{ "id": "v41nqKecTo3htFFl", "meta": { "templateCredsSetupCompleted": true }, "name": "Generate monthly BigQuery KPI PDF reports with Claude, Google Docs and Outlook", "tags": [], "nodes": [ { "id": "d440d2d7-9347-4ff8-a92d-bcdc04a57c1d", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [ 6704, 224 ], "parameters": { "width": 432, "height": 864, "content": "##Generate monthly BigQuery KPI PDF reports with Claude, Google Docs and Outlook\n\n### How it works\n\nThis workflow runs monthly to generate a KPI report for the previous full month. It queries BigQuery for revenue, category, weekly trend, and customer metrics, consolidates the results, and uses Claude to create a narrative summary. It copies a Google Docs template, fills it with KPI data and the AI narrative, exports the document as a PDF, then archives it to OneDrive, emails it through Outlook, and posts a Teams summary.\n\n### Setup steps\n\n- Configure the monthly schedule trigger for the desired reporting time and timezone.\n- Connect Google BigQuery credentials and update the SQL queries, dataset, table names, and date filters used by the KPI query nodes.\n- Configure Anthropic credentials for the Claude chat model used by the LLM chain.\n- Connect Google Drive and Google Docs credentials, and set the report template file ID plus any destination folder IDs needed for copying and exporting.\n- Connect Microsoft OneDrive, Outlook, and Teams credentials, then configure archive locations, email recipients, and Teams channel or chat targets.\n\n### Customization\n\nAdjust the BigQuery queries, template placeholders, Claude prompt, email recipients, and Teams card content to match the KPIs and audience for the report." }, "typeVersion": 1 }, { "id": "3449e3d8-f812-4316-ae48-78565793309b", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [ 7200, 448 ], "parameters": { "color": 7, "width": 576, "height": 384, "content": "## Start reporting period\n\nTriggers the workflow on the monthly schedule and calculates the previous full month as the reporting window used by all downstream queries." }, "typeVersion": 1 }, { "id": "b1c755d5-2a0c-4e6d-8b0d-4fbbc3eb8e99", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [ 7824, 32 ], "parameters": { "color": 7, "width": 416, "height": 304, "content": "## Fetch revenue KPIs\n\nRuns the revenue KPI query in BigQuery and tags those rows with their source before merging." }, "typeVersion": 1 }, { "id": "64eecea3-b5df-4609-9ef1-04e80145b790", "name": "Sticky Note3", "type": "n8n-nodes-base.stickyNote", "position": [ 7824, 368 ], "parameters": { "color": 7, "width": 416, "height": 320, "content": "## Fetch category rankings\n\nQueries top product or business categories from BigQuery and labels the returned category results for later aggregation." }, "typeVersion": 1 }, { "id": "1a879d20-27c4-4b6a-a60c-a5fdfb7de55c", "name": "Sticky Note4", "type": "n8n-nodes-base.stickyNote", "position": [ 7824, 720 ], "parameters": { "color": 7, "width": 416, "height": 320, "content": "## Fetch weekly trend\n\nRetrieves week-by-week trend data from BigQuery and tags the weekly results with their source query identifier." }, "typeVersion": 1 }, { "id": "58ed5879-7e27-465a-9c61-9a4578dd0393", "name": "Sticky Note5", "type": "n8n-nodes-base.stickyNote", "position": [ 7824, 1072 ], "parameters": { "color": 7, "width": 416, "height": 320, "content": "## Fetch top