{
  "workflow": {
    "id": 5430,
    "name": "Market research & business case generator with GPT-4o, Perplexity & Claude",
    "views": 4459,
    "recentViews": 1,
    "totalViews": 4459,
    "createdAt": "2025-06-28T10:25:17.885Z",
    "description": "*This workflow contains community nodes that are only compatible with the self-hosted version of n8n.* \n\n🧠 Market Research & Business Case Study Generator\nCategory: AI + Research | GPT + Perplexity | Business Strategy\nSkill Level: Intermediate\nUse Case: Market Research, Business Planning, Strategic Analysis\n\n📌 Description:\nThis template automates the creation of comprehensive, data-backed business case studies—perfect for entrepreneurs, analysts, consultants, and market researchers.\n\nFor more of such build + step-by-step video tutorials, check out:\nhttps://www.youtube.com/@Automatewithmarc\n\nJust send a simple message like:\n\n“Give me a market opportunity analysis of a bicycle rental business in North Africa.”\n\nAnd the workflow does the rest. It scopes your research topic, performs live web research, and crafts a well-structured 1500-word business case study—all automatically saved to Google Docs.\n\n🔧 How It Works:\n🟢 Chat Trigger:\nStart the workflow by sending a prompt via the built-in Chat interface (Langchain Chat Trigger).\n\n🧭 Research Scope Definer (GPT-4o):\nBreaks down the user input into structured components like industry, geography, trends, and challenges.\n\n🌐 Deep Research (Perplexity Sonar):\nPerforms live research to retrieve relevant industry data, consumer trends, competitive insights, and more.\n\n📘 Business Case Writer (Claude Sonnet):\nSynthesizes the findings into a detailed case study with sections including:\nExecutive Summary\nMarket Overview\nOpportunity Analysis\nCompetitive Landscape\nRisks & Challenges\nStrategic Recommendations\nConclusion\n📄 Google Docs Integration:\nThe final output is appended to a connected Google Doc, so all your insights are neatly stored and ready to share.\n🧰 Tools Used:\nOpenAI GPT-4o\nPerplexity Sonar Deep Research\nAnthropic Claude Sonnet\nGoogle Docs\nChat Trigger\n✅ Ideal For:\nBusiness consultants & strategy teams\nMarket researchers & analysts\nStartup founders & product managers\nEducators & MBA students",
    "workflow": {
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      "meta": {
        "instanceId": "1c7b08fed4406d546caf4a44e8b942ca317e7e207bb9a5701955a1a6e1ce1843",
        "templateCredsSetupCompleted": true
      },
      "name": "Market Research Generator",
      "tags": [],
      "nodes": [
        {
          "id": "76a873cb-d035-4ca4-8ca9-ca9d2b1d3aa1",
          "name": "When chat message received",
          "type": "@n8n/n8n-nodes-langchain.chatTrigger",
          "position": [
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            -60
          ],
          "webhookId": "ef1cfdf4-c68f-44d6-8600-1ea3b9fd2025",
          "parameters": {
            "options": {}
          },
          "typeVersion": 1.1
        },
        {
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          "name": "Anthropic Chat Model",
          "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
          "position": [
            580,
            120
          ],
          "parameters": {
            "model": {
              "__rl": true,
              "mode": "list",
              "value": "claude-sonnet-4-20250514",
              "cachedResultName": "Claude 4 Sonnet"
            },
            "options": {}
          },
          "credentials": {},
          "typeVersion": 1.3
        },
        {
          "id": "ce9f1ce5-2e12-4acc-ad9c-f92ba13ca246",
          "name": "Google Docs",
          "type": "n8n-nodes-base.googleDocs",
          "position": [
            820,
            -60
          ],
          "parameters": {
            "actionsUi": {
              "actionFields": [
                {
                  "text": "={{ $json.text }}",
                  "action": "insert"
                }
              ]
            },
            "operation": "update",
            "documentURL": "Redacted"
          },
          "credentials": {},
          "typeVersion": 2
        },
        {
          "id": "7932ae33-d1e4-4bb8-b38e-91b74435cb5f",
          "name": "Sticky Note",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -340,
            -180
          ],
          "parameters": {
            "width": 220,
            "height": 500,
            "content": "Chat Input Trigger"
          },
          "typeVersion": 1
        },
        {
          "id": "0a490125-3a86-43cf-83c5-1b436e54e7ff",
          "name": "Sticky Note1",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -100,
            -180
          ],
          "parameters": {
            "color": 5,
            "width": 300,
            "height": 500,
            "content": "Define Research Scope"
          },
          "typeVersion": 1
