{ "name": "WF-008 Monthly Report", "nodes": [ { "parameters": { "rule": { "interval": [ { "field": "cronExpression", "expression": "0 9 1 * *" } ] } }, "id": "wf008-node-schedule", "name": "1st of Month 9AM ET", "type": "n8n-nodes-base.scheduleTrigger", "typeVersion": 1.2, "position": [ 0, 300 ] }, { "parameters": { "operation": "getAll", "tableId": "tenants", "returnAll": true, "filterType": "string", "filterString": "subscription_status=eq.active" }, "id": "wf008-node-get-tenants", "name": "Get Active Tenants", "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 250, 300 ], "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "batchSize": 1, "options": {} }, "id": "wf008-node-loop", "name": "Loop Over Tenants", "type": "n8n-nodes-base.splitInBatches", "typeVersion": 3, "position": [ 500, 300 ] }, { "parameters": { "method": "GET", "url": "https://yepggeqhtspgzlkhqhgo.supabase.co/rest/v1/usage_monthly", "authentication": "predefinedCredentialType", "nodeCredentialType": "supabaseApi", "sendQuery": true, "queryParameters": { "parameters": [ { "name": "tenant_id", "value": "={{ 'eq.' + $('Loop Over Tenants').item.json.id }}" }, { "name": "year_month", "value": "={{ (() => { const d = new Date(); d.setMonth(d.getMonth() - 1); return 'eq.' + d.getFullYear() + '-' + String(d.getMonth() + 1).padStart(2, '0'); })() }}" }, { "name": "select", "value": "*" } ] } }, "id": "wf008-node-get-monthly", "name": "Get Monthly Usage", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 750, 300 ], "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "method": "GET", "url": "https://yepggeqhtspgzlkhqhgo.supabase.co/rest/v1/usage_daily", "authentication": "predefinedCredentialType", "nodeCredentialType": "supabaseApi", "sendQuery": true, "queryParameters": { "parameters": [ { "name": "tenant_id", "value": "={{ 'eq.' + $('Loop Over Tenants').item.json.id }}" }, { "name": "date", "value": "={{ (() => { const d = new Date(); d.setMonth(d.getMonth() - 1); const start = d.getFullYear() + '-' + String(d.getMonth() + 1).padStart(2, '0') + '-01'; const end = new Date(d.getFullYear(), d.getMonth() + 1, 0).toISOString().split('T')[0]; return 'gte.' + start + '&date=lte.' + end; })() }}" }, { "name": "select", "value": "*" }, { "name": "order", "value": "date.asc" } ] } }, "id": "wf008-node-get-daily", "name": "Get Daily Trends", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 1000, 300 ], "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "jsCode": "// Compute monthly insights from daily and monthly data\nconst dailyItems = $input.all();\nconst monthlyData = $('Get Monthly Usage').first().json || {};\nconst tenant = $('Loop Over Tenants').item.json;\n\nconst dailyRecords = dailyItems.map(i => i.json).filter(d => d.date);\n\n// Previous month label\nconst prevDate = new Date();\nprevDate.setMonth(prevDate.getMonth() - 1);\nconst monthLabel = prevDate.toLocaleDateString('en-US', { year: 'numeric', month: 'long' });\n\n// Basic stats from monthly summary\nconst totalCalls = monthlyData.total_calls || 0;\nconst totalMinutes = monthlyData.total_minutes || 0;\nconst answered = monthlyData.answered || 0;\nconst missed = monthlyData.missed || 0;\nconst voicemail = monthlyData.voicemail || 0;\nconst escalations = monthlyData.escalations || 0;\nconst daysInMonth = dailyRecords.length || 1;\n\n// Computed insights\nconst avgCallsPerDay = Math.round(totalCalls / daysInMonth * 10) / 10;\nconst answerRate = totalCalls > 0 ? Math.round((answered / totalCalls) * 100) : 0;\nconst missRate = totalCalls > 0 ? Math.round((missed / totalCalls) * 100) : 0;\nconst escalationRate = totalCalls > 0 ? Math.round((escalations / totalCalls) * 100) : 0;\n\n// Busiest day\nlet busiestDay = { date: 'N/A', calls: 0 };\nfor (const day of dailyRecords) {\n if ((day.total_calls || 0) > busiestDay.calls) {\n busiestDay = {\n date: new Date(day.date).toLocaleDateString('en-US', { weekday: 'long', month: 'short', day: 'numeric' }),\n calls: day.total_calls\n };\n }\n}\n\n// Time & cost savings (1.5x multiplier, $25/hr)\nconst totalHours = Math.round(totalMinutes / 60 * 100) / 100;\nconst hoursSaved = Math.round(totalHours * 1.5 * 100) / 100;\nconst laborCostSaved = Math.round(hoursSaved * 25 * 100) / 100;\n\n// Resolution rate (answered without escalation)\nconst resolvedWithoutEscalation = answered - escalations;\nconst resolutionRate = answered > 0 ? Math.round((resolvedWithoutEscalation / answered) * 100) : 0;\n\n// Build insights array for ai_insights table\nconst insights = [\n {\n tenant_id: tenant.id,\n category: 'trend',\n severity: 'info',\n title: 'Monthly Call Volume',\n message: `${totalCalls} total calls handled in ${monthLabel}, averaging ${avgCallsPerDay} calls per day.