customers\n\nQueries top customer metrics from BigQuery and annotates the customer rows so they can be separated after the merge." }, "typeVersion": 1 }, { "id": "7c752f98-2c2b-4e64-a8f0-d7f39f120a00", "name": "Sticky Note6", "type": "n8n-nodes-base.stickyNote", "position": [ 8320, 432 ], "parameters": { "color": 7, "width": 656, "height": 400, "content": "## Consolidate report data\n\nCombines all tagged BigQuery outputs, aggregates them into a structured report payload, and explicitly carries that payload forward for both narrative and document creation branches." }, "typeVersion": 1 }, { "id": "1ab5cc2e-23f5-410e-bee4-d154d770d26a", "name": "Sticky Note7", "type": "n8n-nodes-base.stickyNote", "position": [ 9040, 64 ], "parameters": { "color": 7, "width": 608, "height": 576, "content": "## Generate Claude narrative\n\nSends the report payload to Claude through the LLM chain, then parses and merges the generated narrative back into the report data structure.\n\n" }, "typeVersion": 1 }, { "id": "21eef0ce-2e07-43c9-9450-81776ba3111c", "name": "Sticky Note8", "type": "n8n-nodes-base.stickyNote", "position": [ 9040, 688 ], "parameters": { "color": 7, "width": 608, "height": 352, "content": "## Copy report template\n\nCreates a new Google Drive copy of the report template in the lower document-preparation branch.\n" }, "typeVersion": 1 }, { "id": "43d21119-9042-4890-b589-46ab9423bd0d", "name": "Sticky Note9", "type": "n8n-nodes-base.stickyNote", "position": [ 9696, 432 ], "parameters": { "color": 7, "width": 416, "height": 384, "content": "## Prepare template replacements\n\nWaits for both the Claude-enhanced report data and copied document ID, then builds the Google Docs replacement requests for template placeholders." }, "typeVersion": 1 }, { "id": "71b041f9-4b5c-49ee-8070-3348b1859320", "name": "Sticky Note10", "type": "n8n-nodes-base.stickyNote", "position": [ 10144, 432 ], "parameters": { "color": 7, "width": 448, "height": 384, "content": "## Fill and export PDF\n\nApplies the replacement requests to the copied Google Doc and exports the completed report as a PDF through Google Drive.\n\n" }, "typeVersion": 1 }, { "id": "21816bb9-9626-48cc-b4b8-b6a0fdf50942", "name": "Sticky Note11", "type": "n8n-nodes-base.stickyNote", "position": [ 10640, 368 ], "parameters": { "color": 7, "width": 608, "height": 512, "content": "## Distribute finished report\n\nArchives the generated PDF to OneDrive, emails it through Outlook, and posts a summary notification to Microsoft Teams.\n\n" }, "typeVersion": 1 }, { "id": "af873869-33b2-4bad-abe3-2c6b1b5053fb", "name": "When First of Month at 07:00", "type": "n8n-nodes-base.scheduleTrigger", "notes": "Runs on the 1st of every month at 07:00 UTC. Change expression to weekly (0 7 * * 1) or daily (0 7 * * *) as needed.", "position": [ 7312, 640 ], "parameters": { "rule": { "interval": [ { "field": "cronExpression", "expression": "0 7 1 * *" } ] } }, "typeVersion": 1.2 }, { "id": "e54f406c-cc83-4f74-8855-e75e8b8b5011", "name": "Calculate Previous Month", "type": "n8n-nodes-base.code", "notes": "Calculates start/end dates for the previous full calendar month and generates a collision-safe report ID using crypto.randomUUID().", "position": [ 7536, 640 ], "parameters": { "jsCode": "const now = new Date();\nconst firstOfLastMonth = new Date(now.getFullYear(), now.getMonth() - 1, 1);\nconst lastOfLastMonth = new