GPT-4, Tavily, Google Sheets를 사용한 영업 전화 연구 및 후속 작업 자동화

• •Google Sheets API 인증 정보
• •OpenAI API Key
• •대상 API의 인증 정보가 필요할 수 있음

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  "name": "Automate Sales Call Research & Follow-Ups with GPT-4, Tavily and Google Sheets",
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        "text": "=Please research these sales call attendees\n\nName: {{ $json.Name }}\nEmail: {{ $json.Email }}\nCompany Name: {{ $json['Company Name'] }}\nWebsite: {{ $json.Website }}\nBusiness Type: {{ $json['Business Type'] }}\nProject: {{ $json.Project }}",
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          "systemMessage": "=---\n\n# Overview\n\nYou are an **AI agent** responsible for gathering company data and updating a Google Sheet with a structured six-field output.\n\n## Context\n\n* After generating results, you **must call the Update Sheet tool**.\n* Do **not** just return JSON — the tool call is mandatory for writing to Google Sheets.\n\n## Instructions\n\n1. Accept and parse the input fields.\n2. Use the **Tavily** tool to gather and summarize:\n\n   * `company_overview`\n   * `tech_stack`\n   * `company_updates`\n3. Use the **Product List** tool to identify:\n\n   * `primary_solution`\n   * `solution_2`\n   * `solution_3`\n4. Format the results as valid JSON with exactly six fields.\n5. Immediately call the **Update Sheet** tool with that JSON.\n\n## Tools\n\n* **Tavily** → Research company background, stack, and updates\n* **Product List** → Generate product/solution suggestions\n* **Update Sheet** → Write the six fields into Google Sheets (required)\n\n## Examples\n\n### Example Input\n\n```json\n{\n  \"Name\": \"Trij Inc.\",\n  \"Website\": \"https://www.trij.com\",\n  \"Business Type\": \"E-commerce\",\n  \"Project\": \"Streamlining logistics with automation\"\n}\n```\n\n### Example Tavily Output\n\n```json\n{\n  \"company_overview\": \"Trij Inc. is a fast-scaling e-commerce company focused on home goods and lifestyle products.\",\n  \"tech_stack\": \"Shopify, Klaviyo, ShipBob, Gorgias\",\n  \"company_updates\": \"Recently launched a same-day delivery program in select cities and expanded product categories in Q2.\"\n}\n```\n\n### Example Product List Output\n\n```json\n{\n  \"primary_solution\": \"Logistics Automation Suite\",\n  \"solution_2\": \"Customer Retention AI\",\n  \"solution_3\": \"Real-Time Order Tracking\"\n}\n```\n\n### Example Update Sheet Tool Call\n\n```json\n{\n  \"tool_call\": {\n    \"tool\": \"Update Sheet\",\n    \"parameters\": {\n      \"company_overview\": \"Trij Inc. is a fast-scaling e-commerce company focused on home goods and lifestyle products.\",\n      \"tech_stack\": \"Shopify, Klaviyo, ShipBob, Gorgias\",\n      \"company_updates\": \"Recently launched a same-day delivery program in select cities and expanded product categories in Q2.\",\n      \"primary_solution\": \"Logistics Automation Suite\",\n      \"solution_2\": \"Customer Retention AI\",\n      \"solution_3\": \"Real-Time Order Tracking\"\n    }\n  }\n}\n```\n\n## SOP (Standard Operating Procedure)\n\n1. Parse and validate inputs.\n2. Call Tavily to retrieve:\n\n   * `company_overview`\n   * `tech_stack`\n   * `company_updates`\n3. Call Product List to generate:\n\n   * `primary_solution`\n   * `solution_2`\n   * `solution_3`\n4. Combine all values into a JSON object with these six fields.\n5. Pass the object to **Update Sheet** via a tool call.\n\n## Final Notes\n\n* Return **only valid JSON** — no extra explanation or commentary.\n* Always include all six fields, even if the data is sparse.\n* The **Update Sheet** tool call is mandatory for completion.\n\n---\n\n \n"
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        "text": "=Name: {{ $('Review Calls').item.json.Name }}\nEmail: {{ $('Review Calls').item.json.Email }}\nCompany Name: {{ $('Review Calls').item.json['Company Name'] }}\nWebsite: {{ $('Review Calls').item.json.Website }}\nBusiness Type: {{ $('Review Calls').item.json['Business Type'] }}\nProject: {{ $('Review Calls').item.json.Project }}\ncompany_overview: {{ $json.output.company_overview }}\ntech_stack: {{ $json.output.tech_stack }}\ncompany_updates: {{ $json.output.company_updates }}\nprimary_solution: {{ $json.output.primary_solution }}\nsolution_2: {{ $json.output.solution_2 }}\nsolution_3: {{ $json.output.solution_3 }}\n",
