← All Productivity
Google Docs email verification with BillionVerify
Google Docs is widely used to draft newsletters, outreach templates, contact lists, and reports that include email addresses. BillionVerify adds email verification to any Google Docs-based workflow, ensuring that addresses pulled from or stored in documents are valid before they are used for communication or imported into other tools.
Why verify before the send
Documents that collect or reference email addresses — intake forms exported to Docs, compiled prospect lists, event sign-up summaries — often contain errors, fake addresses, and disposable emails. Acting on those addresses without verification leads to bounces, wasted effort, and potential sender reputation damage. Verifying at the workflow stage catches problems early.
Ready-to-use n8n workflow
Import this workflow into n8n — it verifies every address with BillionVerify before Google Docs sends, so only deliverable contacts are emailed. Install the BillionVerify community node first, then add your API key. Adapted from this n8n template
verify-emails-in-google-docs.json
{
"name": "Automate UX research planning with Gemini AI, Google Docs, and human feedback + BillionVerify",
"nodes": [
{
"id": "a92f96d8-42fd-498e-bc7d-60d9bfb0e191",
"name": "On form submission",
"type": "n8n-nodes-base.formTrigger",
"position": [
496,
704
],
"webhookId": "9c1c5243-1da1-40d6-afe7-7f47c101bee8",
"parameters": {
"options": {},
"formTitle": "Provide Context for Writing a Research Plan",
"formFields": {
"values": [
{
"fieldType": "textarea",
"fieldLabel": "What type of organization do you work for?",
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "What kind of product, service, or experience does your company provide?",
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "What do you want to learn about your users or the problem you are addressing?",
"requiredField": true
},
{
"fieldType": "email",
"fieldLabel": "Which email address would you prefer to receive the email at?",
"requiredField": true
}
]
}
},
"typeVersion": 2.3
},
{
"id": "c73b6880-dc9c-4678-a2cf-b092a2b52eef",
"name": "Gemini",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
672,
848
],
"parameters": {
"options": {}
},
"credentials": {
"googlePalmApi": {
"id": "credential-id",
"name": "googlePalmApi Credential"
}
},
"typeVersion": 1
},
{
"id": "68573d63-98b1-42f0-83d3-9bce7d364a11",
"name": "AI Agent: Question Maker",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
672,
704
],
"parameters": {
"text": "=You are a UX researcher assistant. Your role is to generate **10 research questions** based on the following information:\n\n* What type of organization do you work for?: `{{ $json['What type of organization do you work for?'] }}`\n* What kind of product, service, or experience does your company provide?: `{{ $json['What kind of product, service, or experience does your company provide?'] }}`\n* What do you want to learn about your users or the problem you are addressing?: `{{ $json['What do you want to learn about your users or the problem you are addressing?'] }}`\n\nReturn the questions in **JSON format** exactly as follows:\n\n```json\n{\n \"Question 01\": \"<created question>\",\n \"Question 02\": \"<created question>\",\n \"Question 03\": \"<created question>\",\n \"Question 04\": \"<created question>\",\n \"Question 05\": \"<created question>\",\n \"Question 06\": \"<created question>\",\n \"Question 07\": \"<created question>\",\n \"Question 08\": \"<created question>\",\n \"Question 09\": \"<created question>\",\n \"Question 10\": \"<created question>\"\n}\n",
"options": {},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"id": "70af22d2-8bda-479c-a1d0-2b3f166a31b8",
"name": "AI Agent: Question Editor",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
848,
1104
],
"parameters": {
