WeblineIndia This workflow corresponds to n8n.io template #18085 — we link there as the canonical source.
This workflow follows the Chainllm → Gmail recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "mBDfDFwGwOWas8kN",
"name": "Webhook Lead Capture to AI-Based Wealth Scoring & CRM Logging (AI + Sheets + Follow-Up System)",
"tags": [],
"nodes": [
{
"id": "b9ad480d-daef-441c-9fe8-4fbe5297d787",
"name": "Daily Follow-Up Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-16,
2224
],
"parameters": {
"rule": {
"interval": [
{}
]
}
},
"typeVersion": 1.2
},
{
"id": "2eec60f2-8aa6-4bc2-9fc0-04e8692c1847",
"name": "Set Incoming Fields",
"type": "n8n-nodes-base.set",
"position": [
272,
592
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"name": "record_type",
"type": "string",
"value": "={{ ($json.body?.record_type || $json.record_type || '').toString().trim().toLowerCase() }}"
},
{
"name": "source",
"type": "string",
"value": "={{ $json.body?.source || $json.body?.lead_source || $json.body?.advisor_source || 'webhook' }}"
},
{
"name": "received_at",
"type": "string",
"value": "={{ $now }}"
},
{
"name": "raw_payload",
"type": "string",
"value": "={{ JSON.stringify($json.body || $json) }}"
},
{
"name": "advisor_name",
"type": "string",
"value": "={{ $json.body?.advisor_name || '' }}"
},
{
"name": "advisor_email",
"type": "string",
"value": "={{ $json.body?.advisor_email || '' }}"
},
{
"name": "advisor_phone",
"type": "string",
"value": "={{ $json.body?.advisor_phone || '' }}"
},
{
"name": "advisor_type",
"type": "string",
"value": "={{ $json.body?.advisor_type || '' }}"
},
{
"name": "specialization",
"type": "string",
"value": "={{ Array.isArray($json.body?.specialization) ? $json.body.specialization.join(', ') : ($json.body?.specialization || '') }}"
},
{
"name": "experience_years",
"type": "string",
"value": "={{ $json.body?.experience_years || 0 }}"
},
{
"name": "aum_range",
"type": "string",
"value": "={{ $json.body?.aum_range || '' }}"
},
{
"name": "client_type",
"type": "string",
"value": "={{ $json.body?.client_type || '' }}"
},
{
"name": "city",
"type": "string",
"value": "={{ $json.body?.city || '' }}"
},
{
"name": "lead_name",
"type": "string",
"value": "={{ $json.body?.lead_name || $json.body?.full_name || '' }}"
},
{
"name": "lead_email",
"type": "string",
"value": "={{ $json.body?.lead_email || $json.body?.email || '' }}"
},
{
"name": "lead_phone",
"type": "string",
"value": "={{ $json.body?.lead_phone || $json.body?.phone || '' }}"
},
{
"name": "interest_area",
"type": "string",
"value": "={{ $json.body?.interest_area || '' }}"
},
{
"name": "budget_range",
"type": "string",
"value": "={{ $json.body?.budget_range || '' }}"
},
{
"name": "notes",
"type": "string",
"value": "={{ $json.body?.notes || '' }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "9ac03512-544c-4c10-bf65-4bee09e29ea0",
"name": "Normalize Payload",
"type": "n8n-nodes-base.code",
"position": [
464,
592
],
"parameters": {
"jsCode": "const item = $input.first().json;\n\nconst cleanEmail = (v) => (v || '').toString().trim().toLowerCase();\nconst cleanPhone = (v) => (v || '').toString().replace(/\\D/g, '');\nconst cleanText = (v) => (v || '').toString().trim();\n\nconst recordType = cleanText(item.record_type).toLowerCase();\nconst now = new Date().toISOString();\n\nconst out = {\n ...item,\n record_type: recordType,\n source: cleanText(item.source) || 'webhook',\n city: cleanText(item.city),\n created_at: item.created_at || now,\n updated_at: now,\n\n // define these upfront so n8n type checker does not complain\n advisor_id: cleanText(item.advisor_id),\n lead_id: cleanText(item.lead_id),\n\n // keep as string because incoming schema treats it as string\n experience_years: cleanText(item.experience_years),\n};\n\nif (recordType === 'advisor') {\n out.advisor_name = cleanText(item.advisor_name);\n out.advisor_email = cleanEmail(item.advisor_email);\n out.advisor_phone = cleanPhone(item.advisor_phone);\n out.advisor_type = cleanText(item.advisor_type);\n out.specialization = cleanText(item.specialization);\n out.experience_years = cleanText(item.experience_years || '0');\n out.aum_range = cleanText(item.aum_range);\n out.client_type = cleanText(item.client_type);\n out.advisor_id = cleanText(item.advisor_id) || `ADV-${Date.now()}`;\n}\n\nif (recordType === 'lead') {\n out.lead_name = cleanText(item.lead_name);\n out.lead_email = cleanEmail(item.lead_email);\n out.lead_phone = cleanPhone(item.lead_phone);\n out.interest_area = cleanText(item.interest_area);\n out.budget_range = cleanText(item.budget_range);\n out.lead_id = cleanText(item.lead_id) || `LED-${Date.now()}`;\n}\n\nreturn [{ json: out }];"
},
"typeVersion": 2
},
{
"id": "ea436ca6-9d50-420a-9b9c-de3736772698",
"name": "Route By Record Type",
"type": "n8n-nodes-base.switch",
"position": [
656,
592
],
"parameters": {
"rules": {
"values": [
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "06cdd138-2739-4551-b508-895133b9a583",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.record_type }}",
"rightValue": "advisor"
}
]
}
},
{
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "c9ccf3d4-947a-492e-b741-382e819455fc",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.record_type }}",
"rightValue": "lead"
}
]
}
}
]
},
"options": {},
"looseTypeValidation": true
},
"typeVersion": 3.2
},
{
"id": "3ebd5337-6614-49de-8350-5e703e5f2153",
"name": "Read Advisors CRM For Advisor",
"type": "n8n-nodes-base.googleSheets",
"position": [
1216,
208
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM/edit#gid=0",
"cachedResultName": "Advisors_CRM"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM/edit?usp=drivesdk",
