{"workflow":{"id":14323,"name":"Send a daily paid acquisition and website intelligence report with Databox, GPT-4o and Gmail","views":58,"recentViews":2,"totalViews":58,"createdAt":"2026-03-25T15:38:55.567Z","description":"Your paid ads and website analytics live in separate tools. This workflow bridges both via Databox MCP, runs three specialized AI agents in sequence, and emails a daily intelligence report with a correlation layer that surfaces insights neither dataset could show alone.\n\n## Who's it for\n\n- **Performance marketers** who want to understand how ads influence website quality\n- **Growth teams** looking for daily cross-channel signals without building custom dashboards\n- **Marketing managers** who need one morning briefing covering paid spend and website behavior\n\n## How it works\n\n1. Schedule Trigger fires every day at 8 AM\n2. Agent 1 fetches website performance from Databox: sessions, bounce rate, goal completions, conversion rate\n3. Agent 2 fetches paid channel data from Databox: spend, CPC, CTR, ROAS per platform\n4. Agent 3 synthesizes both outputs - ranks channel efficiency, estimates cost per quality visit, and writes 3 actionable recommendations\n5. A styled HTML email report is delivered to your inbox\n\n## Requirements\n\n- **[Databox account](https://databox.com/?ref=n8n)** with website analytics and at least one paid ads platform connected (free plan works)\n- OpenAI API key (or Anthropic)\n- Gmail account\n\n## How to set up\n\n1. Click each **Databox MCP Tool** node - set Authentication to OAuth2 and authorize\n2. Add your **OpenAI API key** to each of the three Chat Model nodes\n3. Connect **Gmail** and set the recipient address in the Send Email node\n4. Activate - your first report arrives tomorrow at 8 AM","workflow":{"id":"DEmOnEbgsR5bEoAH","meta":{"instanceId":"5e7432fe8afd0144f7397a6ce277b55cde7b2b8cd3575a25b13c8eb90ebe91ea"},"name":"Daily paid acquisition intelligence report","tags":[{"id":"ZLNp4q7bLInAPzlr","name":"Databox MCP","createdAt":"2026-02-12T05:49:19.149Z","updatedAt":"2026-02-12T05:49:19.149Z"},{"id":"OITWk9JNRp1srhj6","name":"Paid Ads","createdAt":"2026-02-26T16:50:04.993Z","updatedAt":"2026-02-26T16:50:04.993Z"},{"id":"fjJWe0P5GkqnbIXj","name":"Automation","createdAt":"2026-02-12T05:49:19.177Z","updatedAt":"2026-02-12T05:49:19.177Z"}],"nodes":[{"id":"51b9a6e9-5a6f-4815-9c7a-43fb276e0bee","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[16,16],"parameters":{"color":7,"width":1680,"height":400,"content":"## Daily Paid Acquisition Intelligence Report via Databox MCP\n\nGet a daily intelligence briefing on your paid acquisition performance. Three specialized AI agents run in sequence: Agent 1 analyzes website behavior, Agent 2 analyzes paid channel performance across all connected platforms, and Agent 3 runs cross-channel correlation analysis - surfacing insights like cost per quality visit, channel efficiency rankings, and concrete budget reallocation recommendations.\n\n### How it works\n`Schedule Trigger` - `Agent 1: Website Analysis (Databox MCP)` - `Agent 2: Paid Acquisition Analysis (Databox MCP)` - `Agent 3: Correlations + Recommendations` - `HTML Email Report`\n\n### What you need\n- Databox account with website analytics and at least one paid ads platform connected - Free plan available: https://databox.com/?ref=n8n\n- OpenAI API key\n- Gmail account\n\n### Supported Data Sources\nGoogle Analytics - Google Ads - Facebook Ads - LinkedIn Ads - TikTok Ads - YouTube Ads - Microsoft Ads - Reddit Ads - And 100+ more - https://databox.com/integrations"},"typeVersion":1},{"id":"82c15713-2ebc-4b54-8d9d-f05c91200446","name":"Sticky Note 1","type":"n8n-nodes-base.stickyNote","position":[16,448],"parameters":{"color":4,"width":440,"height":772,"content":"## 1 - Schedule\n\n### What this section does\nTriggers the workflow every day at 8 AM and captures today's date so all three agents use consistent reporting windows.