"text": "=You are a UX research assistant helping refine Planning Research Questions.\n\nHere is general information about the organization and research goal:\n\n* Type of organization: {{ $('On form submission').item.json['What type of organization do you work for?'] }}\n* Product/service/experience provided: {{ $('On form submission').item.json['What kind of product, service, or experience does your company provide?'] }}\n* Research objective: {{ $('On form submission').item.json['What do you want to learn about your users or the problem you are addressing?'] }}\n\nThe previous AI Agent generated several user research questions:\n{{ $('AI Agent: Question Maker').item.json.output }}\n\nThe designer reviewed these questions and gave feedback. \nSome were **approved**, some were **rejected**, and some were marked as **\"Should be edited\"**.\nAlso the user give their feedback on how you can improve it.\n\nYour task:\n- For questions marked as **\"Should be edited\"**, rephrase or refine them based on the user's feedback. If there is no feedback from the user edit it to improve clarity, relevance, or tone. \n- **Avoid reusing the format or style** of any questions that were rejected.\n- If a question was approved, keep it unchanged.\n\nHere are the questions and their respective review outcomes:\n\n\n{{ $json['Question 1'] }}\nStatus: {{ $json['status 1'] }}\nIf Question 01 needs editing, how should it be edited?: {{ $json['status 1'] }}\n---\n{{ $json['Question 2'] }}\nStatus: {{ $json['status 2'] }}\nIf Question 02 needs editing, how should it be edited?: {{ $json['status 2'] }}\n---\n{{ $json['Question 3'] }}\nStatus: {{ $json['status 3'] }}\nIf Question 03 needs editing, how should it be edited?: {{ $json['status 3'] }}\n---\n{{ $json['Question 4'] }}\nStatus: {{ $json['status 4'] }}\nIf Question 04 needs editing, how should it be edited?: {{ $json['status 4'] }}\n---\n{{ $json['Question 5'] }}\nStatus: {{ $json['status 5'] }}\nIf Question 05 needs editing, how should it be edited?: {{ $json['status 5'] }}\n---\n{{ $json['Question 6'] }}\nStatus: {{ $json['status 6'] }}\nIf Question 06 needs editing, how should it be edited?: {{ $json['status 6'] }}\n---\n{{ $json['Question 7'] }}\nStatus: {{ $json['status 7'] }}\nIf Question 07 needs editing, how should it be edited?: {{ $json['status 7'] }}\n---\n{{ $json['Question 8'] }}\nStatus: {{ $json['status 8'] }}\nIf Question 08 needs editing, how should it be edited?: {{ $json['status 8'] }}\n---\n{{ $json['Question 9'] }}\nStatus: {{ $json['status 9'] }}\nIf Question 09 needs editing, how should it be edited?: {{ $json['status 9'] }}\n---\n{{ $json['Question 10'] }}\nStatus: {{ $json['status 10'] }}\nIf Question 10 needs editing, how should it be edited?: {{ $json['status 10'] }}\n\nReturn your final output **only** in a list of questions (no markdown or extra text). Reset the numbering so it starts again from Question 01 in order. \n",
"options": {},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"id": "f0cdc45b-6a52-44c0-a9cd-cbeef08f8d58",
"name": "Gemini Google",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
848,
1248
],
"parameters": {
"options": {}
},
"credentials": {
"googlePalmApi": {
"id": "credential-id",
"name": "googlePalmApi Credential"
}
},
"typeVersion": 1
},
{
"id": "88aececb-21da-4a47-a23c-1cc7eb1172d4",
"name": "Separate Questions",
"type": "n8n-nodes-base.code",
"position": [
976,
704
],
"parameters": {
"jsCode": "// n8n Function Node code\n// Assumes input comes in the first item as `input[0].json.output`\n\n// Get the raw string containing JSON\nconst rawString = $json[\"output\"];\n\n// Remove the ```json wrapper if present\nconst jsonString = rawString.replace(/```json|```/g, '').trim();\n\n// Parse it into a JavaScript object\nconst data = JSON.parse(jsonString);\n\n// Return only the questions in the same structure\nreturn [\n {\n json: data\n }\n];\n"
},
"typeVersion": 2
},
{
"id": "1bc75236-67a4-4d5f-934f-c868287be67d",
"name": "Question Approval",
"type": "n8n-nodes-base.gmail",
"position": [
496,
1104
],
"webhookId": "5952cd6a-8670-41bd-9b64-a89aba96683e",
"parameters": {
"sendTo": "={{ $('On form submission').item.json['Which email address would you prefer to receive the email at?'] }}",
"message": "=Dear Designer,\n\nI hope this email finds you well.\n\nI am writing to share the proposed research questions for your project and kindly request your feedback. Please review each question and indicate whether you approve or disapprove of them.\n\nYour guidance is greatly appreciated, and your approval will help me move forward with the research design.\n\nThank you very much for your time and support.\n\nBest regards,\nYour UX Assistance",
"options": {},
"subject": "Request for Approval of Research Questions",
"operation": "sendAndWait",
"formFields": {
"values": [
{
"fieldType": "radio",
"fieldLabel": "=Question 01: {{ $json[\"Question 01\"] }}",
"fieldOptions": {
"values": [
{
"option": "Approved"
},
{
"option": "Disapproved"
},
{
"option": "Should be edited"
}
]
},
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "If Question 01 needs editing, how should it be edited?"