"cachedResultName": "Lead & Advisor CRM"
}
},
"typeVersion": 4.5,
"alwaysOutputData": true
},
{
"id": "9d51d741-cdc1-44df-995e-e48192d7c900",
"name": "Check Duplicate And Score Advisor",
"type": "n8n-nodes-base.code",
"position": [
1424,
208
],
"parameters": {
"jsCode": "const incoming = $('Normalize Payload').first().json;\nconst rows = $input.all().map(i => i.json).filter(r => Object.keys(r || {}).length > 0);\n\nconst norm = (v) => String(v || '').trim().toLowerCase();\nconst toNum = (v, fallback = 0) => {\n const n = Number(v);\n return Number.isFinite(n) ? n : fallback;\n};\n\nlet match = null;\nfor (const row of rows) {\n const rowEmail = norm(row.advisor_email);\n const rowPhone = String(row.advisor_phone || '').replace(/\\D/g, '');\n const emailMatch = incoming.advisor_email && rowEmail && norm(incoming.advisor_email) === rowEmail;\n const phoneMatch = incoming.advisor_phone && rowPhone && String(incoming.advisor_phone || '').replace(/\\D/g, '') === rowPhone;\n if (emailMatch || phoneMatch) {\n match = row;\n break;\n }\n}\n\nconst advisorType = norm(incoming.advisor_type);\nconst specializationText = norm(incoming.specialization);\nconst clientType = norm(incoming.client_type);\nconst aumRange = norm(incoming.aum_range);\nconst experience = toNum(incoming.experience_years, 0);\n\nconst specializationList = specializationText\n .split(',')\n .map(s => s.trim())\n .filter(Boolean);\n\nlet score = 0;\n\n// Role strength\nif (advisorType.includes('wealth')) score += 18;\nelse if (advisorType.includes('investment')) score += 14;\nelse if (advisorType.includes('mutual')) score += 12;\nelse if (advisorType.includes('tax')) score += 10;\nelse score += 6;\n\n// Specialization breadth and relevance\nscore += Math.min(specializationList.length, 4) * 6;\nif (specializationText.includes('retirement')) score += 8;\nif (specializationText.includes('sip')) score += 6;\nif (specializationText.includes('tax')) score += 6;\nif (specializationText.includes('wealth')) score += 8;\nif (specializationText.includes('portfolio')) score += 6;\n\n// Experience quality\nif (experience >= 3) score += 8;\nif (experience >= 5) score += 8;\nif (experience >= 10) score += 8;\nif (experience >= 15) score += 4;\n\n// Client segment and AUM fit\nif (clientType.includes('hni')) score += 10;\nelse if (clientType.includes('mixed')) score += 8;\nelse if (clientType.includes('retail')) score += 6;\n\nif (aumRange.includes('10cr')) score += 16;\nelse if (aumRange.includes('5cr')) score += 14;\nelse if (aumRange.includes('1cr') || aumRange.includes('crore')) score += 12;\nelse if (aumRange.includes('50l') || aumRange.includes('25l')) score += 8;\n\n// Data quality / operational readiness\nif (incoming.city) score += 4;\nif (incoming.advisor_email) score += 4;\nif (incoming.advisor_phone) score += 4;\nif (incoming.advisor_email && incoming.advisor_phone) score += 4;\n\nscore = Math.max(0, Math.min(100, Math.round(score)));\n\nlet advisor_grade = 'C';\nlet priority = 'Low';\nlet status = 'needs_review';\n\nif (score >= 80) {\n advisor_grade = 'A';\n priority = 'High';\n status = 'high_value';\n} else if (score >= 60) {\n advisor_grade = 'B';\n priority = 'Medium';\n status = 'qualified';\n} else {\n advisor_grade = 'C';\n priority = 'Low';\n status = 'needs_review';\n}\n\nreturn [{\n json: {\n ...incoming,\n is_duplicate: !!match,\n duplicate_flag: !!match ? 'yes' : 'no',\n existing_advisor_id: match?.advisor_id || null,\n existing_created_at: match?.created_at || incoming.created_at || null,\n active_leads_count: Number(match?.active_leads_count || 0),\n max_capacity: Number(match?.max_capacity || 10),\n availability_status: match?.availability_status || 'available',\n wealth_score: score,\n advisor_grade,\n priority,\n status\n }\n}];"
},
"typeVersion": 2
},
{
"id": "9c8c5390-fd9b-47d4-8593-7df466f01f9d",
"name": "AI Summarize Advisor",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
1616,
176
],
"parameters": {
"text": "=You are enriching an advisor CRM record for assignment in a wealth advisory workflow.\n\nReturn valid JSON only with exactly these keys:\nadvisor_category, normalized_specializations, client_segment_focus, service_tier, ideal_budget_band, service_regions, intake_quality, ai_summary, next_action\n\nAdvisor data:\n{{ JSON.stringify($json) }}\n\nRules:\n- advisor_category must be one of: Wealth Advisor, Retirement Advisor, Mutual Fund Advisor, Tax Advisor, Investment Advisor, Insurance Advisor, General Advisor\n- normalized_specializations must be an array using only these values when relevant:\n [\"wealth_management\",\"retirement_planning\",\"sip\",\"mutual_funds\",\"tax_planning\",\"portfolio_management\",\"stock_investing\",\"insurance\",\"goal_planning\",\"estate_planning\"]\n- client_segment_focus must be one of: HNI, Retail, Mixed\n- service_tier must be one of: Premium, Standard, Entry\n- ideal_budget_band must be one of: High, Mid, Standard\n- service_regions must be an array of city/region strings and can include the advisor city\n- intake_quality must be one of: Strong, Moderate, Basic\n- ai_summary must be 2 short sentences\n- next_action must be one clear CRM action\n- infer from the advisor data only\n- return JSON only",
"batching": {},
"promptType": "define"
},
"typeVersion": 1.7
},
{
"id": "609c2ee0-24ec-4d4f-9b9b-4ed49f97cae0",
"name": "Finalize Advisor Record",
"type": "n8n-nodes-base.code",
"position": [
1904,
208
],
"parameters": {