        },
        {
          "id": "09e33798-af03-45bf-b0a0-a01aa654d8e3",
          "name": "Research Scope Definer Agent",
          "type": "@n8n/n8n-nodes-langchain.openAi",
          "position": [
            -80,
            -60
          ],
          "parameters": {
            "modelId": {
              "__rl": true,
              "mode": "list",
              "value": "chatgpt-4o-latest",
              "cachedResultName": "CHATGPT-4O-LATEST"
            },
            "options": {},
            "messages": {
              "values": [
                {
                  "content": "={{ $json.chatInput }}"
                },
                {
                  "role": "system",
                  "content": "You are a market research planner, and a Perplexity (research) prompt agent.\n\nYour task is to take the following user query and define a structured scope of research to guide AI agents. Break it down into the following components:\n1. Industry/Business Type\n2. Geographic Focus\n3. Key Trends to Research\n4. Potential Opportunities/Challenges\n5. Suggested Data Sources (public reports, industry benchmarks, etc.)\n\nOutput a prompt meant for Perplexity research node based on the components."
                }
              ]
            }
          },
          "credentials": {},
          "typeVersion": 1.8
        },
        {
          "id": "17d56e9a-735f-4195-963b-e5939a596728",
          "name": "Sticky Note2",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            220,
            -180
          ],
          "parameters": {
            "color": 2,
            "width": 220,
            "height": 500,
            "content": "Perplexity Deep Research"
          },
          "typeVersion": 1
        },
        {
          "id": "16ca83ec-c18d-4196-8122-0ca4dfeb0871",
          "name": "Sticky Note3",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            460,
            -180
          ],
          "parameters": {
            "color": 5,
            "width": 300,
            "height": 500,
            "content": "Business Case Builder"
          },
          "typeVersion": 1
        },
        {
          "id": "4794c40e-9eef-4c91-9d31-56c07072537c",
          "name": "Perplexity Business Case Deep Research",
          "type": "n8n-nodes-base.perplexity",
          "position": [
            280,
            -60
          ],
          "parameters": {
            "model": "sonar-deep-research",
            "options": {},
            "messages": {
              "message": [
                {
                  "role": "system",
                  "content": "You are a professional market analyst with access to real-time data and reports.\n\nYour task is to conduct deep web research based on the following structured research scope. Provide a concise, well-cited summary for each of the following areas:\n- Industry trends\n- Consumer behavior\n- Competitive landscape\n- Regulatory or environmental factors\n- Key statistics and data\n\nUse reliable sources (government reports, industry publications, global databases). Include in-text citation links in markdown format.\n\nPresent the research summary in clear sections with headings.\n"
                },
                {
                  "content": "={{ $json.message.content }}"
                }
              ]
            },
            "requestOptions": {}
          },
          "credentials": {},
          "typeVersion": 1
        },
        {
          "id": "2de9f3f6-5e61-47c1-842d-c7bf996d4a1b",
          "name": "Claude Business Case Writer",
          "type": "@n8n/n8n-nodes-langchain.chainLlm",
          "position": [
            480,
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          ],
          "parameters": {
            "text": "={{ $json.choices[0].message.content }}",
            "batching": {},
            "messages": {
              "messageValues": [
                {
                  "message": "You are a business strategy consultant writing a professional market opportunity case study. You will receive user input from a Perplexity node which includes the thinking steps. exclude the content of the thinking steps, which is usually the content between <think> at the beginning of Perplexity's output. Use the structured topic scope and supporting research provided to write a well-organized, 1500-word case study. Your case study must include:  1. Executive Summary   2. Market Overview   3. Opportunity Analysis   4. Competitive Landscape   5. Challenges and Risks   6. Strategic Recommendations   7. Conclusion    Maintain a formal and analytical tone. Use section headers. Ensure insights are backed by the research provided.  "
                }
              ]
            },
            "promptType": "define"
          },
          "typeVersion": 1.7
        },
        {
          "id": "dbc5fc4a-3f45-45f6-a34c-c302900dedd0",