},
{
"fieldType": "radio",
"fieldLabel": "={{ $json[\"Question 02\"] }}",
"fieldOptions": {
"values": [
{
"option": "Approved"
},
{
"option": "Disapproved"
},
{
"option": "Should be edited"
}
]
},
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "If Question 02 needs editing, how should it be edited?"
},
{
"fieldType": "radio",
"fieldLabel": "={{ $json[\"Question 03\"] }}",
"fieldOptions": {
"values": [
{
"option": "Approved"
},
{
"option": "Disapproved"
},
{
"option": "Should be edited"
}
]
},
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "If Question 03 needs editing, how should it be edited?"
},
{
"fieldType": "radio",
"fieldLabel": "={{ $json[\"Question 04\"] }}",
"fieldOptions": {
"values": [
{
"option": "Approved"
},
{
"option": "Disapproved"
},
{
"option": "Should be edited"
}
]
},
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "If Question 04 needs editing, how should it be edited?"
},
{
"fieldType": "radio",
"fieldLabel": "={{ $json[\"Question 05\"] }}",
"fieldOptions": {
"values": [
{
"option": "Approved"
},
{
"option": "Disapproved"
},
{
"option": "Should be edited"
}
]
},
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "If Question 05 needs editing, how should it be edited?"
},
{
"fieldType": "radio",
"fieldLabel": "={{ $json[\"Question 06\"] }}",
"fieldOptions": {
"values": [
{
"option": "Approved"
},
{
"option": "Disapproved"
},
{
"option": "Should be edited"
}
]
},
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "If Question 06 needs editing, how should it be edited?"
},
{
"fieldType": "radio",
"fieldLabel": "={{ $json[\"Question 07\"] }}",
"fieldOptions": {
"values": [
{
"option": "Approved"
},
{
"option": "Disapproved"
},
{
"option": "Should be edited"
}
]
},
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "If Question 07 needs editing, how should it be edited?"
},
{
"fieldType": "radio",
"fieldLabel": "={{ $json[\"Question 08\"] }}",
"fieldOptions": {
"values": [
{
"option": "Approved"
},
{
"option": "Disapproved"
},
{
"option": "Should be edited"
}
]
},
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "If Question 08 needs editing, how should it be edited?"
},
{
"fieldType": "radio",
"fieldLabel": "={{ $json[\"Question 09\"] }}",
"fieldOptions": {
"values": [
{
"option": "Approved"
},
{
"option": "Disapproved"
},
{
"option": "Should be edited"
}
]
},
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "If Question 09 needs editing, how should it be edited?"
},
{
"fieldType": "radio",
"fieldLabel": "={{ $json[\"Question 10\"] }}",
"fieldOptions": {
"values": [
{
"option": "Approved"
},
{
"option": "Disapproved"
},
{
"option": "Should be edited"
}
]
},
"requiredField": true
},
{
"fieldType": "textarea",
"fieldLabel": "If Question 10 needs editing, how should it be edited?"
}
]
},
"responseType": "customForm"
},
"credentials": {
"gmailOAuth2": {
"id": "credential-id",
"name": "gmailOAuth2 Credential"
}
},
"typeVersion": 2.1
},
{
"id": "feac9d2d-23be-42d8-ad97-90757c98748f",
"name": "Edit Approval",
"type": "n8n-nodes-base.gmail",
"position": [
496,
1504
],
"webhookId": "5952cd6a-8670-41bd-9b64-a89aba96683e",
"parameters": {
"sendTo": "={{ $('On form submission').item.json['Which email address would you prefer to receive the email at?'] }}",
"message": "=Dear Designer,\n\nI hope this email finds you well.\n\nI am writing to share the proposed research questions for your project and kindly request your feedback. Please review each question and indicate whether you approve or disapprove of them:\n{{ $('AI Agent: Question Editor').item.json.output }}\n\nYour guidance is greatly appreciated, and your approval will help me move forward with the research design.\n\nThank you very much for your time and support.\n\nBest regards,\nYour UX Assistance",
"options": {},
"subject": "Request for Approval of Research Questions",
"operation": "sendAndWait",
"formFields": {
"values": [
{
"fieldLabel": "Which question have you not approved? Please write the number only."