"jsCode": "const base = $('Check Duplicate And Score Advisor').first().json;\n\nlet raw =\n $input.first().json.text ||\n $input.first().json.response ||\n $input.first().json.content ||\n '{}';\n\nif (typeof raw === 'string') {\n raw = raw.trim();\n raw = raw.replace(/^```json\\s*/i, '');\n raw = raw.replace(/^```/, '');\n raw = raw.replace(/```$/, '');\n raw = raw.trim();\n}\n\nlet parsed = {};\ntry {\n parsed = typeof raw === 'string' ? JSON.parse(raw) : raw;\n} catch (e) {\n parsed = {};\n}\n\nconst norm = (v) => String(v || '').trim();\nconst normLower = (v) => String(v || '').trim().toLowerCase();\nconst uniq = (arr) => [...new Set(arr.filter(Boolean))];\n\nconst keywordMap = [\n ['retirement', 'retirement_planning'],\n ['sip', 'sip'],\n ['mutual', 'mutual_funds'],\n ['tax', 'tax_planning'],\n ['wealth', 'wealth_management'],\n ['portfolio', 'portfolio_management'],\n ['stock', 'stock_investing'],\n ['equity', 'stock_investing'],\n ['insurance', 'insurance'],\n ['goal', 'goal_planning'],\n ['estate', 'estate_planning']\n];\n\nconst toSpecializations = (value) => {\n if (Array.isArray(value)) return uniq(value.map(v => normLower(v)));\n const text = normLower(value);\n if (!text) return [];\n const tags = [];\n for (const [needle, tag] of keywordMap) {\n if (text.includes(needle)) tags.push(tag);\n }\n return uniq(tags.length ? tags : text.split(',').map(s => s.trim()).filter(Boolean));\n};\n\nconst rawSpecs = toSpecializations(parsed.normalized_specializations);\nconst fallbackSpecs = toSpecializations(base.specialization);\nconst normalizedSpecializations = uniq(rawSpecs.length ? rawSpecs : fallbackSpecs);\n\nconst advisorCategory = norm(parsed.advisor_category) || (\n normLower(base.advisor_type).includes('retirement') ? 'Retirement Advisor' :\n normLower(base.advisor_type).includes('mutual') ? 'Mutual Fund Advisor' :\n normLower(base.advisor_type).includes('tax') ? 'Tax Advisor' :\n normLower(base.advisor_type).includes('investment') ? 'Investment Advisor' :\n normLower(base.advisor_type).includes('insurance') ? 'Insurance Advisor' :\n normLower(base.advisor_type).includes('wealth') ? 'Wealth Advisor' :\n 'General Advisor'\n);\n\nconst clientSegmentFocus = ['HNI', 'Retail', 'Mixed'].includes(parsed.client_segment_focus)\n ? parsed.client_segment_focus\n : (normLower(base.client_type).includes('hni') ? 'HNI' : normLower(base.client_type).includes('retail') ? 'Retail' : 'Mixed');\n\nconst serviceTier = ['Premium', 'Standard', 'Entry'].includes(parsed.service_tier)\n ? parsed.service_tier\n : (Number(base.wealth_score || 0) >= 80 ? 'Premium' : Number(base.wealth_score || 0) >= 60 ? 'Standard' : 'Entry');\n\nconst idealBudgetBand = ['High', 'Mid', 'Standard'].includes(parsed.ideal_budget_band)\n ? parsed.ideal_budget_band\n : (\n normLower(base.aum_range).includes('10cr') || normLower(base.aum_range).includes('5cr') || normLower(base.client_type).includes('hni')\n ? 'High'\n : normLower(base.aum_range).includes('1cr') || normLower(base.aum_range).includes('50l')\n ? 'Mid'\n : 'Standard'\n );\n\nconst serviceRegions = uniq(\n (Array.isArray(parsed.service_regions) ? parsed.service_regions : [parsed.service_regions, base.city])\n .map(v => norm(v))\n .filter(Boolean)\n);\n\nconst profile = {\n advisor_category: advisorCategory,\n normalized_specializations: normalizedSpecializations,\n client_segment_focus: clientSegmentFocus,\n service_tier: serviceTier,\n ideal_budget_band: idealBudgetBand,\n service_regions: serviceRegions,\n intake_quality: ['Strong', 'Moderate', 'Basic'].includes(parsed.intake_quality) ? parsed.intake_quality : (Number(base.wealth_score || 0) >= 75 ? 'Strong' : Number(base.wealth_score || 0) >= 55 ? 'Moderate' : 'Basic')\n};\n\nconst originalNotes = norm(base.notes);\nconst profileBlock = `PROFILE::${JSON.stringify(profile)}`;\nconst notes = originalNotes\n ? (originalNotes.includes('PROFILE::') ? originalNotes.replace(/PROFILE::\\{.*\\}$/s, profileBlock) : `${originalNotes}\\n${profileBlock}`)\n : profileBlock;\n\nreturn [{\n json: {\n advisor_id: base.existing_advisor_id || base.advisor_id,\n advisor_name: base.advisor_name,\n advisor_email: base.advisor_email,\n advisor_phone: base.advisor_phone,\n city: base.city,\n advisor_type: advisorCategory,\n specialization: normalizedSpecializations.join(', '),\n experience_years: Number(base.experience_years || 0),\n aum_range: base.aum_range,\n client_type: clientSegmentFocus,\n wealth_score: Number(base.wealth_score || 0),\n advisor_grade: base.advisor_grade,\n priority: base.priority,\n status: base.status,\n ai_summary: parsed.ai_summary || 'Advisor profile standardized and ready for lead assignment.',\n next_action: parsed.next_action || 'Review advisor capacity and activate for matching.',\n source: base.source,\n created_at: base.existing_created_at || base.created_at || new Date().toISOString(),\n updated_at: new Date().toISOString(),\n duplicate_flag: base.duplicate_flag,\n notes,\n active_leads_count: Number(base.active_leads_count || 0),\n max_capacity: Number(base.max_capacity || 10),\n availability_status: base.availability_status || 'available'\n }\n}];"
},
"typeVersion": 2
},
{
"id": "207d7802-9d11-4709-9510-dabc4bc4df51",
"name": "Save Advisor Record",
"type": "n8n-nodes-base.googleSheets",
"position": [
2192,
208
],
"parameters": {
"columns": {
"value": {
"city": "={{ $json.city }}",
"notes": "={{ $json.notes }}",
"source": "={{ $json.source }}",
"status": "={{ $json.status }}",
"priority": "={{ $json.priority }}",
"aum_range": "={{ $json.aum_range }}",
"advisor_id": "={{ $json.advisor_id }}",
"ai_summary": "={{ $json.ai_summary }}",
"created_at": "={{ $json.created_at }}",
"updated_at": "={{ $json.updated_at }}",
"client_type": "={{ $json.client_type }}",