\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\n\n\n\n\n\n\n\n\n\n### Change the schedule (optional)\n- Click the \"Every Monday 8 AM\" node\n- Click on the Cron Expression field\n- Modify the schedule (e.g., change to daily, weekly on different day, or custom time)"},"typeVersion":1},{"id":"312cd311-e63a-4ca2-897e-dc69564ecfb1","name":"Sticky Note 2","type":"n8n-nodes-base.stickyNote","position":[496,448],"parameters":{"color":6,"width":1204,"height":772,"content":"## 2 - AI Agents + Databox MCP Setup\n\n### What this section does\nThree agents run in sequence:\n- **Agent 1 - Website Analyst**: fetches sessions, bounce rate, pages per session, goal completions from your website analytics source\n- **Agent 2 - Paid Acquisition Analyst**: fetches spend, CPC, CTR, ROAS and impressions for every connected paid platform\n- **Agent 3 - Correlation Analyst**: receives both outputs, finds cross-channel patterns, ranks channel efficiency, and writes the final HTML report (no MCP calls needed)\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\n\n\n\n\n\n### What you need to do\n1. Click each **OpenAI Chat Model** node and add your API key\n   - You can replace with an **Anthropic Chat Model** node\n2. Click each **Databox MCP Tool** node - set Authentication to `OAuth2` - authorize with your Databox account\n3. Ensure at least one paid ads platform and a website analytics source are connected in Databox"},"typeVersion":1},{"id":"cf0ecb3b-06b4-4e6a-853d-fb4a01d85df8","name":"Sticky Note 3","type":"n8n-nodes-base.stickyNote","position":[1728,448],"parameters":{"color":5,"width":492,"height":772,"content":"## 3 - Email Report Output\n\n### What this section does\nFormats the correlation analysis as a styled HTML email and delivers it to the configured recipient every morning.\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\n\n\n\n\n\n\n\n\n\n### What you need to do\n- Click the **Send Email** node and add your **Gmail credential**\n- Update the **To** field with the recipient email address\n- **Optional**: Add a Slack node after Prepare Email for an additional Slack notification"},"typeVersion":1},{"id":"184c61e2-e4b9-496d-90fc-1d2fcfce9a15","name":"Every Day 8 AM","type":"n8n-nodes-base.scheduleTrigger","notes":"Triggers every day at 8 AM - adjust the cron expression to change frequency","position":[80,704],"parameters":{"rule":{"interval":[{"field":"cronExpression","expression":"0 8 * * *"}]}},"typeVersion":1.2},{"id":"e7a6fbb9-ce74-49a1-a21b-e883e008d388","name":"Get Current Date","type":"n8n-nodes-base.dateTime","position":[272,704],"parameters":{"options":{}},"typeVersion":2},{"id":"8cb84507-2f08-45eb-940e-bee02b6f06a3","name":"Website Analysis Agent","type":"@n8n/n8n-nodes-langchain.agent","position":[608,704],"parameters":{"text":"=Today's Date: {{ $json.formattedDate }}\n\nFetch website performance data from Databox for the last 7 days compared to the previous 7 days. Calculate the exact date ranges based on today's date.\n\nFocus on: traffic volume, engagement quality (bounce rate, pages per session, session duration), and conversion metrics (goal completions, conversion rate).","options":{"systemMessage":"You are a website analytics specialist. Fetch website performance data from Databox via MCP and produce a structured plain-text analysis.\n\nSTEP-BY-STEP:\n1. Call list_accounts to get the account ID.\n2. Call list_data_sources to find connected website analytics sources (Google Analytics, GA4, Adobe Analytics, etc.).\n3. For each website analytics source found, fetch these metrics for both the last 7 days and the previous 7 days:\n   - Sessions or Users\n   - Bounce Rate\n   - Pages per Session\n   - Average Session Duration\n   - Goal Completions or Conversions\n   - Conversion Rate\n4. Calculate week-over-week (WoW) percentage change for each metric.\n\nOUTPUT FORMAT:\nProduce a structured plain-text summary (NOT HTML) with:\n- Data source name\n- Sessions/Users: current value, WoW change %\n- Bounce Rate: current value, WoW change %\n- Pages per Session: current value, WoW change %\n- Avg Session Duration: current value, WoW change %\n- Goal Completions: current value, WoW change %\n- Conversion Rate: current value, WoW change %\n- 2-3 short observations about website behavior patterns\n\nIf no website analytics source is connected, output: \"No website analytics data available.