},
{
"fieldType": "textarea",
"fieldLabel": "Why are they rejected?"
}
]
},
"responseType": "customForm"
},
"credentials": {
"gmailOAuth2": {
"id": "credential-id",
"name": "gmailOAuth2 Credential"
}
},
"typeVersion": 2.1
},
{
"id": "5c37ff3e-1433-4bd4-a6d8-588e406e56ce",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
624,
1632
],
"parameters": {
"options": {}
},
"credentials": {
"googlePalmApi": {
"id": "credential-id",
"name": "googlePalmApi Credential"
}
},
"typeVersion": 1
},
{
"id": "e859a1db-874f-475f-8d06-957a544938fd",
"name": "AI Agent: Second Editor",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
624,
1504
],
"parameters": {
"text": "=You are a UX research assistant helping refine Planning Research Questions.\n\nHere is general information about the organization and research goal:\n\n* Type of organization: {{ $('On form submission').item.json['What type of organization do you work for?'] }}\n* Product/service/experience provided: {{ $('On form submission').item.json['What kind of product, service, or experience does your company provide?'] }}\n* Research objective: {{ $('On form submission').item.json['What do you want to learn about your users or the problem you are addressing?'] }}\n\nThe previous AI Agent generated several user research questions:\n{{ $('AI Agent: Question Editor').item.json.output }}\n\nThe designer reviewed these questions and gave feedback. \nSome were **approved**, some were **rejected**, and the reason why it is rejected.\n\nWhich question have been rejected: \n{{ $json.data['Which question have you not approved? Please write the number only.'] }}\n\nYour task:\n- Rewrite the questions that the user not approved. Use the users' feedback if it is available:\n{{ $json.data['Why are they rejected?'] }}\n\nReturn your final output **only** in a list of questions (no markdown or extra text). Reset the numbering so it starts again from Question 01 in order. \n",
"options": {},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"id": "77e4a8bc-c953-461e-86e8-79d869a6ce72",
"name": "Google Gemini Chat",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
912,
1648
],
"parameters": {
"options": {}
},
"credentials": {
"googlePalmApi": {
"id": "credential-id",
"name": "googlePalmApi Credential"
}
},
"typeVersion": 1
},
{
"id": "d07287cb-de97-453a-861b-a76d6c414883",
"name": "AI Agent: Request Methods",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
912,
1504
],
"parameters": {
"text": "=You are a **UX research assistant** helping identify suitable **research methods** for user research questions.\n\n**Context**\n\n* **Type of organization:** {{ $('On form submission').item.json['What type of organization do you work for?'] }}\n* **Product/service/experience provided:** {{ $('On form submission').item.json['What kind of product, service, or experience does your company provide?'] }}\n* **Research objective:** {{ $('On form submission').item.json['What do you want to learn about your users or the problem you are addressing?'] }}\n\n**Input**\n\nThe previous AI Agent generated the following user research questions:\n{{ $json.output }}\n\n**Your task**\n\nFor each research question:\n\n* Recommend the **most suitable UX research method(s)** (e.g., interviews, usability testing, diary study, survey, A/B testing, etc.).\n* Explain **why** that method is appropriate for the question and research goal.\n* Ensure your reasoning is clear, concise, and practical.\n\n**Output format**\n\nReturn your final answer **only** as a list, with each item containing:\n\n1. The **question**\n2. The **recommended method(s)**\n3. A brief **rationale** for why the method was chosen\n\nDo **not** include markdown formatting, bullet points, or extra text — only the numbered list in plain text.\n",
"options": {},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"id": "9f14a352-e490-43d9-8b90-e0df4379bfcc",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
400,
592
],
"parameters": {
"height": 384,
"content": "## Get Information about Organisation\n"
},
"typeVersion": 1
},
{
"id": "a981eb5a-12a7-4783-8ff6-ae76d5e18be5",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
656,
592
],
"parameters": {
"width": 496,
"height": 384,
"content": "## Using AI to Write a Research Plan\n"
},
"typeVersion": 1
},
{
"id": "cb8bdd33-627c-4a57-a879-9ee50dc5f9e6",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
400,
992
],
"parameters": {