"next_action": "={{ $json.next_action }}",
"advisor_name": "={{ $json.advisor_name }}",
"advisor_type": "={{ $json.advisor_type }}",
"max_capacity": "={{ $json.max_capacity }}",
"wealth_score": "={{ $json.wealth_score }}",
"advisor_email": "={{ $json.advisor_email }}",
"advisor_grade": "={{ $json.advisor_grade }}",
"advisor_phone": "={{ $json.advisor_phone }}",
"duplicate_flag": "={{ $json.duplicate_flag }}",
"specialization": "={{ $json.specialization }}",
"experience_years": "={{ $json.experience_years }}",
"active_leads_count": "={{ $json.active_leads_count }}",
"availability_status": "={{ $json.availability_status }}"
},
"schema": [
{
"id": "advisor_id",
"type": "string",
"display": true,
"required": false,
"displayName": "advisor_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "advisor_name",
"type": "string",
"display": true,
"required": false,
"displayName": "advisor_name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "advisor_email",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "advisor_email",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "advisor_phone",
"type": "string",
"display": true,
"required": false,
"displayName": "advisor_phone",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "city",
"type": "string",
"display": true,
"required": false,
"displayName": "city",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "advisor_type",
"type": "string",
"display": true,
"required": false,
"displayName": "advisor_type",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "specialization",
"type": "string",
"display": true,
"required": false,
"displayName": "specialization",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "experience_years",
"type": "string",
"display": true,
"required": false,
"displayName": "experience_years",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "aum_range",
"type": "string",
"display": true,
"required": false,
"displayName": "aum_range",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "client_type",
"type": "string",
"display": true,
"required": false,
"displayName": "client_type",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "wealth_score",
"type": "string",
"display": true,
"required": false,
"displayName": "wealth_score",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "advisor_grade",
"type": "string",
"display": true,
"required": false,
"displayName": "advisor_grade",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "priority",
"type": "string",
"display": true,
"required": false,
"displayName": "priority",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "status",
"type": "string",
"display": true,
"required": false,
"displayName": "status",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "ai_summary",
"type": "string",
"display": true,
"required": false,
"displayName": "ai_summary",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "next_action",
"type": "string",
"display": true,
"required": false,
"displayName": "next_action",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "source",
"type": "string",
"display": true,
"required": false,
"displayName": "source",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "created_at",
"type": "string",
"display": true,
"required": false,
"displayName": "created_at",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "updated_at",
"type": "string",
"display": true,
"required": false,
"displayName": "updated_at",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "duplicate_flag",
"type": "string",
"display": true,
"required": false,
"displayName": "duplicate_flag",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "notes",
"type": "string",
"display": true,
"required": false,
"displayName": "notes",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "active_leads_count",
"type": "string",
"display": true,
"required": false,
"displayName": "active_leads_count",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "max_capacity",
"type": "string",
"display": true,
"required": false,
"displayName": "max_capacity",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "availability_status",
"type": "string",
"display": true,
"required": false,
"displayName": "availability_status",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"advisor_email"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "appendOrUpdate",
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM/edit#gid=0",
"cachedResultName": "Advisors_CRM"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM/edit?usp=drivesdk",
"cachedResultName": "Lead & Advisor CRM"
}
},
"typeVersion": 4.5
},
{
"id": "486bd067-ff42-4ccb-9972-0ffe27460642",
"name": "Append Advisor Activity Log",
"type": "n8n-nodes-base.googleSheets",
"position": [
2640,
208
],
"parameters": {
"columns": {
"value": {
"log_id": "={{ $json.log_id }}",
"record_id": "={{ $json.record_id }}",
"timestamp": "={{ $json.timestamp }}",
"action_type": "={{ $json.action_type }}",
"record_type": "={{ $json.record_type }}",
"workflow_name": "={{ $json.workflow_name }}",
"action_details": "={{ $json.action_details }}"
},
"schema": [
{
"id": "log_id",
"type": "string",
"display": true,
"required": false,
"displayName": "log_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "record_type",
"type": "string",
"display": true,
"required": false,
"displayName": "record_type",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "record_id",
"type": "string",
"display": true,
"required": false,
"displayName": "record_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "action_type",
"type": "string",
"display": true,
"required": false,