`\n },\n {\n tenant_id: tenant.id,\n category: 'trend',\n severity: 'info',\n title: 'Busiest Day',\n message: `${busiestDay.date} was the busiest day with ${busiestDay.calls} calls.`\n },\n {\n tenant_id: tenant.id,\n category: 'trend',\n severity: 'info',\n title: 'Answer Rate',\n message: `${answerRate}% answer rate with ${missed} missed calls and ${voicemail} voicemails.`\n },\n {\n tenant_id: tenant.id,\n category: 'recommendation',\n severity: 'info',\n title: 'Time & Cost Savings',\n message: `TitleFlow AI saved an estimated ${hoursSaved} staff hours ($${laborCostSaved.toLocaleString()} in labor costs) at a 1.5x efficiency multiplier.`\n },\n {\n tenant_id: tenant.id,\n category: 'trend',\n severity: 'info',\n title: 'Resolution Rate',\n message: `${resolutionRate}% of answered calls resolved without escalation.`\n }\n];\n\nif (escalationRate > 15) {\n insights.push({\n tenant_id: tenant.id,\n category: 'recommendation',\n severity: 'info',\n title: 'High Escalation Rate',\n message: `Escalation rate was ${escalationRate}%. Consider reviewing AI call scripts to reduce escalations.`\n });\n}\n\nreturn [\n {\n json: {\n tenant_id: tenant.id,\n company_name: tenant.company_name || 'Customer',\n owner_email: tenant.owner_email || tenant.contact_email || '',\n plan: tenant.plan || 'Standard',\n month_label: monthLabel,\n total_calls: totalCalls,\n total_minutes: totalMinutes,\n total_hours: totalHours,\n answered: answered,\n missed: missed,\n voicemail: voicemail,\n escalations: escalations,\n avg_calls_per_day: avgCallsPerDay,\n answer_rate: answerRate,\n miss_rate: missRate,\n escalation_rate: escalationRate,\n resolution_rate: resolutionRate,\n busiest_day: busiestDay.date,\n busiest_day_calls: busiestDay.calls,\n hours_saved: hoursSaved,\n labor_cost_saved: laborCostSaved,\n insights: insights\n }\n }\n];" }, "id": "wf008-node-compute-insights", "name": "Compute Insights", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1250, 300 ] }, { "parameters": { "jsCode": "// Insert each insight as a separate item for the Supabase upsert\nconst data = $input.all()[0].json;\nconst insights = data.insights || [];\n\nreturn insights.map(insight => ({\n json: {\n tenant_id: insight.tenant_id,\n category: insight.category,\n severity: insight.severity,\n title: insight.title,\n message: insight.message,\n month: data.month_label,\n created_at: new Date().toISOString(),\n // Pass through report data for downstream nodes\n _report: {\n tenant_id: data.tenant_id,\n company_name: data.company_name,\n owner_email: data.owner_email,\n plan: data.plan,\n month_label: data.month_label,\n total_calls: data.total_calls,\n total_minutes: data.total_minutes,\n total_hours: data.total_hours,\n answered: data.answered,\n missed: data.missed,\n voicemail: data.voicemail,\n escalations: data.escalations,\n avg_calls_per_day: data.avg_calls_per_day,\n answer_rate: data.answer_rate,\n miss_rate: data.miss_rate,\n escalation_rate: data.escalation_rate,\n resolution_rate: data.resolution_rate,\n busiest_day: data.busiest_day,\n busiest_day_calls: data.busiest_day_calls,\n hours_saved: data.hours_saved,\n labor_cost_saved: data.labor_cost_saved\n }\n }\n}));" }, "id": "wf008-node-split-insights", "name": "Prepare Insight Records", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1500, 300 ] }, { "parameters": { "operation": "create", "tableId": "ai_insights", "dataToSend": "defineBelow", "fieldsUi": { "fieldValues": [ { "fieldName": "tenant_id", "fieldValue": "={{ $json.tenant_id }}" }, { "fieldName": "category", "fieldValue": "={{ $json.category }}" }, { "fieldName": "severity", "fieldValue": "={{ $json.severity }}" }, { "fieldName": "title", "fieldValue": "={{ $json.title }}" }, { "fieldName": "message", "fieldValue": "={{ $json.message }}" } ] } }, "id": "wf008-node-insert-insights", "name": "Insert AI Insights", "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 1750, 300 ], "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "jsCode": "// Build HTML monthly report email from the report data\nconst items = $input.all();\n// Get the report data from the last item (all items carry the same _report)\nconst report = items[items.length - 1].json._report || items[0].json._report || {};\n\nconst r = report;\nconst monthLabel = r.month_label || 'Last Month';\n\nconst subject = `Your TitleFlow AI Monthly Report - ${monthLabel}`;\n\nconst htmlBody = `\n
\n \n
\n