"color": 2,
"height": 384,
"content": "## Questions are checked by the user\n"
},
"typeVersion": 1
},
{
"id": "2985ebff-dc3d-42e7-9046-21835e8af4b3",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
656,
992
],
"parameters": {
"color": 2,
"width": 496,
"height": 384,
"content": "## Edit the questions based on the user's feedback and be rechecked by the user\n"
},
"typeVersion": 1
},
{
"id": "e0188e7d-ec2f-4ee2-a940-9636ab92a729",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
400,
1392
],
"parameters": {
"color": 3,
"width": 480,
"height": 384,
"content": "## Questions are regenerated "
},
"typeVersion": 1
},
{
"id": "85e322c2-7987-49cf-965e-59efdb1b733a",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
896,
1392
],
"parameters": {
"color": 3,
"width": 256,
"height": 384,
"content": "## Design methods are proposed for each question"
},
"typeVersion": 1
},
{
"id": "9adff9a5-cbfd-4ecc-8a75-b0e75666c2c8",
"name": "Combine Questions",
"type": "n8n-nodes-base.code",
"position": [
704,
1104
],
"parameters": {
"jsCode": "const inputData = items[0].json.data;\nlet combined = {};\nlet questionCount = 1;\n\nfor (let key in inputData) {\n // Skip edit keys\n if (key.startsWith(\"If Question\")) continue;\n\n // Main question\n const editKey = `If Question ${questionCount} needs editing, how should it be edited?`;\n\n combined[`Question ${questionCount}`] = key; // question text\n combined[`status ${questionCount}`] = inputData[key]; // status\n combined[`edit ${questionCount}`] = inputData[editKey] || \"\"; // edit suggestion\n\n questionCount++;\n}\n\nreturn [{ json: combined }];\n"
},
"typeVersion": 2
},
{
"id": "5db3754b-8720-4fce-9aa3-93ed878b540d",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1472,
1504
],
"parameters": {
"text": "=You are given a research plan generated by AI, which includes UX research methods and related details.\n\nYour task is to transform this raw content into a **visually appealing, well-structured HTML report** suitable for conversion into a Google Doc.\n\nRequirements:\n- Organize the report into clear, logical sections (e.g., <h1>Title</h1>, <h2>Introduction</h2>, <h2>Objectives</h2>, <h2>Research Questions</h2>, <h2>Methods</h2>, <h2>Expected Outcomes</h2>, <h2>Timeline</h2>, <h2>References</h2>).\n- Use clean, semantic HTML (<h1>, <h2>, <p>, <ul>, <ol>, <strong>, <em>).\n- Make the layout **visually appealing**: \n - Add light visual hierarchy (consistent heading sizes and spacing).\n - Use short paragraphs, bullet points, and bold for emphasis where helpful.\n - Keep style elegant and minimal — suitable for academic or professional presentation.\n- Ensure it looks **polished, readable, and ready to paste into Google Docs**.\n- Do not include scripts or external CSS; use inline styling only if needed for visual clarity (e.g., font-weight, spacing, or color).\n\nInput content:\n{{ $('AI Agent: Request Methods').item.json.output }}\n",
"options": {},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"id": "d4eacca7-a927-4b49-b7c1-5dd6eadb5b38",
"name": "Gemini ChatAssis",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1472,
1648
],
"parameters": {
"options": {}
},
"credentials": {
"googlePalmApi": {
"id": "credential-id",
"name": "googlePalmApi Credential"
}
},
"typeVersion": 1
},
{
"id": "3ebf7abd-96a7-49ef-96b8-2859a7d4a2fd",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
1200,
1424
],
"parameters": {
"color": 4,
"width": 528,
"height": 352,
"content": "## Prepare the Report"
},
"typeVersion": 1
},
{
"id": "41a3d493-2ffa-4674-86da-603ec94b455b",
"name": "Report Approval",
"type": "n8n-nodes-base.gmail",
"position": [
2000,
1504
],
"webhookId": "5952cd6a-8670-41bd-9b64-a89aba96683e",
"parameters": {
"sendTo": "={{ $('On form submission').item.json['Which email address would you prefer to receive the email at?'] }}",
"message": "=Dear Designer,\n\nI hope this email finds you well.\n\nHere you can find the planning research question and the proposed method: \n{{ 'https://docs.google.com/document/d/' + $('Create a Report').item.json.id + '/view' }}\n\nPlease take a look and share your feedback.\n\nThank you very much for your time and support.\n\nBest regards,\nYour UX Assistant",
"options": {},
"subject": "Feedback on Research Question and Proposed Method",
"operation": "sendAndWait",
"formFields": {
"values": [
{
"fieldType": "textarea",
"fieldLabel": "In what ways should the report be changed?"