"displayName": "action_type",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "action_details",
"type": "string",
"display": true,
"required": false,
"displayName": "action_details",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "timestamp",
"type": "string",
"display": true,
"required": false,
"displayName": "timestamp",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "workflow_name",
"type": "string",
"display": true,
"required": false,
"displayName": "workflow_name",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 829720620,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM/edit#gid=829720620",
"cachedResultName": "Activity_Log"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM/edit?usp=drivesdk",
"cachedResultName": "Lead & Advisor CRM"
}
},
"typeVersion": 4.5
},
{
"id": "dfb022d7-e897-4d83-aff4-092c3deda652",
"name": "Read Leads CRM",
"type": "n8n-nodes-base.googleSheets",
"position": [
976,
800
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": 127192940,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM/edit#gid=127192940",
"cachedResultName": "Leads_CRM"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM/edit?usp=drivesdk",
"cachedResultName": "Lead & Advisor CRM"
}
},
"typeVersion": 4.5,
"alwaysOutputData": true
},
{
"id": "22ff3f8b-c711-44b8-b054-6ed7f7f552ae",
"name": "Check Duplicate And Score Lead",
"type": "n8n-nodes-base.code",
"position": [
1152,
800
],
"parameters": {
"jsCode": "const incoming = $('Normalize Payload').first().json;\nconst rows = $input.all().map(i => i.json).filter(r => Object.keys(r || {}).length > 0);\n\nconst norm = (v) => String(v || '').trim().toLowerCase();\n\nlet match = null;\nfor (const row of rows) {\n const rowEmail = norm(row.lead_email);\n const rowPhone = String(row.lead_phone || '').replace(/\\D/g, '');\n const emailMatch = incoming.lead_email && rowEmail && norm(incoming.lead_email) === rowEmail;\n const phoneMatch = incoming.lead_phone && rowPhone && String(incoming.lead_phone || '').replace(/\\D/g, '') === rowPhone;\n if (emailMatch || phoneMatch) {\n match = row;\n break;\n }\n}\n\nconst interest = norm(incoming.interest_area);\nconst budget = norm(incoming.budget_range);\nconst source = norm(incoming.source);\n\nlet score = 0;\n\n// Intent richness\nif (interest.includes('retirement')) score += 18;\nif (interest.includes('sip')) score += 12;\nif (interest.includes('wealth')) score += 14;\nif (interest.includes('tax')) score += 10;\nif (interest.includes('portfolio')) score += 10;\nif (interest.includes('investment')) score += 12;\n\n// Buying power / potential\nif (budget.includes('1cr') || budget.includes('crore')) score += 30;\nelse if (budget.includes('50l')) score += 24;\nelse if (budget.includes('25l')) score += 18;\nelse if (budget.includes('10l')) score += 12;\n\n// Data quality\nif (incoming.city) score += 8;\nif (incoming.lead_email) score += 8;\nif (incoming.lead_phone) score += 8;\nif (incoming.lead_email && incoming.lead_phone) score += 6;\n\n// Source quality\nif (source.includes('referral')) score += 14;\nelse if (source.includes('campaign')) score += 10;\nelse if (source.includes('website')) score += 6;\n\nscore = Math.max(0, Math.min(100, Math.round(score)));\n\nlet lead_grade = 'C';\nlet priority = 'Low';\nlet status = 'needs_review';\n\nif (score >= 75) {\n lead_grade = 'A';\n priority = 'High';\n status = 'qualified';\n} else if (score >= 50) {\n lead_grade = 'B';\n priority = 'Medium';\n status = 'qualified';\n}\n\nreturn [{\n json: {\n ...incoming,\n is_duplicate: !!match,\n duplicate_flag: !!match ? 'yes' : 'no',\n existing_lead_id: match?.lead_id || null,\n existing_created_at: match?.created_at || incoming.created_at || null,\n interaction_count: Number(match?.interaction_count || 0) + 1,\n lead_score: score,\n lead_grade,\n priority,\n status\n }\n}];"
},
"typeVersion": 2
},
{
"id": "26b11c16-6549-4c62-9baa-406dfeec22bd",
"name": "AI Summarize Lead",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
1328,
800
],
"parameters": {
"text": "=You are enriching a lead CRM record for a wealth advisory workflow.\n\nReturn valid JSON only with exactly these keys:\nwealth_score, investment_potential, urgency, primary_need, secondary_needs, lead_segment, budget_band, ai_summary, next_action\n\nLead data:\n{{ JSON.stringify($json) }}\n\nRules:\n- wealth_score must be a number from 0 to 100\n- investment_potential must be one of: High, Medium, Low\n- urgency must be one of: High, Medium, Low\n- primary_need must be one of:\n retirement_planning, wealth_management, sip, mutual_funds, tax_planning, portfolio_management, stock_investing, insurance, goal_planning, general_investment\n- secondary_needs must be an array using only the same allowed values\n- lead_segment must be one of: HNI, Affluent, Retail\n- budget_band must be one of: High, Mid, Standard\n- ai_summary must be 2 short sentences\n- next_action must be one clear CRM action\n- infer from the lead data only\n- return JSON only",
"batching": {},
"promptType": "define"
},
"typeVersion": 1.7
},
{
"id": "faa7c462-b3eb-4922-b6b1-aa046c1c43ed",
"name": "Read Advisors For Assignment",
"type": "n8n-nodes-base.googleSheets",
"position": [
1616,
800
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM/edit#gid=0",
"cachedResultName": "Advisors_CRM"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1q31d9V8kC7FRc43n7Q7ST9YunSuQrLZ1DyCIpnLnshM/edit?usp=drivesdk",
"cachedResultName": "Lead & Advisor CRM"
}
},
"typeVersion": 4.5
},
{
"id": "14d0049c-d334-4917-9c23-ae07e114b963",
"name": "Assign Advisor Finalize Lead",
"type": "n8n-nodes-base.code",
"position": [