\"\nDo NOT produce HTML - output plain text only."},"promptType":"define"},"retryOnFail":false,"typeVersion":3,"alwaysOutputData":true},{"id":"17afd3f1-7697-46bf-a303-7a91ba14b4c8","name":"Databox MCP Tool","type":"@n8n/n8n-nodes-langchain.mcpClientTool","position":[752,896],"parameters":{"options":{},"endpointUrl":"https://mcp.databox.com/mcp","authentication":"mcpOAuth2Api"},"credentials":{"mcpOAuth2Api":{"id":"credential-id","name":"Databox"}},"typeVersion":1.2},{"id":"7843456d-dba3-484c-8982-f76640ac7ce6","name":"Paid Acquisition Agent","type":"@n8n/n8n-nodes-langchain.agent","position":[960,704],"parameters":{"text":"=Today's Date: {{ $('Get Current Date').item.json.formattedDate }}\n\nWebsite analysis from Agent 1:\n{{ $json.output }}\n\nNow fetch paid acquisition performance data from Databox for the same period (last 7 days vs previous 7 days). Focus on all connected paid advertising platforms - fetch spend efficiency (CPC, CTR, ROAS), volume metrics (impressions, clicks), and conversion data per platform.","options":{"systemMessage":"You are a paid acquisition analyst. Fetch paid channel performance data from Databox via MCP and produce a structured plain-text analysis.\n\nSTEP-BY-STEP:\n1. Call list_accounts to get the account ID.\n2. Call list_data_sources to find all connected paid advertising platforms (Google Ads, Facebook Ads, LinkedIn Ads, TikTok Ads, Microsoft Ads, Reddit Ads, Snapchat Ads, Pinterest Ads, X/Twitter Ads, YouTube Ads).\n3. For EACH connected paid platform, fetch these metrics for both the last 7 days and the previous 7 days:\n   - Spend or Cost\n   - Clicks\n   - CPC (Cost Per Click)\n   - CTR (Click-Through Rate)\n   - Impressions\n   - ROAS or Conversions\n4. Calculate WoW percentage change for each metric on each platform.\n5. Calculate aggregated totals across all platforms: total spend, total clicks, total impressions, total conversions, average CPC, average CTR.\n\nOUTPUT FORMAT:\nProduce a structured plain-text summary (NOT HTML) with:\n- For EACH connected platform: name, spend, clicks, CPC, CTR, impressions, ROAS/conversions with WoW changes\n- Aggregated totals across all platforms with WoW changes\n- 2-3 short observations about paid performance patterns\n\nIf no paid ads platforms are connected, output: \"No paid advertising data available.\"\nDo NOT produce HTML - output plain text only."},"promptType":"define"},"retryOnFail":false,"typeVersion":3,"alwaysOutputData":true},{"id":"e6de4884-bf7c-45f1-a5c8-3481b9ed5f5b","name":"Correlation Agent","type":"@n8n/n8n-nodes-langchain.agent","position":[1328,704],"parameters":{"text":"=Today's Date: {{ $('Get Current Date').item.json.formattedDate }}\n\nWEBSITE ANALYSIS (from Agent 1):\n{{ $('Website Analysis Agent').item.json.output }}\n\nPAID ACQUISITION ANALYSIS (from Agent 2):\n{{ $json.output }}\n\nUsing ONLY the data above (do not call any external tools), produce a complete daily intelligence report as an HTML email body. Structure it as follows:\n\n1. Executive Summary - 2-3 sentences on the single most important cross-channel finding\n2. Website Performance - table with key metrics and WoW changes\n3. Paid Acquisition - per-platform tables with spend, clicks, CPC, CTR, ROAS and WoW changes\n4. Correlation Analysis - the unique insight layer:\n   - Does this week's paid spend correlate with website traffic volume?\n   - Which paid channels drive the highest-quality visitors (lowest bounce rate, highest conversion rate)?\n   - Estimated cost per website conversion by channel (total paid spend divided by goal completions)\n   - Efficiency ranking of paid channels (best to worst)\n5. Recommendations - exactly 3 specific, actionable recommendations based on the data\n6. Footer\n\nOutput ONLY the HTML body content starting with a <div> tag. Do not include <html>, <head>, or <body> tags.","options":{"systemMessage":"You are a marketing intelligence analyst specializing in cross-channel correlation analysis. You do NOT call any tools - you analyze only the data provided in the prompt.