}
]
},
"responseType": "customForm"
},
"credentials": {
"gmailOAuth2": {
"id": "credential-id",
"name": "gmailOAuth2 Credential"
}
},
"typeVersion": 2.1
},
{
"id": "acd40e18-6b97-4def-ac96-5f62ac5717fe",
"name": "Sticky Note7",
"type": "n8n-nodes-base.stickyNote",
"position": [
1744,
1424
],
"parameters": {
"color": 4,
"width": 432,
"height": 352,
"content": "## Get and Send the Report"
},
"typeVersion": 1
},
{
"id": "c6cb50d3-32ed-411f-b12b-1bcdbd9b0322",
"name": "Google GeminiChat",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1280,
1280
],
"parameters": {
"options": {}
},
"credentials": {
"googlePalmApi": {
"id": "credential-id",
"name": "googlePalmApi Credential"
}
},
"typeVersion": 1
},
{
"id": "54ca1d28-b042-4630-be9f-689c6d479295",
"name": "Sticky Note8",
"type": "n8n-nodes-base.stickyNote",
"position": [
1200,
1072
],
"parameters": {
"color": 5,
"width": 528,
"height": 336,
"content": "## Edit the Report"
},
"typeVersion": 1
},
{
"id": "1a478b88-3d92-48c8-95d9-e67e10501e31",
"name": "AI Agent: Report Editor",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1280,
1136
],
"parameters": {
"text": "=You are given a research plan generated by an AI, which includes UX research methods and related details.\n\nRead the report below:\n{{ $('AI Agent').item.json.output }}\n\nThen read the user’s feedback:\n{{ $json.data[\"In what ways should the report be changed?\"] }}\n\nRevise the research plan according to the user’s feedback. Keep the structure and clarity of the report while making the requested changes.",
"options": {},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"id": "4cb275cd-c95d-43f9-8d9d-61c0c2e36b96",
"name": "HTTP Request: Report",
"type": "n8n-nodes-base.httpRequest",
"position": [
1824,
1504
],
"parameters": {
"url": "https://script.google.com/macros/s/AKfycbycCRkQRMw2hQPRKvBq-8fPSTlrWsHt3rNd5qjuCytZavI66m1ovif4HEoW9TtuUaar/exec",
"method": "POST",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "docId",
"value": "={{ $('Create a Report').item.json.id }}"
},
{
"name": "mode",
"value": "append"
},
{
"name": "HTML",
"value": "={{ $json.output }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "f220a797-73af-4dbb-a696-66c218e9e65b",
"name": "HTTP Request: Edited Report",
"type": "n8n-nodes-base.httpRequest",
"position": [
1824,
1136
],
"parameters": {
"url": "https://script.google.com/macros/s/AKfycbycCRkQRMw2hQPRKvBq-8fPSTlrWsHt3rNd5qjuCytZavI66m1ovif4HEoW9TtuUaar/exec",
"method": "POST",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "docId",
"value": "={{ $json.id }}"
},
{
"name": "mode",
"value": "append"
},
{
"name": "HTML",
"value": "={{ $('AI Agent: Report Editor').item.json.output }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "f71091c1-74b5-4b6f-8840-2978a0cf0163",
"name": "Create a Report",
"type": "n8n-nodes-base.googleDocs",
"position": [
1280,
1504
],
"parameters": {
"title": "=Research Plan {{ new Date().toLocaleString('en-GB', { hour12: false }).replace(/[/,: ]/g, '.').replace(',', '').slice(0, 16).replace(' ', '.') }}",
"folderId": "default"
},
"credentials": {
"googleDocsOAuth2Api": {
"id": "credential-id",
"name": "googleDocsOAuth2Api Credential"
}
},
"typeVersion": 2
},
{
"id": "1a235927-f553-4e5f-b027-1d10abb14fd4",
"name": "Create the Final Report",
"type": "n8n-nodes-base.googleDocs",
"position": [
1584,
1136
],
"parameters": {
"title": "=Final Research Plan {{ new Date().toLocaleString('en-GB', { hour12: false }).replace(/[/,: ]/g, '.').replace(',', '').slice(0, 16).replace(' ', '.') }}",
"folderId": "default"
},
"credentials": {
"googleDocsOAuth2Api": {
"id": "credential-id",
"name": "googleDocsOAuth2Api Credential"
}
},
"typeVersion": 2
},
{
"id": "83b8608e-1431-461d-b515-a296de5b02f6",
"name": "Sticky Note9",
"type": "n8n-nodes-base.stickyNote",
"position": [
1744,
1072
],
"parameters": {
"color": 5,
"width": 432,
"height": 336,
"content": "## Create the Final Report"
},
"typeVersion": 1
},
{
"id": "e43ceaa3-8b69-4d04-b822-5280cda43c43",
"name": "Sticky Note10",
"type": "n8n-nodes-base.stickyNote",
"position": [
112,
592
],
"parameters": {
"color": 6,
"height": 1184,