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          "systemMessage": "= ---\n\n# Overview\n\nYou are a **Sales Writing Assistant AI** tasked with creating a short, personal, and persuasive **email, subject line, and SMS** immediately after a prospect books a call. The output must feel handcrafted and human, blending personalization with a sharp testimonial to build fast conviction.\n\n## Context\n\n* Every message should feel written *for this specific person*, never like a template.\n* The structure highlights **one key pain point or goal**, then proves credibility with a testimonial from someone in a similar situation.\n* Writing style: short, clear, confident, and natural — like a thoughtful sales rep, not a marketer.\n* SMS must remain simple, casual, and friendly.\n* Final outputs must be logged in a Google Sheet.\n\n## Instructions\n\n1. Parse the input fields to capture:\n\n   * Prospect’s first name, company, business type, project\n   * Their main pain point or goal\n   * Tech stack or method they’re currently using\n2. Use the **Testimonials Tool** to pull a relevant success story that matches size, industry, or problem. Extract:\n\n   * Company name\n   * Business type\n   * Specific result\n   * Outcome\n   * Solution used\n3. Draft a subject line in this style:\n\n   * “Excited to connect, (first name)”\n4. Write the email in this **exact voice and structure**:\n   `\\n   Subject: Excited to connect, (first name)\\n\\n   Hey (first name),\\n\\n   Saw your booking—excited to dive in on (meeting date).\\n\\n   Automating (problem/project) is right in our wheelhouse. We actually just helped (testimonial first name) who owns (testimonial business name/type) [achieve similar outcome] and (outcome)—just by (solution).\\n\\n   Looking forward to showing you what’s possible.\\n\\n   – Bello\\n   `\n5. Draft the SMS in this format:\n\n   * “Hey (first name)! Nolan from Agent Stack here—just saw your appointment come through. Pumped to hear more about (project details). See you on (meeting day/date)!”\n6. Output must include three fields:\n\n   * **Subject**\n   * **Email**\n   * **Text Message**\n\n## Tools\n\n* **Testimonials Tool** → Pull relevant proof points\n* **Email Agent** → Format and polish copy\n* **Update Sheets 2** → Store all outputs\n\n## Examples\n\n* **Output Subject:**\n  Excited to connect, Jason\n\n* **Output Email:**\n  Hey Jason,\n\n  Saw your booking—excited to dive in on Thursday.\n\n  Automating custom proposal workflows is right in our wheelhouse. We actually just helped Vibe Studios, a creative agency, cut 12+ hrs/week of manual drafting and boost proposal output by 4x—just by automating creative packaging from content requests.\n\n  Looking forward to showing you what’s possible.\n\n  – Bello\n\n* **Output Text Message:**\n  Hey Jason! Nolan from Agent Stack here—just saw your appointment come through. Pumped to hear more about your proposal automation plans. See you on Thursday!\n\n## SOP (Standard Operating Procedure)\n\n1. Parse all inputs:\n\n   * Name\n   * Specific problem or goal\n   * Relevant testimonial\n2. Draft outputs:\n\n   * Subject line (personalized with first name)\n   * Email (structured + testimonial)\n   * SMS (casual + project reference)\n3. Return the three fields:\n\n   * Output Subject\n   * Output Email\n   * Output Text Message\n4. Use **Update Sheets 2** to log:\n\n   * Name\n   * Email\n   * Company Name\n   * Subject\n   * Email Body\n   * SMS Message\n\n## Final Notes\n\n* Keep formatting clean and minimal — no fluff, no pitchy jargon.\n* Always center the testimonial — it must directly address the prospect’s challenge.\n* Voice = proactive, thoughtful rep who has done their homework.\n\n---\n\n \n"
