Natural language Google Sheets data analysis with Gemini AI
This n8n workflow template creates an efficient data analysis system that uses Google Gemini AI to interpret user questions about spreadsheet data and processes them through a specialized sub-workflow for optimized token usage and faster responses.
What This Workflow Does
- Smart Query Parsing: Uses Gemini AI to understand natural language questions about your data
- Efficient Processing: Routes calculations through a dedicated sub-workflow to minimize token consumption
- Structured Output: Automatically identifies the column, aggregation type, and grouping levels from user queries
- Multiple Aggregation Types: Supports sum, average, count, count distinct, min, and max operations
- Flexible Grouping: Can aggregate data by single or multiple dimensions
- Token Optimization: Processes large datasets without overwhelming AI context limits
Tools Used
- Google Gemini Chat Model - Natural language query understanding and response formatting
- Google Sheets Tool - Data access and column metadata extraction
- Execute Workflow - Sub-workflow processing for data calculations
- Structured Output Parser - Converts AI responses to actionable parameters
- Memory Buffer Window - Basic conversation context management
- Switch Node - Routes to appropriate aggregation method
- Summarize Nodes - Performs various data aggregations
📋 MAIN WORKFLOW - Query Parser
What This Workflow Does
The main workflow receives natural language questions from users and converts them into structured parameters that the sub-workflow can process. It uses Google Gemini AI to understand the intent and extract the necessary information.
Prerequisites for Main Workflow
- Google Cloud Platform account with Gemini API access
- Google account with access to Google Sheets
- n8n instance (cloud or self-hosted)
Main Workflow Setup Instructions
1. Import the Main Workflow
- Copy the main workflow JSON provided
- In your n8n instance, go to Workflows → Import from JSON
- Paste the JSON and click Import
- Save with name: "Gemini Data Query Parser"
2. Set Up Google Gemini Connection
- Go to Google AI Studio
- Sign in with your Google account
- Go to Get API Key section
- Create a new API key or use an existing one
- Copy the API key
Configure in n8n:
- Click on Google Gemini Chat Model node
- Click Create New Credential
- Select Google PaLM API
- Paste your API key
- Save the credential
3. Set Up Google Sheets Connection for Main Workflow
- Go to Google Cloud Console
- Create a new project or select existing one
- Enable the Google Sheets API
- Create OAuth 2.0 Client ID credentials
- In n8n, click on Get Column Info node
- Create Google Sheets OAuth2 API credential
- Complete OAuth flow
4. Configure Your Data Source
Option A: Use Sample Data
- The workflow is pre-configured for: Sample Marketing Data
- Make a copy to your Google Drive
Option B: Use Your Own Sheet
- Update Get Column Info node with your Sheet ID
- Ensure you have a "Columns" sheet for metadata
- Update sheet references as needed
5. Set Up Workflow Trigger
- Configure how you want to trigger this workflow (webhook, manual, etc.)
- The workflow will output structured JSON for the sub-workflow
⚙️ SUB-WORKFLOW - Data Processor
What This Workflow Does
The sub-workflow receives structured parameters from the main workflow and performs the actual data calculations. It handles fetching data, routing to appropriate aggregation methods, and formatting results.
Sub-Workflow Setup Instructions
1. Import the Sub-Workflow
- Create a new workflow in n8n
- Copy the sub-workflow JSON (embedded in the Execute Workflow node)
- Import as a separate workflow
- Save with name: "Data Processing Sub-Workflow"
2. Configure Google Sheets Connection for Sub-Workflow
- Apply the same Google Sheets OAuth2 credential you created for the main workflow
- Update the Get Data node with your Sheet ID
- Ensure it points to your data sheet (e.g., "Data" sheet)
3. Configure Google Gemini for Output Formatting
- Apply the same Gemini API credential to the Google Gemini Chat Model1 node
- This handles final result formatting
4. Link Workflows Together
- In the main workflow, find the Execute Workflow - Summarize Data node
- Update the workflow reference to point to your sub-workflow
- Ensure the sub-workflow is set to accept execution from other workflows
Sub-Workflow Components
- When Executed by Another Workflow: Trigger that receives parameters
- Get Data: Fetches all data from Google Sheets
- Type of Aggregation: Switch node that routes based on aggregation type
- Multiple Summarize Nodes: Handle different aggregation types (sum, avg, count, etc.)