TitleFlow AI

\n

Monthly Performance Report

\n

${monthLabel}

\n
\n \n \n
\n

Hi ${r.company_name}, here is your monthly performance summary:

\n \n
\n
\n
${r.total_calls}
\n
Total Calls
\n
\n
\n
${r.total_hours}h
\n
Total Hours
\n
\n
\n
${r.answer_rate}%
\n
Answer Rate
\n
\n
\n \n \n
\n

Call Breakdown

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Answered${r.answered}
Missed${r.missed}
Voicemail${r.voicemail}
Escalations${r.escalations}
Avg Calls/Day${r.avg_calls_per_day}
Resolution Rate${r.resolution_rate}%
\n
\n \n \n
\n

Key Insights

\n

● Busiest day: ${r.busiest_day} with ${r.busiest_day_calls} calls

\n

● ${r.resolution_rate}% of calls resolved without human escalation

\n

● ${r.escalation_rate}% escalation rate

\n
\n \n \n
\n

Estimated Savings This Month

\n
$${r.labor_cost_saved.toLocaleString()}
\n

${r.hours_saved} staff hours saved at 1.5x efficiency × $25/hr

\n
\n \n \n
\n \n \n
\n

TitleFlow AI AI — Automating title industry communications

\n

You are receiving this because you are subscribed to the ${r.plan} plan.

\n
\n
`;\n\nreturn [\n {\n json: {\n to: r.owner_email,\n subject: subject,\n html: htmlBody,\n tenant_id: r.tenant_id,\n company_name: r.company_name,\n month_label: monthLabel\n }\n }\n];" }, "id": "wf008-node-build-email", "name": "Build HTML Report Email", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 2000, 300 ] }, { "parameters": { "fromEmail": "user@example.com", "toEmail": "={{ $json.to }}", "subject": "={{ $json.subject }}", "emailType": "html", "html": "={{ $json.html }}" }, "id": "wf008-node-send-email", "name": "Send Monthly Report", "type": "n8n-nodes-base.emailSend", "typeVersion": 2.1, "position": [ 2250, 300 ], "credentials": { "smtp": { "name": "" } } }, { "parameters": { "operation": "create", "tableId": "notifications", "dataToSend": "defineBelow", "fieldsUi": { "fieldValues": [ { "fieldName": "tenant_id", "fieldValue": "={{ $json.tenant_id }}" }, { "fieldName": "type", "fieldValue": "monthly_report" }, { "fieldName": "title", "fieldValue": "={{ 'Monthly Report - ' + $json.month_label }}" }, { "fieldName": "message", "fieldValue": "={{ 'Monthly performance report for ' + $json.month_label + ' sent to ' + $json.company_name }}" }, { "fieldName": "channel", "fieldValue": "email" }, { "fieldName": "sent_at", "fieldValue": "={{ new Date().toISOString() }}" } ] } }, "id": "wf008-node-log-notification", "name": "Log Report Notification", "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 2500, 300 ], "credentials": { "supabaseApi": { "name": "" } } } ], "connections": { "1st of Month 9AM ET": { "main": [ [ { "node": "Get Active Tenants", "type": "main", "index": 0 } ] ] }, "Get Active Tenants": { "main": [ [ { "node": "Loop Over Tenants", "type": "main", "index": 0 } ] ] }, "Loop Over Tenants": { "main": [ null, [ { "node": "Get Monthly Usage", "type": "main", "index": 0 } ] ] }, "Get Monthly Usage": { "main": [ [ { "node": "Get Daily Trends", "type": "main", "index": 0 } ] ] }, "Get Daily Trends": { "main": [ [ { "node": "Compute Insights", "type": "main", "index": 0 } ] ] }, "Compute Insights": { "main": [ [ { "node": "Prepare Insight Records", "type": "main", "index": 0 } ] ] }, "Prepare Insight Records": { "main": [ [ { "node": "Insert AI Insights", "type": "main", "index": 0 } ] ] }, "Insert AI Insights": { "main": [ [ { "node": "Build HTML Report Email", "type": "main", "index": 0 } ] ] }, "Build HTML Report Email": { "main": [ [ { "node": "Send Monthly Report", "type": "main", "index": 0 } ] ] }, "Send Monthly Report": { "main": [ [ { "node": "Log Report Notification", "type": "main", "index": 0 } ] ] }, "Log Report Notification": { "main": [ [ { "node": "Loop Over Tenants", "type": "main", "index": 0 } ] ] } }, "settings": { "executionOrder": "v1", "saveManualExecutions": true, "callerPolicy": "workflowsFromSameOwner", "timezone": "America/New_York" }, "meta": { "templateCredsSetupCompleted": false }, "active": false, "tags": [ { "name": "reporting" }, { "name": "monthly" }, { "name": "insights" } ] }