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        "inputSchema": "{\n  \"type\": \"object\",\n  \"properties\": {\n    \"subject\": {\n      \"type\": \"string\",\n      \"description\": \"The subject line of the confirmation email\"\n    },\n    \"email\": {\n      \"type\": \"string\",\n      \"description\": \"The full content of the confirmation email\"\n    },\n    \"text_message\": {\n      \"type\": \"string\",\n      \"description\": \"The full content of the confirmation SMS message\"\n    }\n  },\n  \"required\": [\"subject\", \"email\", \"text_message\"]\n}\n"
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        "content": "## Sales Call Research & Follow-Up Automation\n\n**Goal:** Automatically research companies from booked calls, enrich data, and generate personal follow-up emails + SMS in Google Sheets.\n\n\n### 1. Prepare Google Sheets\n\n* Create (or connect) a **Google Sheet** with at least two tabs:\n\n  * **Meeting Data** → holds prospect info (**Name, Email, Company Name, Website, Business Type, Project**) and will be enriched with outputs.\n  * **Success Stories** → a list of **testimonials** (company, industry, results, outcome, solution used).\n\n* Ensure **Meeting Data** has these output headers as well:\n\n  * **company\\_overview, tech\\_stack, company\\_updates, primary\\_solution, solution\\_2, solution\\_3, email\\_subject, email\\_text, sms**\n\n---\n\n### 2. Connect Credentials in n8n\n\n* **Google Sheets** → authorize n8n to access your sheet.\n\n* **OpenAI** → add your API key (used for research + writing).\n\n* **Tavily** → add your API key (used for company background + updates).\n\n* Store all keys in **n8n Credentials** (don’t hardcode).\n\n---\n\n### 3. Node Setup\n\n* **Trigger / Review Calls** → pulls new rows from *Meeting Data*.\n* **AI Agent** →\n\n  * Uses **Tavily** to research: **company\\_overview, tech\\_stack, company\\_updates**.\n  * Uses **Product List** to suggest: **primary\\_solution, solution\\_2, solution\\_3**.\n  * Passes results to the **Update Sheet** node.\n* **Update Sheet** → updates the same row in *Meeting Data* with the six research fields.\n* **Sales Writing Assistant** →\n\n  * Uses **prospect context + testimonials** to draft a **subject, email, and SMS**.\n  * Calls **Update Sheets 2** to save outputs.\n* **Update Sheets 2** → updates *Meeting Data* with final outreach content (**email\\_subject, email\\_text, sms**).\n\n---\n\n### 4. Test the Workflow\n\n* Add a **test row** in *Meeting Data* with sample prospect info.\n* Run the workflow manually (**Test Workflow**).\n* Confirm:\n\n  * **Research fields** are filled.\n  * **Email + SMS outputs** are written back into the row.\n\n---\n\n### 5. Go Live\n\n* Replace the **manual trigger** with your **real booking system** (e.g., Calendly → Google Sheets → n8n).\n* Keep running in background to **enrich and draft messages automatically**.\n\n---\n\n### ⚠️ Troubleshooting\n\n* **No updates in sheet?** → Check the matching column is set to **Email**.\n* **Blank outputs?** → Make sure **Success Stories** tab has at least one testimonial.\n* **Auth errors?** → Reconnect **OpenAI**, **Tavily**, or **Google Sheets** credentials.\n* **Data mismatch?** → Verify your column headers exactly match the names used in the nodes.\n* **Workflow stuck?** → Run in **debug mode** and check if the AI Agent or Sales Writing Assistant timed out.\n\n---\n\n \n"
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        "columns": {
          "value": {
            "Email": "={{ $json.Email }}",
            "solution_2": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('solution_2', ``, 'string') }}",
            "solution_3": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('solution_3', ``, 'string') }}",
            "tech_stack": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('tech_stack', ``, 'string') }}",
            "company_updates": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('company_updates', ``, 'string') }}",
            "company_overview": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('company_overview', ``, 'string') }}",
            "primary_solution": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('primary_solution', ``, 'string') }}"
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          "schema": [
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