Date(now.getFullYear(), now.getMonth(), 0);\nconst fmt = (d) => d.toISOString().split('T')[0];\nconst startDate = fmt(firstOfLastMonth);\nconst endDate = fmt(lastOfLastMonth);\nconst periodSlug = startDate.replace(/-/g, '');\nconst reportId = `RPT-${periodSlug}-${crypto.randomUUID().split('-')[0].toUpperCase()}`;\nreturn [{ json: {\n label: firstOfLastMonth.toLocaleString('en-GB', { month: 'long', year: 'numeric' }),\n startDate,\n endDate,\n reportId,\n generatedAt: now.toISOString()\n} }];" }, "typeVersion": 2 }, { "id": "e69b456f-8ba7-463b-8f1a-4b01f81daf5e", "name": "Fetch Revenue KPIs", "type": "n8n-nodes-base.googleBigQuery", "notes": "Returns one aggregated row. Credential: Google BigQuery. Env vars: GCP_PROJECT_ID, BQ_DATASET. Update table name if not 'orders'.", "position": [ 7872, 160 ], "parameters": { "options": { "location": "EU" }, "sqlQuery": "SELECT\n COUNT(*) AS total_orders,\n SUM(order_total) AS total_revenue,\n AVG(order_total) AS avg_order_value,\n COUNT(DISTINCT customer_id) AS unique_customers,\n COUNTIF(is_new_customer = TRUE) AS new_customers,\n COUNTIF(is_new_customer = FALSE) AS returning_customers\nFROM `{{ $env.BQ_DATASET }}.orders`\nWHERE DATE(created_at) BETWEEN @start_date AND @end_date", "projectId": "={{ $env.GCP_PROJECT_ID }}" }, "credentials": { "googleBigQueryOAuth2Api": { "name": "" } }, "typeVersion": 2 }, { "id": "23e4cade-1863-4d59-94a2-03beeb73ce42", "name": "Fetch Top Sales Categories", "type": "n8n-nodes-base.googleBigQuery", "notes": "Returns up to 10 rows, one per category. Credential: Google BigQuery.", "position": [ 7872, 528 ], "parameters": { "options": { "location": "EU" }, "sqlQuery": "SELECT\n product_category,\n COUNT(*) AS orders,\n SUM(order_total) AS revenue,\n ROUND(100.0 * SUM(order_total) / SUM(SUM(order_total)) OVER (), 1) AS revenue_pct\nFROM `{{ $env.BQ_DATASET }}.orders`\nWHERE DATE(created_at) BETWEEN @start_date AND @end_date\nGROUP BY product_category\nORDER BY revenue DESC\nLIMIT 10", "projectId": "={{ $env.GCP_PROJECT_ID }}" }, "typeVersion": 2 }, { "id": "8ed3cf3a-be2d-44c1-b85c-b027c6f05b09", "name": "Fetch Weekly Sales Trend", "type": "n8n-nodes-base.googleBigQuery", "notes": "Returns one row per week in the reporting period. Credential: Google BigQuery.", "position": [ 7872, 880 ], "parameters": { "options": { "location": "EU" }, "sqlQuery": "SELECT\n DATE_TRUNC(DATE(created_at), WEEK) AS week_start,\n COUNT(*) AS orders,\n SUM(order_total) AS weekly_revenue\nFROM `{{ $env.BQ_DATASET }}.orders`\nWHERE DATE(created_at) BETWEEN @start_date AND @end_date\nGROUP BY week_start\nORDER BY week_start ASC", "projectId": "={{ $env.GCP_PROJECT_ID }}" }, "credentials": { "googleBigQueryOAuth2Api": { "name": "" } }, "typeVersion": 2 }, { "id": "bce15ffd-f877-4f9e-aab0-cf1896cd10a7", "name": "Fetch Top Customers", "type": "n8n-nodes-base.googleBigQuery", "notes": "Returns up to 10 rows, one per customer. Credential: Google BigQuery.", "position": [ 7872, 1232 ], "parameters": { "options": { "location": "EU" }, "sqlQuery": "SELECT\n customer_name,\n COUNT(*) AS orders,\n SUM(order_total) AS total_spent\nFROM `{{ $env.BQ_DATASET }}.orders`\nWHERE DATE(created_at) BETWEEN @start_date AND @end_date\nGROUP BY customer_name\nORDER BY total_spent DESC\nLIMIT 10", "projectId": "={{ $env.GCP_PROJECT_ID }}" }, "typeVersion": 2 }, { "id": "9a848455-3aee-475e-96fb-2de6d2f33b35", "name": "Label Revenue