          "name": "Sticky Note4",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            780,
            -180
          ],
          "parameters": {
            "color": 3,
            "width": 300,
            "height": 500,
            "content": "Business Case Output on Google Docs"
          },
          "typeVersion": 1
        },
        {
          "id": "756b169a-3f46-4671-a8fe-62d7732a3911",
          "name": "Sticky Note5",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -1340,
            -240
          ],
          "parameters": {
            "color": 3,
            "width": 980,
            "height": 1000,
            "content": "🧠 Market Research Case Study Generator\nCategory: AI + Research | GPT + Perplexity | Business Strategy\nSkill Level: Intermediate\nUse Case: Market Research, Business Planning, Strategic Analysis\n\n📌 Description:\nThis template automates the creation of comprehensive, data-backed business case studies—perfect for entrepreneurs, analysts, consultants, and market researchers.\n\nFor more of such build + step-by-step video tutorials, check out:\nhttps://www.youtube.com/@Automatewithmarc\n\nJust send a simple message like:\n\n“Give me a market opportunity analysis of a bicycle rental business in North Africa.”\n\nAnd the workflow does the rest. It scopes your research topic, performs live web research, and crafts a well-structured 1500-word business case study—all automatically saved to Google Docs.\n\n🔧 How It Works:\n🟢 Chat Trigger:\nStart the workflow by sending a prompt via the built-in Chat interface (Langchain Chat Trigger).\n\n🧭 Research Scope Definer (GPT-4o):\nBreaks down the user input into structured components like industry, geography, trends, and challenges.\n\n🌐 Deep Research (Perplexity Sonar):\nPerforms live research to retrieve relevant industry data, consumer trends, competitive insights, and more.\n\n📘 Business Case Writer (Claude Sonnet):\nSynthesizes the findings into a detailed case study with sections including:\nExecutive Summary\nMarket Overview\nOpportunity Analysis\nCompetitive Landscape\nRisks & Challenges\nStrategic Recommendations\nConclusion\n📄 Google Docs Integration:\nThe final output is appended to a connected Google Doc, so all your insights are neatly stored and ready to share.\n🧰 Tools Used:\nOpenAI GPT-4o\nPerplexity Sonar Deep Research\nAnthropic Claude Sonnet\nGoogle Docs\nChat Trigger\n✅ Ideal For:\nBusiness consultants & strategy teams\nMarket researchers & analysts\nStartup founders & product managers\nEducators & MBA students"
          },
          "typeVersion": 1
        }
      ],
      "active": false,
      "pinData": {},
      "settings": {
        "executionOrder": "v1"
      },
      "versionId": "4122d186-b3c0-46d0-8a74-fdb918dc2ceb",
      "connections": {
        "Anthropic Chat Model": {
          "ai_languageModel": [
            [
              {
                "node": "Claude Business Case Writer",
                "type": "ai_languageModel",
                "index": 0
              }
            ]
          ]
        },
        "When chat message received": {
          "main": [
            [
              {
                "node": "Research Scope Definer Agent",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Claude Business Case Writer": {
          "main": [
            [
              {
                "node": "Google Docs",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Research Scope Definer Agent": {
          "main": [
            [
              {
                "node": "Perplexity Business Case Deep Research",
                "type": "main",
                "index": 0
              }
            ]
          ]
        },
        "Perplexity Business Case Deep Research": {
          "main": [
            [
              {
                "node": "Claude Business Case Writer",
                "type": "main",
                "index": 0
              }
            ]
          ]
        }
      }
    },
    "lastUpdatedBy": 51,
    "workflowInfo": {
      "nodeCount": 12,
      "nodeTypes": {
        "n8n-nodes-base.googleDocs": {
          "count": 1
        },
        "n8n-nodes-base.perplexity": {
          "count": 1
        },
        "n8n-nodes-base.stickyNote": {
          "count": 6
        },
        "@n8n/n8n-nodes-langchain.openAi": {
          "count": 1
        },
        "@n8n/n8n-nodes-langchain.chainLlm": {
          "count": 1
        },
        "@n8n/n8n-nodes-langchain.chatTrigger": {
          "count": 1
        },
        "@n8n/n8n-nodes-langchain.lmChatAnthropic": {
          "count": 1
        }
      }
    },
    "status": "published",
    "user": {
      "name": "Automate With Marc",
      "username": "marconi",
      "bio": "Automating Start-Up and Business processes. \nHelping non-techies understand and leverage Agentic AI with easy to understand step-by-step tutorials.\nCheck out my educational content:\nhttps://www.youtube.com/@Automatewithmarc\n",
