentials:

1. Configure Webhook: Activate the Research Request Webhook n8n trigger. Copy the generated webhook URL (path: /research-trigger).


2. Google Sheet Setup: Create a new Google Sheet named Research_Data (or update the n8n node parameters with your desired sheet name/ID) and ensure it has necessary header columns.


3. Test the n8n workflow: Send a POST request containing a JSON payload with the topic and desired research parameters to the webhook URL to start this powerful n8n workflow.

Research Request Webhook (n8n Trigger): Serves as the starting point (n8n trigger). Configured for POST requests on the /research-trigger path, initiating the deep research pipeline.
Research Configuration Processor (Code n8n node): A crucial custom n8n node that handles logic. It validates and defaults input parameters, generates complex search queries based on depth, and creates a unique sessionId for tracking.
Split Search Queries (Split In Batches n8n node): Manages the flow by separating the generated list of search queries so subsequent scraping operations are run sequentially for each query.
AI Research Scraper (ScrapeGraphAI n8n node): Performs general, structured web scraping using AI. Key Configuration: User Prompt demands highly structured JSON output including key findings, statistics, and a credibility assessment.
News Sources Scraper & Academic Sources Scraper (ScrapeGraphAI n8n nodes): Specialized scraping n8n nodes targeting specific URLs (Google News and Google Scholar) to ensure relevant source material is collected.
Merge Research Sources (Merge n8n node): A flow control n8n node that combines the results of the three parallel scraping branches before final processing.
Research Data Processor (Code n8n node): Structures the messy, merged JSON data into a clean object, consolidating findings, news, and academic papers for optimal storage.
Research Data Storage (Google Sheets n8n node): The final action n8n node. It uses the 'Append' operation to save the structured research findings to the defined Google Sheets document, completing this data collection n8n workflow.