\n\nYour job is to synthesize website analytics and paid acquisition data into a single HTML report that surfaces insights neither dataset could reveal on its own.\n\nHTML FORMATTING RULES:\n- Use Databox brand color #3164FA for all headings and table headers\n- Color WoW changes: green (#059669) for improvements, red (#dc2626) for declines\n- Font: 'Helvetica Neue', Arial, sans-serif throughout\n- Table headers: background #3164FA, white text, padding 12px\n- Alternating table rows: #ffffff and #f9fafb\n- Section headings: <h3> with color #3164FA, font-weight 600\n- Executive summary box: background #F7F9FC, left border 4px solid #3164FA, padding 15px, border-radius 4px\n- Correlation insights box: background #FFF8E7, left border 4px solid #F59E0B, padding 15px, border-radius 4px\n- Recommendations box: background #F0FDF4, left border 4px solid #059669, padding 15px, border-radius 4px\n- Footer: small gray text, border-top, font-size 11px\n- No em-dashes - use hyphens instead\n- Format numbers with thousand separators (commas)\n- Currency as $X,XXX.XX, percentages as X.XX%\n- If data for a section is missing, note it gracefully rather than showing an error"},"promptType":"define"},"retryOnFail":false,"typeVersion":3,"alwaysOutputData":true},{"id":"7ff62ebf-8eca-4085-ab2d-aa3ad1656f22","name":"Prepare Email","type":"n8n-nodes-base.code","position":[1808,704],"parameters":{"jsCode":"const agentOutput = $input.first().json.output || '';\n\nconst today = new Date();\nconst dateStr = today.toLocaleDateString('en-US', {\n  month: 'long',\n  day: 'numeric',\n  year: 'numeric'\n});\n\nreturn [{\n  json: {\n    subject: `Daily Paid Acquisition Report - ${dateStr}`,\n    htmlBody: agentOutput\n  }\n}];"},"typeVersion":2},{"id":"f19469a6-7667-4595-93ae-750695e0b3d6","name":"Send Email","type":"n8n-nodes-base.gmail","notes":"Update the To field with the recipient email address","position":[2000,704],"webhookId":"f3e2d1c0-b9a8-7654-3210-fedcba987654","parameters":{"sendTo":"user@example.com","message":"={{ $json.htmlBody }}","options":{},"subject":"={{ $json.subject }}"},"credentials":{"gmailOAuth2":{"id":"credential-id","name":"Gmail"}},"typeVersion":2.2},{"id":"5801443e-8b91-4c50-9c39-4a51ea8981aa","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[1728,16],"parameters":{"color":7,"width":496,"height":400,"content":"### How to connect Databox MCP Tool in n8n\n@[youtube](892KtXhv-vI)"},"typeVersion":1},{"id":"3a24b5cd-a138-4b86-845a-055af932339a","name":"Databox MCP Tool 2","type":"@n8n/n8n-nodes-langchain.mcpClientTool","position":[1136,896],"parameters":{"options":{},"endpointUrl":"https://mcp.databox.com/mcp","authentication":"mcpOAuth2Api"},"credentials":{"mcpOAuth2Api":{"id":"credential-id","name":"Databox"}},"typeVersion":1.2},{"id":"ec486f27-d925-477d-b2e3-bccbdcd08b4a","name":"OpenAI Chat Model 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1","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[560,896],"parameters":{"model":{"__rl":true,"mode":"list","value":"gpt-4o","cachedResultName":"gpt-4o"},"options":{"maxTokens":2048},"builtInTools":{}},"credentials":{"openAiApi":{"id":"credential-id","name":"OpenAi account 2"}},"typeVersion":1.3}],"active":false,"pinData":{},"settings":{"executionOrder":"v1"},"versionId":"39bced5e-61fc-44d0-956b-acd8337a6cf5","connections":{"Prepare Email":{"main":[[{"node":"Send Email","type":"main","index":0}]]},"Every Day 8 AM":{"main":[[{"node":"Get Current Date","type":"main","index":0}]]},"Databox MCP Tool":{"ai_tool":[[{"node":"Website Analysis Agent","type":"ai_tool","index":0}]]},"Get Current Date":{"main":[[{"node":"Website Analysis Agent","type":"main","index":0}]]},"Correlation Agent":{"main":[[{"node":"Prepare Email","type":"main","index":0}]]},"Databox MCP Tool 2":{"ai_tool":[[{"node":"Paid Acquisition Agent","type":"ai_tool","index":0}]]},"OpenAI Chat Model 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