Data", "type": "n8n-nodes-base.code", "position": [ 8096, 160 ], "parameters": { "jsCode": "return $input.all().map(item => ({ json: { ...item.json, _sourceQuery: 'revenue' } }));" }, "typeVersion": 2 }, { "id": "70c8feb8-bdd9-4582-b067-e8440a4ee6a8", "name": "Label Category Data", "type": "n8n-nodes-base.code", "position": [ 8096, 528 ], "parameters": { "jsCode": "return $input.all().map(item => ({ json: { ...item.json, _sourceQuery: 'categories' } }));" }, "typeVersion": 2 }, { "id": "55eeee38-576a-4d03-8208-9de2d81320c8", "name": "Label Weekly Data", "type": "n8n-nodes-base.code", "position": [ 8096, 880 ], "parameters": { "jsCode": "return $input.all().map(item => ({ json: { ...item.json, _sourceQuery: 'weekly' } }));" }, "typeVersion": 2 }, { "id": "3fc6878b-dccd-402a-8068-ea3fc1075d53", "name": "Label Customer Data", "type": "n8n-nodes-base.code", "position": [ 8096, 1232 ], "parameters": { "jsCode": "return $input.all().map(item => ({ json: { ...item.json, _sourceQuery: 'customers' } }));" }, "typeVersion": 2 }, { "id": "c962ffc4-9024-4447-86fb-9d65fa780c58", "name": "Merge BigQuery Results", "type": "n8n-nodes-base.merge", "notes": "mode=append preserves ALL rows from all 4 branches. waitForAll (the default) would truncate multi-row results to 1 row per branch, emptying topCategories, weeklyTrend, and topCustomers arrays.", "position": [ 8384, 592 ], "parameters": { "numberInputs": 4 }, "typeVersion": 3 }, { "id": "326deef6-f208-43d8-ba78-1a2ed5ebe942", "name": "Consolidate BigQuery Data", "type": "n8n-nodes-base.code", "position": [ 8608, 624 ], "parameters": { "jsCode": "const period = $('Calculate Previous Month').first().json;\nconst allItems = $input.all().map(i => i.json);\nconst revenueRow = allItems.find(i => i._sourceQuery === 'revenue') || {};\nconst categoryRows = allItems.filter(i => i._sourceQuery === 'categories');\nconst weeklyRows = allItems.filter(i => i._sourceQuery === 'weekly');\nconst customerRows = allItems.filter(i => i._sourceQuery === 'customers');\nconst eur = (v) => `EUR ${Number(v || 0).toLocaleString('en-FI', { minimumFractionDigits: 2, maximumFractionDigits: 2 })}`;\nconst payload = {\n report: {\n id: period.reportId,\n period: period.label,\n startDate: period.startDate,\n endDate: period.endDate,\n generatedAt: period.generatedAt,\n generatedBy: 'AutomiQ BigQuery Report Agent'\n },\n company: {\n name: 'AutomiQ / KW Catering & Consulting Oy',\n website: 'automiq.fi',\n preparedBy: 'Mychel Garzon'\n },\n kpis: {\n totalOrders: Number(revenueRow.total_orders || 0),\n totalRevenue: eur(revenueRow.total_revenue),\n totalRevenueRaw: Number(revenueRow.total_revenue || 0),\n avgOrderValue: eur(revenueRow.avg_order_value),\n uniqueCustomers: Number(revenueRow.unique_customers || 0),\n newCustomers: Number(revenueRow.new_customers || 0),\n returningCustomers: Number(revenueRow.returning_customers || 0),\n newCustomerPct: revenueRow.unique_customers > 0\n ? Math.round((revenueRow.new_customers / revenueRow.unique_customers) * 100) + '%'\n : '0%'\n },\n topCategories: categoryRows.map(r => ({\n category: r.product_category,\n orders: Number(r.orders),\n revenue: eur(r.revenue),\n revenuePct: r.revenue_pct + '%'\n })),\n weeklyTrend: weeklyRows.map(r => ({\n weekStart: r.week_start,\n orders: Number(r.orders),\n revenue: eur(r.weekly_revenue)\n })),\n topCustomers: customerRows.map(r => ({\n name: r.customer_name,\n orders: Number(r.orders),\n totalSpent: eur(r.total_spent)\n }))\n};\nreturn [{ json: payload }];" }, "typeVersion": 2 }, { "id": "a0892539-ffad-4ec0-b4fb-5c89efa2bd0a", "name": "Transfer Report Data", "type": "n8n-nodes-base.code", "notes": "Wraps the full report payload under a 'reportData' key so downstream nodes can reference it via $json.reportData without cross-branch node lookups.", "position": [ 8832, 624 ], "parameters": { "jsCode": "const reportData = $input.first().json;\nreturn [{ json: { reportData } }];" }, "typeVersion": 2 }, { "id": "4887c977-e14b-463d-b6fc-55e22c81f10c", "name": "Create AI Narrative with Claude", "type": "@n8n/n8n-nodes-langchain.chainLlm", "notes": "Basic LLM Chain. The Claude Chat Model sub-node must be connected to this node's ai_languageModel input (bottom connector on canvas). Output: { text: '' } parsed by Integrate Narrative with Data.", "position": [ 9088, 272 ], "parameters": {}, "typeVersion": 1.4 }, { "id": "c2059374-e4c8-4772-8d13-c1fc8b1f35fa", "name": "Integrate Narrative with Data", "type": "n8n-nodes-base.code", "notes": "Parses Claude's JSON response and merges the narrative into the report payload. Falls back to KPI-derived text if Claude returns invalid JSON or is unavailable.", "position": [ 9440, 272 ], "parameters": { "jsCode": "const chainOutput = $input.first().json;\nconst reportData = $('Transfer Report Data').first().json.reportData;\nconst rawText = chainOutput.text || chainOutput.output || chainOutput.content?.[0]?.text || '';\nlet narrative;\nif (rawText) {\n try {\n const cleaned = rawText.replace(/```json|```/g, '').trim();\n narrative = JSON.parse(cleaned);\n } catch(e) {\n narrative = null;\n }\n}\nif (!narrative) {\n narrative = {\n executiveSummary: `KPI report for ${reportData.report.period}. Total revenue: ${reportData.kpis.totalRevenue}. Total orders: ${reportData.kpis.totalOrders}. AI narrative unavailable this cycle.`,\n revenueAnalysis: `Revenue: ${reportData.kpis.totalRevenue}. Avg order value: ${reportData.kpis.avgOrderValue}.`,\n categoryInsights: 'See category breakdown table.',\n customerInsights: `${reportData.kpis.uniqueCustomers} unique customers. New: ${reportData.kpis.newCustomerPct}.`,\n recommendation: 'AI narrative could not be generated. Review KPI data manually.'\n };\n}\nreportData.narrative = narrative;\nreturn [{ json: reportData }];" }, "typeVersion": 2 }, { "id": "9d6b760c-ac53-4f3e-8f61-052210fc5138", "name": "Claude Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic", "notes": "Anthropic Chat Model sub-node. Credential: Anthropic API (native n8n credential \u2014 paste your API key in the credential form). Connect this node's output to the ai_languageModel input (bottom socket) of Create AI Narrative with Claude.", "position": [ 9088, 496 ], "parameters": { "model": "claude-sonnet-4-6", "options": { "temperature": 0.3 } }, "typeVersion": 1.2 }, { "id": "c2d77142-57aa-4a6f-930f-feb8a6d541b7", "name": "Duplicate Report Template", "type": "n8n-nodes-base.googleDrive", "notes": "Copies the master Google Docs template to your reports folder. The original is never modified. Credential: Google Drive OAuth2. Env vars: GDOCS_TEMPLATE_FILE_ID (Drive file ID from the Doc URL), GDRIVE_REPORTS_FOLDER_ID (destination folder ID).", "position": [ 9264, 864 ], "parameters": { "name": "=KPI_Report_{{ $('Integrate Narrative with Data').first().json.report.period.replace(/ /g, '_') }}_{{ $('Integrate Narrative with Data').first().json.report.id }}", "fileId": "={{ $env.GDOCS_TEMPLATE_FILE_ID }}", "options": {}, "operation": "copy" }, "typeVersion": 3 }, { "id": "933b3767-6e97-413d-99dc-a9287966fef5", "name": "Combine Narrative and Doc ID", "type": "n8n-nodes-base.merge", "notes": "Waits for both concurrent branches: input[0] = narrative-enriched report payload from Integrate Narrative with Data, input[1] = Drive copy response containing the new Doc ID from Duplicate Report Template. Ensures Construct Replacement Requests fires exactly once with both data sets available.", "position": [ 9744, 624 ], "parameters": { "mode": "waitForAll" }, "typeVersion": 3 }, { "id": "69e9d44b-3aaf-4122-97e2-29cf9b09ce69", "name": "Construct Replacement Requests", "type": "n8n-nodes-base.code", "notes": "Builds the Docs API batchUpdate payload. Each {{PLACEHOLDER}} in your template Doc becomes a replaceAllText request. Tables render as monospace plain text. copiedDocId is passed forward for the Populate and Export nodes.", "position": [ 9968, 624 ], "parameters": { "jsCode": "const allItems = $input.all();\nconst reportData = allItems.find(i => i.json.report)?.json;\nconst copiedDocId = allItems.find(i => i.json.id && !i.json.report)?.json.id;\nif (!reportData) throw new Error('Construct Replacement Requests: reportData not found in merged input');\nif (!copiedDocId) throw new Error('Construct Replacement Requests: copiedDocId not found in merged input');\n\nconst tableText = (headers, rows, cols) => {\n const pad = (s, n) => String(s).slice(0, n).padEnd(n);\n const widths = cols.map((c, i) => Math.max(headers[i].length, ...rows.map(r => String(r[c] || '').length)));\n const hr = widths.map(w => '-'.repeat(w + 2)).join('+');\n const row = (cells) => cells.map((c, i) => ' ' + pad(c, widths[i]) + ' ').join('|');\n return [row(headers), hr, ...rows.map(r => row(cols.map(c => r[c] || '')))].join('\\n');\n};\n\nconst categoriesTable = tableText(\n ['Category', 'Orders', 'Revenue', 'Share'],\n reportData.topCategories,\n ['category', 'orders', 'revenue', 'revenuePct']\n);\nconst weeklyTable = tableText(\n ['Week Starting', 'Orders', 'Revenue'],\n reportData.weeklyTrend,\n ['weekStart', 'orders', 'revenue']\n);\nconst customersTable = tableText(\n ['Customer', 'Orders', 'Total Spent'],\n reportData.topCustomers,\n ['name', 'orders', 'totalSpent']\n);\n\nconst replacements = [\n ['{{REPORT_PERIOD}}', reportData.report.period],\n ['{{REPORT_ID}}', reportData.report.id],\n ['{{GENERATED_AT}}', reportData.report.generatedAt],\n ['{{KPI_TOTAL_REVENUE}}', reportData.kpis.totalRevenue],\n ['{{KPI_TOTAL_ORDERS}}', String(reportData.kpis.totalOrders)],\n ['{{KPI_AVG_ORDER}}', reportData.kpis.avgOrderValue],\n ['{{KPI_UNIQUE_CUSTOMERS}}', String(reportData.kpis.uniqueCustomers)],\n ['{{KPI_NEW_CUSTOMERS}}', String(reportData.kpis.newCustomers)],\n ['{{KPI_NEW_PCT}}', reportData.kpis.newCustomerPct],\n ['{{NARRATIVE_SUMMARY}}', reportData.narrative.executiveSummary],\n ['{{NARRATIVE_REVENUE}}', reportData.narrative.revenueAnalysis],\n ['{{NARRATIVE_CATEGORIES}}', reportData.narrative.categoryInsights],\n ['{{NARRATIVE_CUSTOMERS}}', reportData.narrative.customerInsights],\n ['{{NARRATIVE_RECOMMENDATION}}',reportData.narrative.recommendation],\n ['{{TOP_CATEGORIES_TABLE}}', categoriesTable],\n ['{{WEEKLY_TREND_TABLE}}', weeklyTable],\n ['{{TOP_CUSTOMERS_TABLE}}', customersTable]\n];\n\nconst requests = replacements.map(([placeholder, newText]) => ({\n replaceAllText: {\n containsText: { text: placeholder, matchCase: true },\n replaceText: newText || ''\n }\n}));\n\nreturn [{ json: { copiedDocId, requests } }];" }, "typeVersion": 2 }, { "id": "53f1c68f-a798-48e2-96ca-badb7dd354a9", "name": "Populate Template Fields", "type": "n8n-nodes-base.googleDocs", "notes": "Calls Google Docs batchUpdate to replace all {{PLACEHOLDER}} strings in the copied Doc. Requires typeVersion 2 for the requestsJson parameter. Credential: Google Docs OAuth2 (scope: https://www.googleapis.com/auth/documents).", "position": [ 10192, 624 ], "parameters": { "actionsUi": { "actionFields": [ { "action": "insert" } ] }, "operation": "update" }, "credentials": { "googleDocsOAuth2Api": { "name": "" } }, "typeVersion": 2 }, { "id": "eb82940f-2ffc-4a72-88b0-3ce03094929a", "name": "Export Document to PDF", "type": "n8n-nodes-base.googleDrive", "notes": "Exports the populated Google Doc as PDF using Drive's native file conversion. Binary stored as 'report_pdf' \u2014 the same property name expected by Save Report to OneDrive and Send Report via Outlook. Credential: Google Drive OAuth2.", "position": [ 10416, 624 ], "parameters": { "fileId": "={{ $('Construct Replacement Requests').first().json.copiedDocId }}", "options": { "googleFileConversion": { "conversion": { "docsToFormat": "application/pdf" } } }, "operation": "download" }, "typeVersion": 3 }, { "id": "daf0224e-e93c-4acb-b00a-6e1fcad17bad", "name": "Save Report to OneDrive", "type": "n8n-nodes-base.microsoftOneDrive", "notes": "Archives the generated PDF to OneDrive. Credential: Microsoft OneDrive OAuth2. Env var: ONEDRIVE_REPORTS_FOLDER_ID (OneDrive folder GUID).", "position": [ 10864, 528 ], "parameters": {}, "typeVersion": 1 }, { "id": "9616bf10-b5cc-4de8-bcd8-54d169f1aa96", "name": "Send Report via Outlook", "type": "n8n-nodes-base.microsoftOutlook", "notes": "Emails the PDF report to all recipients. Credential: Microsoft Outlook OAuth2. Env var: REPORT_RECIPIENTS (comma-separated email addresses).", "position": [ 10752, 720 ], "parameters": { "subject": "=Monthly KPI Report \u2013 {{ $('Integrate Narrative with Data').first().json.report.period }} | {{ $('Integrate Narrative with Data').first().json.report.id }}", "bodyContent": "=

Monthly KPI Report \u2013 {{ $('Integrate Narrative with Data').first().json.report.period }}

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{{ $('Integrate Narrative with Data').first().json.narrative.executiveSummary }}

\n

Please find the full PDF report attached.

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Key Highlights

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    \n
  • Total Revenue: {{ $('Integrate Narrative with Data').first().json.kpis.totalRevenue }}
    • \n
  • Total Orders: {{ $('Integrate Narrative with Data').first().json.kpis.totalOrders }}
    • \n
  • Avg Order Value: {{ $('Integrate Narrative with Data').first().json.kpis.avgOrderValue }}
    • \n
  • Unique Customers: {{ $('Integrate Narrative with Data').first().json.kpis.uniqueCustomers }} ({{ $('Integrate Narrative with Data').first().json.kpis.newCustomerPct }} new)
    • \n
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AutomiQ / KW Catering & Consulting Oy — automiq.fi

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