      "verified": true,
      "links": [
        "https://www.youtube.com/@Automatewithmarc"
      ],
      "avatar": "https://gravatar.com/avatar/b9654a0dd147e6f3fa7e6eb601b6572b8051c8ab4cb693774451adf9a6294798?r=pg&d=retro&size=200"
    },
    "nodes": [
      {
        "id": 495,
        "icon": "file:googleDocs.svg",
        "name": "n8n-nodes-base.googleDocs",
        "codex": {
          "data": {
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.googledocs/"
                }
              ],
              "credentialDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/credentials/google/oauth-single-service/"
                }
              ]
            },
            "categories": [
              "Miscellaneous"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0"
          }
        },
        "group": "[\"input\"]",
        "defaults": {
          "name": "Google Docs"
        },
        "iconData": {
          "type": "file",
          "fileBuffer": "data:image/svg+xml;base64,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"
        },
        "displayName": "Google Docs",
        "typeVersion": 2,
        "nodeCategories": [
          {
            "id": 11,
            "name": "Miscellaneous"
          }
        ]
      },
      {
        "id": 565,
        "icon": "fa:sticky-note",
        "name": "n8n-nodes-base.stickyNote",
        "codex": {
          "data": {
            "alias": [
              "Comments",
              "Notes",
              "Sticky"
            ],
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers"
              ]
            }
          }
        },
        "group": "[\"input\"]",
        "defaults": {
          "name": "Sticky Note",
          "color": "#FFD233"
        },
        "iconData": {
          "icon": "sticky-note",
          "type": "icon"
        },
        "displayName": "Sticky Note",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 1123,
        "icon": "fa:link",
        "name": "@n8n/n8n-nodes-langchain.chainLlm",
        "codex": {
          "data": {
            "alias": [
              "LangChain"
            ],
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainllm/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Chains",
                "Root Nodes"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Basic LLM Chain",
          "color": "#909298"
        },
        "iconData": {
          "icon": "link",
          "type": "icon"
        },
        "displayName": "Basic LLM Chain",
        "typeVersion": 2,
        "nodeCategories": [
          {
            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      },
      {
        "id": 1145,
        "icon": "file:anthropic.svg",
        "name": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
        "codex": {
          "data": {
            "alias": [
              "claude",
              "sonnet",
              "opus"
            ],
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatanthropic/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Language Models",
                "Root Nodes"
              ],
              "Language Models": [
                "Chat Models (Recommended)"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Anthropic Chat Model"
        },
        "iconData": {
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        },
        "displayName": "Anthropic Chat Model",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      },
      {
        "id": 1247,
        "icon": "fa:comments",
        "name": "@n8n/n8n-nodes-langchain.chatTrigger",
        "codex": {
          "data": {
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.chattrigger/"
                }
              ]
            },
            "categories": [
              "Core Nodes",
              "Langchain"
            ]
          }
        },
        "group": "[\"trigger\"]",
        "defaults": {
          "name": "When chat message received"
        },
        "iconData": {
          "icon": "comments",
          "type": "icon"
        },
        "displayName": "Chat Trigger",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      },
      {
        "id": 1250,
        "icon": "file:openAi.svg",
        "name": "@n8n/n8n-nodes-langchain.openAi",
        "codex": {
          "data": {
            "alias": [
              "LangChain",
              "ChatGPT",
              "Sora",
              "DallE",
              "whisper",
              "audio",
              "transcribe",
              "tts",
              "assistant"
            ],
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-langchain.openai/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Agents",
                "Miscellaneous",
                "Root Nodes"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "OpenAI"
        },
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}