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Analyze bakery sales & inventory with Google Sheets & Azure GPT Chat Assistant

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Analyze bakery sales & inventory with Google Sheets & Azure GPT Chat Assistant preview
Open on n8n.io

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Bakery Data Analytics Workflow Explanation Aim The aim of the Bakery Data Analytics Workflow is to automate the process of analyzing bakery sales and stock data stored in Google Sheets. It allows b...

Best for

  • AI Chatbot automation workflows
  • intermediate n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.chattrigger, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.memorybufferwindow, n8n-nodes-base.googlesheetstool, @n8n/n8n-nodes-langchain.lmchatazureopenai, n8n-nodes-base.stickynote

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Yashraj singh sisodiya.

Original n8n.io source

1.1 Workflow description

Title
Analyze bakery sales & inventory with Google Sheets & Azure GPT Chat Assistant
Workflow name
Analyze bakery sales & inventory with Google Sheets & Azure GPT Chat Assistant

Bakery Data Analytics Workflow Explanation

Aim

The aim of the Bakery Data Analytics Workflow is to automate the process of analyzing bakery sales and stock data stored in Google Sheets. It allows bakery owners or managers to interact with an AI assistant via chat and receive clear, concise, and actionable insights about their business performance without manually reviewing spreadsheets.


Goal

The goal is to:

  • Enable users to query bakery sales and stock data through a chat interface.
  • Use an AI Agent to interpret user queries and fetch the required data.
  • Retrieve relevant sales/stock figures from a Google Sheets dataset.
  • Generate insights in plain English, with short summaries, highlights, or breakdowns.
  • Maintain conversation context so users can ask follow-up questions naturally.

This ensures that bakery owners can make quick, informed decisions about sales trends, inventory shortages, or product performance with minimal manual effort.


Requirements

The workflow relies on the following components and configurations:

n8n Platform

The automation platform hosting the workflow.

Node Requirements
  1. When chat message received (Trigger)

    • Captures user input via chat.
    • Initiates the workflow execution.
  2. AI Agent

    • Central reasoning engine.
    • Interprets queries, decides when to fetch data, and ensures professional responses.
    • Uses short, structured insights (bullets, tables, or compact summaries).
  3. Simple Memory

    • Stores short-term conversation history.
    • Maintains context across multiple user queries.
  4. Retrieve bakery data (Google Sheets)

    • Connects to a linked Google Sheets file.
    • Fetches sales/stock data (e.g., daily totals, item performance).
    • Data source: Bakery Google Sheet.
  5. Azure OpenAI Chat Model

    • Backend language model powering the AI Agent.
    • Provides natural language understanding and generates concise responses.
Credentials
  • Google Sheets OAuth2 account (for accessing bakery data).
  • Azure OpenAI API account (for AI-driven reasoning and conversation).
Input Requirements
  • User question/query via chat (e.g., “What was the best-selling pastry last week?”).
Output
  • Compact, conversational insights (totals, highlights, trends) delivered via chat.

API Usage

The workflow integrates two main APIs:

  1. Google Sheets API

    • Used by the Retrieve bakery data node.
    • Fetches structured data (sales, stock, dates) from the bakery dataset.
    • Provides the AI Agent with real-time data access.
  2. Azure OpenAI API

    • Used by the Azure OpenAI Chat Model node.
    • Powers natural conversation, ensures responses are plain English, concise, and business-focused.
    • Aligns with AI Agent rules to avoid assumptions and provide actionable insights only when asked.

Workflow Summary

The Bakery Data Analytics Workflow automates bakery performance analysis by:

  1. Triggering on chat message input.
  2. Passing the query to the AI Agent for interpretation.
  3. Using Simple Memory to track context across the conversation.
  4. Fetching relevant data from Google Sheets when needed.
  5. Leveraging Azure OpenAI to generate structured, professional responses.

This creates an interactive AI-powered assistant for bakery data, enabling quick insights into sales and inventory trends without manually combing through spreadsheets.


1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - When chat message received

Type / Role
@n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices
Version 1.3

Block 2 - AI Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 2.2

Block 3 - Simple Memory

Type / Role
@n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices
Version 1.3

Block 4 - Retrieve bakery data

Type / Role
n8n-nodes-base.googleSheetsTool - googleSheetsTool
Config choices
Version 4.7

Block 5 - Azure OpenAI Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatAzureOpenAi - lmChatAzureOpenAi
Config choices
Version 1

Block 6 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 7 - Sticky Note1

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 8 - Sticky Note2

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 9 - Sticky Note3

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 10 - Sticky Note4

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

3. Summary Table

Workflow Analyze bakery sales & inventory with Google Sheets & Azure GPT Chat Assistant
Complexity intermediate
Nodes 10
Categories AI Chatbot
Author Yashraj singh sisodiya
Published 07 Sept 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/8344/8344.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Analyze bakery sales & inventory with Google Sheets & Azure GPT Chat Assistant do?

Bakery Data Analytics Workflow Explanation Aim The aim of the Bakery Data Analytics Workflow is to automate the process of analyzing bakery sales and stock data stored in Google Sheets. It allows b...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your AI Chatbot use case.