- Bring All Data Together: Combines results from different aggregation paths
- Write into Table Output: Formats final results using Gemini AI
Example Usage
Once both workflows are set up, you can ask questions like:
Overall Metrics:
- "Show total Spend ($)"
- "Show total Clicks"
- "Show average Conversions"
Single Dimension:
- "Show total Spend ($) by Channel"
- "Show total Clicks by Campaign"
Two Dimensions:
- "Show total Spend ($) by Channel and Campaign"
- "Show average Clicks by Channel and Campaign"
Data Flow Between Workflows
- Main Workflow: User question → Gemini AI → Structured JSON output
- Sub-Workflow: Receives JSON → Fetches data → Performs calculations → Returns formatted table
Contact Information
For support, customization, or questions about this template:
- Email: robert@ynteractive.com
- LinkedIn: Robert Breen
Need help implementing these workflows, want to remove limitations, or require custom modifications? Reach out for professional n8n automation services and AI integration support.
Natural Language Google Sheets Data Analysis with Gemini AI
This n8n workflow empowers users to perform data analysis on Google Sheets using natural language queries, leveraging the power of Google Gemini AI. It acts as a conversational interface, allowing you to ask questions about your spreadsheet data and receive intelligent, structured responses.
What it does
This workflow simplifies data analysis by:
- Receiving a natural language query: It starts by accepting a user's question or command about their Google Sheet data (triggered by an external workflow).
- Activating an AI Agent: An AI Agent, powered by LangChain, is initialized to understand the user's intent and formulate a plan.
- Utilizing Google Sheets as a Tool: The AI Agent is equipped with the ability to read and interact with a specified Google Sheet.
- Maintaining Conversation Context: A simple memory buffer ensures the AI Agent remembers previous interactions within the same conversation, allowing for follow-up questions.
- Processing with Google Gemini: The core intelligence comes from the Google Gemini Chat Model, which processes the natural language input and the data from Google Sheets.
- Structuring Output: A Structured Output Parser ensures that the AI's response is formatted in a consistent and usable manner.
- Aggregating Results: It aggregates the processed information, likely combining data extracted from the sheet with the AI's analysis.
- Summarizing Information: The workflow can summarize the findings, providing concise answers to complex queries.
- Conditional Logic for Response: A Switch node allows for branching logic, potentially handling different types of queries or response formats.
- Returning the Analysis: The final, structured analysis is returned to the calling workflow.
Prerequisites/Requirements
- n8n Instance: A running instance of n8n.
- Google Sheets Account: Access to a Google Sheet containing the data you wish to analyze.
- Google Gemini API Key: An API key for the Google Gemini Chat Model.
- n8n LangChain Nodes: Ensure the
@n8n/n8n-nodes-langchainpackage is installed in your n8n instance.
Setup/Usage
- Import the Workflow:
- Download the provided JSON file.
- In your n8n instance, go to "Workflows" and click "New".
- Click the "Import from JSON" button and paste the workflow JSON or upload the file.
- Configure Credentials:
- Google Sheets: Configure your Google Sheets credential. This typically involves OAuth2 authentication to grant n8n access to your Google Sheets.
- Google Gemini Chat Model: Configure your Google Gemini API key credential.
- Configure Nodes:
- Google Sheets (Node 18): Specify the Spreadsheet ID and Sheet Name that you want the AI to analyze.
- AI Agent (Node 1119): Ensure the "Tools" are correctly configured to include the Google Sheets node. Verify the "Language Model" is set to the Google Gemini Chat Model.
- Simple Memory (Node 1163): This node provides conversational memory. No specific configuration is usually needed unless you want to adjust memory parameters.
- Structured Output Parser (Node 1179): This node defines the expected structure of the AI's output. Review and adjust the schema if your desired output format differs.
- Trigger the Workflow: This workflow is designed to be executed by another workflow using the "Execute Workflow Trigger" node (Node 837). You will need a separate workflow that calls this one, passing the natural language query as input.
- The calling workflow should use an "Execute Sub-workflow" node (Node 111) and select this workflow.
- Pass the user's natural language query into the "Execute Sub-workflow" node's input.
- Activate the Workflow: Once configured, activate the workflow by toggling the "Active" switch in the top right corner of the workflow editor.
Once set up, you can send natural language queries (e.g., "What is the average sales for Q1?", "Show me all products with low stock", "Who are our top 5 customers?") via the calling workflow, and this workflow will process them using Gemini AI to provide structured answers from your Google Sheet.
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