2144,
832
],
"parameters": {
"jsCode": "const base = $('Check Duplicate And Score Lead').first().json;\nconst advisors = $('Read Advisors For Assignment').all().map(i => i.json).filter(r => Object.keys(r || {}).length > 0);\nconst aiNode = $('AI Summarize Lead').first().json;\n\nlet raw = aiNode.text || aiNode.response || aiNode.content || '{}';\nif (typeof raw === 'string') {\n raw = raw.trim();\n raw = raw.replace(/^```json\\s*/i, '');\n raw = raw.replace(/^```/, '');\n raw = raw.replace(/```$/, '');\n raw = raw.trim();\n}\n\nlet parsed = {};\ntry {\n parsed = typeof raw === 'string' ? JSON.parse(raw) : raw;\n} catch (e) {\n parsed = {};\n}\n\nconst norm = (v) => String(v || '').trim().toLowerCase();\nconst toNum = (v, fallback = 0) => {\n const n = Number(v);\n return Number.isFinite(n) ? n : fallback;\n};\nconst uniq = (arr) => [...new Set(arr.filter(Boolean))];\n\nconst keywordMap = [\n ['retirement', 'retirement_planning'],\n ['sip', 'sip'],\n ['mutual', 'mutual_funds'],\n ['tax', 'tax_planning'],\n ['wealth', 'wealth_management'],\n ['portfolio', 'portfolio_management'],\n ['stock', 'stock_investing'],\n ['equity', 'stock_investing'],\n ['insurance', 'insurance'],\n ['goal', 'goal_planning'],\n ['investment', 'general_investment']\n];\n\nconst normalizeNeed = (value) => {\n const text = norm(value);\n if (!text) return [];\n const tags = [];\n for (const [needle, tag] of keywordMap) {\n if (text.includes(needle)) tags.push(tag);\n }\n return uniq(tags);\n};\n\nconst parseProfileFromNotes = (notes) => {\n const text = String(notes || '');\n const match = text.match(/PROFILE::(\\{.*\\})/s);\n if (!match) return {};\n try {\n return JSON.parse(match[1]);\n } catch (e) {\n return {};\n }\n};\n\nconst primaryNeed = String(parsed.primary_need || '').trim() || (normalizeNeed(base.interest_area)[0] || 'general_investment');\nconst secondaryNeeds = Array.isArray(parsed.secondary_needs) ? parsed.secondary_needs.map(v => String(v).trim()).filter(Boolean) : [];\nconst leadNeeds = uniq([primaryNeed, ...secondaryNeeds, ...normalizeNeed(base.interest_area)]);\nconst leadCity = norm(base.city);\nconst budgetBand = ['High', 'Mid', 'Standard'].includes(parsed.budget_band)\n ? parsed.budget_band\n : (\n norm(base.budget_range).includes('1cr') || norm(base.budget_range).includes('crore')\n ? 'High'\n : norm(base.budget_range).includes('50l') || norm(base.budget_range).includes('25l')\n ? 'Mid'\n : 'Standard'\n );\n\nconst leadSegment = ['HNI', 'Affluent', 'Retail'].includes(parsed.lead_segment)\n ? parsed.lead_segment\n : (budgetBand === 'High' ? 'HNI' : budgetBand === 'Mid' ? 'Affluent' : 'Retail');\n\nconst allowedStatuses = ['qualified', 'high_value', 'active', 'approved'];\nconst scoredCandidates = [];\nconst fallbackCandidates = [];\n\nfor (const adv of advisors) {\n const status = norm(adv.status || 'active');\n const availability = norm(adv.availability_status || 'available');\n const activeLeads = toNum(adv.active_leads_count, 0);\n const maxCapacity = Math.max(toNum(adv.max_capacity, 10), 1);\n\n if (availability !== 'available') continue;\n if (status && !allowedStatuses.includes(status)) continue;\n if (activeLeads >= maxCapacity) continue;\n\n const profile = parseProfileFromNotes(adv.notes);\n const advisorCategory = String(profile.advisor_category || adv.advisor_type || '').trim();\n const specializationTags = uniq(\n Array.isArray(profile.normalized_specializations)\n ? profile.normalized_specializations.map(v => String(v).trim()).filter(Boolean)\n : String(adv.specialization || '')\n .split(',')\n .map(s => s.trim())\n .filter(Boolean)\n .flatMap(normalizeNeed)\n );\n const clientSegmentFocus = String(profile.client_segment_focus || adv.client_type || 'Mixed').trim();\n const serviceTier = String(profile.service_tier || '').trim() || (toNum(adv.wealth_score) >= 80 ? 'Premium' : toNum(adv.wealth_score) >= 60 ? 'Standard' : 'Entry');\n const idealBudgetBand = String(profile.ideal_budget_band || '').trim() || (clientSegmentFocus === 'HNI' ? 'High' : clientSegmentFocus === 'Mixed' ? 'Mid' : 'Standard');\n const advisorCity = norm(adv.city);\n const utilization = activeLeads / maxCapacity;\n const advisorScore = Math.max(0, Math.min(100, toNum(adv.wealth_score)));\n\n let semanticScore = 0;\n const reasons = [];\n const overlap = leadNeeds.filter(tag => specializationTags.includes(tag));\n\n if (overlap.length) {\n semanticScore += overlap.includes(primaryNeed) ? 40 : 0;\n semanticScore += overlap.filter(tag => tag !== primaryNeed).length * 12;\n reasons.push(`Need match: ${overlap.join(', ')}`);\n }\n\n const categoryNeedMap = {\n 'Wealth Advisor': ['wealth_management', 'general_investment', 'goal_planning', 'portfolio_management'],\n 'Retirement Advisor': ['retirement_planning', 'goal_planning', 'wealth_management'],\n 'Mutual Fund Advisor': ['mutual_funds', 'sip', 'general_investment'],\n 'Tax Advisor': ['tax_planning'],\n 'Investment Advisor': ['stock_investing', 'portfolio_management', 'general_investment'],\n 'Insurance Advisor': ['insurance', 'goal_planning'],\n 'General Advisor': ['general_investment', 'goal_planning']\n };\n\n if ((categoryNeedMap[advisorCategory] || []).includes(primaryNeed)) {\n semanticScore += 18;\n reasons.push(`Advisor category fit: ${advisorCategory}`);\n }\n\n let geographyScore = 0;\n if (leadCity && advisorCity && leadCity === advisorCity) {\n geographyScore += 12;\n reasons.push('City match');\n } else if (!advisorCity) {\n geographyScore += 4;\n }\n\n let segmentScore = 0;\n if (leadSegment === 'HNI' && clientSegmentFocus === 'HNI') {\n segmentScore += 18;\n reasons.push('HNI segment fit');\n } else if (leadSegment === 'HNI' && clientSegmentFocus === 'Mixed') {\n segmentScore += 10;\n } else if (leadSegment === 'Affluent' && ['Mixed', 'HNI', 'Retail'].includes(clientSegmentFocus)) {\n segmentScore += clientSegmentFocus === 'Mixed' ? 