"content": "## Planning Research Workflow\n\nThis automation streamlines the process of designing and refining a research plan using AI and human feedback. It integrates Google Gemini, Gmail, and HTTP requests to coordinate each stage—from gathering information to delivering a finalized report.\n\nGet Information – Collects key details about the organization or project through a form submission.\n\nAI-Assisted Planning – Gemini generates an initial research plan and breaks it into structured questions.\n\nUser Review Loop – The questions are sent to the user via email for review, edits, or approval. Feedback triggers AI refinement.\n\nQuestion Regeneration & Method Design – If needed, the system regenerates improved questions and proposes appropriate design methods for each.\n\nReport Preparation – The approved content is compiled into a structured research report.\n\nFinal Editing & Delivery – Gemini edits the report, creates the final document, and sends it automatically for approval or sharing."
},
"typeVersion": 1
},
{
"parameters": {
"operation": "verify",
"email": "={{ $('On form submission').item.json['Which email address would you prefer to receive the email at?'] }}",
"additionalOptions": {}
},
"type": "n8n-nodes-billionverify.billionVerify",
"typeVersion": 1,
"position": [
136,
1104
],
"name": "Verify Email (BillionVerify)",
"credentials": {
"billionVerifyApi": {
"id": "",
"name": "BillionVerify account"
}
}
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "is-deliverable",
"leftValue": "={{ $json.is_deliverable }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
}
}
]
}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2,
"position": [
316,
1104
],
"name": "IF deliverable"
},
{
"parameters": {
"operation": "verify",
"email": "={{ $('On form submission').item.json['Which email address would you prefer to receive the email at?'] }}",
"additionalOptions": {}
},
"type": "n8n-nodes-billionverify.billionVerify",
"typeVersion": 1,
"position": [
136,
1504
],
"name": "Verify Email (BillionVerify) 2",
"credentials": {
"billionVerifyApi": {
"id": "",
"name": "BillionVerify account"
}
}
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "is-deliverable",
"leftValue": "={{ $json.is_deliverable }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
}
}
]
}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2,
"position": [
316,
1504
],
"name": "IF deliverable 2"
},
{
"parameters": {
"operation": "verify",
"email": "={{ $('On form submission').item.json['Which email address would you prefer to receive the email at?'] }}",
"additionalOptions": {}
},
"type": "n8n-nodes-billionverify.billionVerify",
"typeVersion": 1,
"position": [
1640,
1504
],
"name": "Verify Email (BillionVerify) 3",
"credentials": {
"billionVerifyApi": {
"id": "",
"name": "BillionVerify account"
}
}
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "is-deliverable",
"leftValue": "={{ $json.is_deliverable }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
}
}
]
}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2,
"position": [
1820,
1504
],
"name": "IF deliverable 3"
}
],
"connections": {
"Gemini": {
"ai_languageModel": [
[
{
"node": "AI Agent: Question Maker",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"AI Agent": {
"main": [
[
{
"node": "HTTP Request: Report",
"type": "main",
"index": 0
}
]
]
},
"Edit Approval": {
"main": [
[
{
"node": "AI Agent: Second Editor",
"type": "main",
"index": 0
}
]
]
},
"Gemini Google": {
"ai_languageModel": [
[
{
"node": "AI Agent: Question Editor",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Create a Report": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Report Approval": {
"main": [
[
{
"node": "AI Agent: Report Editor",
"type": "main",
"index": 0
}
]
]
},
"Gemini ChatAssis": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Combine Questions": {
"main": [
[
{
"node": "AI Agent: Question Editor",
"type": "main",
"index": 0
}
]
]
},
"Google GeminiChat": {
"ai_languageModel": [
[
{
"node": "AI Agent: Report Editor",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Question Approval": {
"main": [
[
{
"node": "Combine Questions",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat": {
