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Run AI-powered market research with Groq, OpenAI, Documentero and Gmail

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Run AI-powered market research with Groq, OpenAI, Documentero and Gmail preview
Open on n8n.io

Important notice

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

1. Workflow Overview

Description This n8n template demonstrates how to build an AI powered Market Research Assistant using a multi agent workflow. It helps you get a 360 degree view of a product idea or research topic ...

Best for

  • Market Research automation workflows
  • AI Chatbot automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.chattrigger, @n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.merge, @n8n/n8n-nodes-langchain.lmchatgroq, n8n-nodes-preview-documentero.documentero, @n8n/n8n-nodes-langchain.lmchatopenai

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title
Run AI-powered market research with Groq, OpenAI, Documentero and Gmail
Workflow name
Run AI-powered market research with Groq, OpenAI, Documentero and Gmail

Description

This n8n template demonstrates how to build an AI-powered Market Research Assistant using a multi-agent workflow. It helps you get a 360-degree view of a product idea or research topic by analysing:

  • Customer insights and pain points
  • Market size and macro/micro-economic trends
  • Competitive landscape and alternatives The workflow mirrors how product managers and strategy teams conduct discovery — by breaking down research into parallel workstreams and then synthesizing insights into a single narrative.

How it works

  1. Planner Agent
The main agent receives your research topic as input and defines:
    • Research objective
    • Key areas of focus (Customer, Market, Competition)
    • Assumptions and constraints
  2. Parallel Research Agents
Based on the planner’s output, three specialist agents run in parallel:
    • Customer Insights Agent
Researches public sources such as articles and forums to infer customer behaviour, pain points, and existing tools.
    • Market Scan Agent
Analyses macro-economic and micro-economic trends, estimates TAM/SAM/SOM, and highlights key risks and assumptions.
    • Competitor Insights Agent
Identifies existing competitors and substitutes and summarises how they are positioned in the market.
  3. Synthesis Agent
The outputs from all research agents are consolidated and analysed by a synthesis agent, which produces a market discovery memo.
  4. Final Output
The discovery memo is generated as a document and sent to your email.

How to use

  • Trigger the workflow via the chat message node.
  • Provide your research topic or product idea, along with optional context such as target market.
  • The workflow runs automatically and delivers a structured discovery memo to your inbox.

Setup Steps

  • API credentials for:
    • Groq or OpenAI (LLM)
    • Documentero (document generation)
  • A configured Documentero template
  • Gmail OAuth or email credentials for delivery of memo

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 1.4

Block 2 - Simple Memory

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

Block 3 - Planner Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3

Block 4 - Simple Memory1

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

Block 5 - Market Scan Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3

Block 6 - Simple Memory2

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

Block 7 - Customer Insights Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3

Block 8 - Competitor Insights Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3

Block 9 - Simple Memory3

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

Block 10 - Structured Output Parser1

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

Block 11 - Structured Output Parser2

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

Block 12 - Structured Output Parser3

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

Block 13 - Structured Output Parser4

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

Block 14 - Merge

Type / Role
n8n-nodes-base.merge - merge
Config choices
Version 3.2

Block 15 - Synthesis Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3

Block 16 - Simple Memory4

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

Block 17 - Groq Chat Model1

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

Block 18 - Groq Chat Model2

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

Block 19 - Groq Chat Model3

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

Block 20 - Groq Chat Model4

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

Block 21 - Documentero

Type / Role
n8n-nodes-preview-documentero.documentero - documentero
Config choices
Version 1

Block 22 - OpenAI Chat Model3

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

Block 23 - Send a message

Type / Role
n8n-nodes-base.gmail - gmail
Config choices
Version 2.2

Block 24 - Format Data for Documentero

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Showing the first 24 of 30 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow Run AI-powered market research with Groq, OpenAI, Documentero and Gmail
Complexity advanced
Nodes 30
Categories Market Research, AI Chatbot
Author Monisha
Published 28 Dec 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/12236/12236.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 Run AI-powered market research with Groq, OpenAI, Documentero and Gmail do?

Description This n8n template demonstrates how to build an AI powered Market Research Assistant using a multi agent workflow. It helps you get a 360 degree view of a product idea or research topic ...

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 Market Research, AI Chatbot use case.