14 : 10;\n reasons.push('Affluent segment fit');\n } else if (leadSegment === 'Retail' && ['Retail', 'Mixed'].includes(clientSegmentFocus)) {\n segmentScore += clientSegmentFocus === 'Retail' ? 14 : 10;\n reasons.push('Retail segment fit');\n }\n\n let budgetScore = 0;\n if (budgetBand === idealBudgetBand) {\n budgetScore += 14;\n reasons.push(`Budget fit: ${budgetBand}`);\n } else if (budgetBand === 'High' && serviceTier === 'Premium') {\n budgetScore += 12;\n } else if (budgetBand === 'Mid' && ['Premium', 'Standard'].includes(serviceTier)) {\n budgetScore += 10;\n } else if (budgetBand === 'Standard') {\n budgetScore += 8;\n }\n\n const experienceScore = Math.min(toNum(adv.experience_years, 0), 15) * 0.5;\n const qualityScore = advisorScore * 0.08;\n const loadScore = Math.max(0, (1 - utilization) * 10);\n\n const totalScore = semanticScore + geographyScore + segmentScore + budgetScore + experienceScore + qualityScore + loadScore;\n\n const candidate = {\n advisor: adv,\n totalScore,\n semanticScore,\n reasons,\n activeLeads,\n maxCapacity\n };\n\n if (semanticScore > 0 || segmentScore >= 10) {\n scoredCandidates.push(candidate);\n } else {\n fallbackCandidates.push(candidate);\n }\n}\n\nconst orderedCandidates = (scoredCandidates.length ? scoredCandidates : fallbackCandidates)\n .sort((a, b) => b.totalScore - a.totalScore || a.activeLeads - b.activeLeads || b.advisor.wealth_score - a.advisor.wealth_score);\n\nconst selected = orderedCandidates[0] || null;\nconst best = selected?.advisor || null;\nconst bestScore = selected ? Math.round(selected.totalScore) : 0;\nconst matchReason = selected?.reasons?.length ? selected.reasons.join(' | ') : (best ? 'Assigned using fallback availability and quality rules' : 'No eligible advisor available');\n\nconst followUpDate = new Date();\nconst effectiveUrgency = ['High', 'Medium', 'Low'].includes(parsed.urgency)\n ? parsed.urgency\n : (base.priority === 'High' ? 'High' : base.priority === 'Medium' ? 'Medium' : 'Low');\n\nif (effectiveUrgency === 'High') followUpDate.setDate(followUpDate.getDate() + 1);\nelse if (effectiveUrgency === 'Medium') followUpDate.setDate(followUpDate.getDate() + 2);\nelse followUpDate.setDate(followUpDate.getDate() + 4);\n\nconst wealthScore = Math.max(0, Math.min(100, toNum(parsed.wealth_score ?? base.lead_score, 0)));\nconst investmentPotential = ['High', 'Medium', 'Low'].includes(parsed.investment_potential)\n ? parsed.investment_potential\n : (base.priority === 'High' ? 'High' : base.priority === 'Medium' ? 'Medium' : 'Low');\n\nreturn [{\n json: {\n lead_id: base.existing_lead_id || base.lead_id,\n lead_name: base.lead_name,\n lead_email: base.lead_email,\n lead_phone: base.lead_phone,\n city: base.city,\n interest_area: base.interest_area,\n budget_range: base.budget_range,\n lead_source: base.source,\n lead_score: Number(base.lead_score || 0),\n wealth_score: wealthScore,\n investment_potential: investmentPotential,\n lead_grade: base.lead_grade,\n priority: base.priority,\n priority_queue_rank: base.priority === 'High' ? 1 : base.priority === 'Medium' ? 2 : 3,\n status: best ? 'assigned' : base.status,\n assigned_advisor_id: best?.advisor_id || '',\n assigned_advisor_name: best?.advisor_name || '',\n assigned_advisor_email: best?.advisor_email || '',\n advisor_match_score: bestScore,\n urgency: effectiveUrgency,\n intent: primaryNeed,\n ai_summary: parsed.ai_summary || 'Lead scored successfully and is ready for advisor review.',\n next_action: parsed.next_action || (best ? 'Assigned to the best-fit available advisor based on need, segment, capacity, and city.' : 'No eligible advisor found. Review manually and assign.'),\n next_action_date: followUpDate.toISOString().slice(0, 10),\n follow_up_required: 'yes',\n last_contacted_at: '',\n created_at: base.existing_created_at || base.created_at || new Date().toISOString(),\n updated_at: new Date().toISOString(),\n duplicate_flag: base.duplicate_flag,\n notes: [base.notes, `ASSIGNMENT_REASON::${matchReason}`].filter(Boolean).join('\\n'),\n interaction_count: Number(base.interaction_count || 1),\n assigned_advisor_reason: matchReason\n }\n}];"
},
"typeVersion": 2
},
{
"id": "dbb42561-afda-4fb7-98e5-0400adc19f63",
"name": "Save Lead Record",
"type": "n8n-nodes-base.googleSheets",
"position": [
2320,
832
],
"parameters": {
"columns": {
"value": {
"city": "={{ $json.city }}",
"notes": "={{ $json.notes }}",
"intent": "={{ $json.intent }}",
"status": "={{ $json.status }}",
"lead_id": "={{ $json.lead_id }}",
"urgency": "={{ $json.urgency }}",
"priority": "={{ $json.priority }}",
"lead_name": "={{ $json.lead_name }}",
"ai_summary": "={{ $json.ai_summary }}",
"created_at": "={{ $json.created_at }}",
"lead_email": "={{ $json.lead_email }}",
"lead_grade": "={{ $json.lead_grade }}",
"lead_phone": "={{ $json.lead_phone }}",
"lead_score": "={{ $json.lead_score }}",
"updated_at": "={{ $json.updated_at }}",
"lead_source": "={{ $json.lead_source }}",
"next_action": "={{ $json.next_action }}",
"budget_range": "={{ $json.budget_range }}",
"wealth_score": "={{ $json.wealth_score }}",
"interest_area": "={{ $json.interest_area }}",
"duplicate_flag": "={{ $json.duplicate_flag }}",
"next_action_date": "={{ $json.next_action_date }}",
"interaction_count": "={{ $json.interaction_count }}",
"last_contacted_at": "={{ $json.last_contacted_at }}",