"ai_languageModel": [
[
{
"node": "AI Agent: Request Methods",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"On form submission": {
"main": [
[
{
"node": "AI Agent: Question Maker",
"type": "main",
"index": 0
}
]
]
},
"Separate Questions": {
"main": [
[
{
"node": "Verify Email (BillionVerify)",
"type": "main",
"index": 0
}
]
]
},
"HTTP Request: Report": {
"main": [
[
{
"node": "Verify Email (BillionVerify) 3",
"type": "main",
"index": 0
}
]
]
},
"AI Agent: Report Editor": {
"main": [
[
{
"node": "Create the Final Report",
"type": "main",
"index": 0
}
]
]
},
"AI Agent: Second Editor": {
"main": [
[
{
"node": "AI Agent: Request Methods",
"type": "main",
"index": 0
}
]
]
},
"Create the Final Report": {
"main": [
[
{
"node": "HTTP Request: Edited Report",
"type": "main",
"index": 0
}
]
]
},
"AI Agent: Question Maker": {
"main": [
[
{
"node": "Separate Questions",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent: Second Editor",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"AI Agent: Question Editor": {
"main": [
[
{
"node": "Verify Email (BillionVerify) 2",
"type": "main",
"index": 0
}
]
]
},
"AI Agent: Request Methods": {
"main": [
[
{
"node": "Create a Report",
"type": "main",
"index": 0
}
]
]
},
"Verify Email (BillionVerify)": {
"main": [
[
{
"node": "IF deliverable",
"type": "main",
"index": 0
}
]
]
},
"IF deliverable": {
"main": [
[
{
"node": "Question Approval",
"type": "main",
"index": 0
}
],
[]
]
},
"Verify Email (BillionVerify) 2": {
"main": [
[
{
"node": "IF deliverable 2",
"type": "main",
"index": 0
}
]
]
},
"IF deliverable 2": {
"main": [
[
{
"node": "Edit Approval",
"type": "main",
"index": 0
}
],
[]
]
},
"Verify Email (BillionVerify) 3": {
"main": [
[
{
"node": "IF deliverable 3",
"type": "main",
"index": 0
}
]
]
},
"IF deliverable 3": {
"main": [
[
{
"node": "Report Approval",
"type": "main",
"index": 0
}
],
[]
]
}
},
"settings": {
"executionOrder": "v1"
}
}Workflow templates with Google Docs
Ready-to-use workflows that verify emails before Google Docs sends.
How it works
- 1
Use n8n (with the BillionVerify community node) or Integrately to connect your Google Docs workflow to BillionVerify.
- 2
Set up a trigger when a document is updated or a specific table or list inside it changes to initiate verification.
- 3
Extracted email addresses are sent to BillionVerify, which checks syntax, DNS, SMTP reachability, and disposable or catch-all status.
- 4
Results are written back into the document, a linked Sheet, or routed to downstream tools based on the verification outcome.
- 5
Valid addresses continue through the workflow; invalid or risky ones are flagged or excluded automatically.
When to use this
Verify email addresses extracted from documents
When a workflow parses email addresses out of a Google Doc — such as a list compiled from a manual process — BillionVerify validates each one before it is added to your CRM or email list, catching typos and invalid addresses automatically.
Pre-send check for document-based outreach lists
Teams that maintain prospect or client lists in Google Docs can trigger a verification pass before exporting to an email tool. Invalid and disposable addresses are flagged, so only clean, deliverable contacts make it to the campaign.
FAQ
Can BillionVerify read email addresses directly from a Google Doc?
BillionVerify verifies addresses passed to it by your automation workflow. n8n or Integrately can extract text from Google Docs and send individual addresses to BillionVerify for checking.
What types of email issues does BillionVerify detect?
It detects syntax errors, invalid or missing MX records, unresponsive mail servers, disposable email domains, role-based addresses, and catch-all domains that mask whether individual mailboxes are real.
Is there a limit to how many addresses I can verify?
BillionVerify supports both real-time single lookups via its REST API and bulk processing for large lists. Your plan's credit balance determines throughput.
Verify emails in Google Docs
Create a free account, grab your API key, and stop bounces before they happen.
Get started free