"follow_up_required": "={{ $json.follow_up_required }}",
"advisor_match_score": "={{ $json.advisor_match_score }}",
"assigned_advisor_id": "={{ $json.assigned_advisor_id }}",
"priority_queue_rank": "={{ $json.priority_queue_rank }}",
"investment_potential": "={{ $json.investment_potential }}",
"assigned_advisor_name": "={{ $json.assigned_advisor_name }}",
"assigned_advisor_email": "={{ $json.assigned_advisor_email }}"
},
"schema": [
{
"id": "lead_id",
"type": "string",
"display": true,
"required": false,
"displayName": "lead_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "lead_name",
"type": "string",
"display": true,
"required": false,
"displayName": "lead_name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "lead_email",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "lead_email",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "lead_phone",
"type": "string",
"display": true,
"required": false,
"displayName": "lead_phone",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "city",
"type": "string",
"display": true,
"required": false,
"displayName": "city",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "interest_area",
"type": "string",
"display": true,
"required": false,
"displayName": "interest_area",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "budget_range",
"type": "string",
"display": true,
"required": false,
"displayName": "budget_range",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "lead_source",
"type": "string",
"display": true,
"required": false,
"displayName": "lead_source",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "lead_score",
"type": "string",
"display": true,
"required": false,
"displayName": "lead_score",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "lead_grade",
"type": "string",
"display": true,
"required": false,
"displayName": "lead_grade",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "priority",
"type": "string",
"display": true,
"required": false,
"displayName": "priority",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "priority_queue_rank",
"type": "string",
"display": true,
"required": false,
"displayName": "priority_queue_rank",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "status",
"type": "string",
"display": true,
"required": false,
"displayName": "status",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "assigned_advisor_id",
"type": "string",
"display": true,
"required": false,
"displayName": "assigned_advisor_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "assigned_advisor_name",
"type": "string",
"display": true,
"required": false,
"displayName": "assigned_advisor_name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "advisor_match_score",
"type": "string",
"display": true,
"required": false,
"displayName": "advisor_match_score",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "urgency",
"type": "string",
"display": true,
"required": false,
"displayName": "urgency",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "intent",
"type": "string",
"display": true,
"required": false,
"displayName": "intent",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "ai_summary",
"type": "string",
"display": true,
"required": false,
"displayName": "ai_summary",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "next_action",
"type": "string",
"display": true,
"required": false,
"displayName": "next_action",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "next_action_date",
"type": "string",
"display": true,
"required": false,
"displayName": "next_action_date",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "follow_up_required",
"type": "string",
"display": true,
"required": false,
"displayName": "follow_up_required",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "last_contacted_at",
"type": "string",
"display": true,
"required": false,
"displayName": "last_contacted_at",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "created_at",
"type": "string",
"display": true,
"required": false,
"displayName": "created_at",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "updated_at",
"type": "string",
"display": true,
"required": false,
"displayName": "updated_at",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "duplicate_flag",
"type": "string",
"display": true,
"required": false,
"displayName": "duplicate_flag",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "notes",
"type": "string",
"display": true,
"required": false,
"displayName": "notes",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "interaction_count",
"type": "string",
"display": true,
"required": false,
"displayName": "interaction_count",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "wealth_score",
"type": "string",
"display": true,
"required": false,
"displayName": "wealth_score",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "investment_potential",
"type": "string",
"display": true,
"required": false,
"displayName": "investment_potential",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "assigned_advisor_email",
"type": "string",
"display": true,
"required": false,
"displayName": "assigned_advisor_email",
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About this workflow
This workflow captures advisor and lead submissions via webhooks, scores and enriches them with Google Gemini, and stores them in Google Sheets as a lightweight CRM. It auto-assigns leads to available advisors, sends Gmail notifications, runs daily follow-up reminders, and…
Source: https://n8n.io/workflows/18085/ — original creator credit. Request a take-down →
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