Automate Pinterest Analysis & AI-Powered Content Suggestions With Pinterest API
Workflow JSON
{"id": "gP9EsxKN5agUGzDS", "meta": {"instanceId": "73d9d5380db181d01f4e26492c771d4cb5c4d6d109f18e2621cf49cac4c50763", "templateCredsSetupCompleted": true}, "name": "Automate Pinterest Analysis & AI-Powered Content Suggestions With Pinterest API", "tags": [], "nodes": [{"id": "7f582bb4-97cd-458e-a7b7-b518c5b8a4ca", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [540, -260], "parameters": {"model": {"__rl": true, "mode": "list", "value": "gpt-4o-mini"}, "options": {}}, "credentials": {"openAiApi": {"id": "", "name": "[Your openAiApi]"}}, "typeVersion": 1.2}, {"id": "c6772882-468c-4391-a259-93e52daf49d4", "name": "Airtable2", "type": "n8n-nodes-base.airtableTool", "position": [700, -260], "parameters": {"id": "=", "base": {"__rl": true, "mode": "list", "value": "appfsNi1QEhw6WvXK", "cachedResultUrl": "https://airtable.com/appfsNi1QEhw6WvXK", "cachedResultName": "Pinterest_Metrics"}, "table": {"__rl": true, "mode": "list", "value": "tbl9Dxdrwx5QZGFnp", "cachedResultUrl": "https://airtable.com/appfsNi1QEhw6WvXK/tbl9Dxdrwx5QZGFnp", "cachedResultName": "Pinterest_Organic_Data"}, "options": {}}, "credentials": {"airtableTokenApi": {"id": "", "name": "[Your airtableTokenApi]"}}, "typeVersion": 2.1}, {"id": "85ea8bec-14c8-4277-b2e3-eb145db0713a", "name": "OpenAI Chat Model1", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [920, -280], "parameters": {"model": {"__rl": true, "mode": "list", "value": "gpt-4o-mini"}, "options": {}}, "credentials": {"openAiApi": {"id": "", "name": "[Your openAiApi]"}}, "typeVersion": 1.2}, {"id": "b8f7d0d6-b58f-4a41-a15d-99f4d838bb8c", "name": "8:00am Morning Scheduled Trigger", "type": "n8n-nodes-base.scheduleTrigger", "position": [-660, -140], "parameters": {"rule": {"interval": [{"daysInterval": 7, "triggerAtHour": 8}]}}, "typeVersion": 1.2}, {"id": "593a320d-825e-42f9-8ab6-adafd5288fa5", "name": "Pull List of Pinterest Pins From Account", "type": "n8n-nodes-base.httpRequest", "position": [-340, -140], "parameters": {"url": "https://api.pinterest.com/v5/pins", "options": {"redirect": {"redirect": {}}}, "sendBody": true, "sendHeaders": true, "bodyParameters": {"parameters": [{}]}, "headerParameters": {"parameters": [{"name": "Authorization", "value": "Bearer "}]}}, "typeVersion": 4.2}, {"id": "1e6d00fe-2b32-4d46-a230-063254ebab74", "name": "Update Data Field To Include Organic", "type": "n8n-nodes-base.code", "position": [-20, -140], "parameters": {"jsCode": "// Initialize an array to hold the output formatted for Airtable\nconst outputItems = [];\n\nfor (const item of $input.all()) {\n if (item.json.items && Array.isArray(item.json.items)) {\n for (const subItem of item.json.items) {\n // Construct an object with only the required fields for Airtable\n outputItems.push({\n id: subItem.id || null,\n created_at: subItem.created_at || null,\n title: subItem.title || null,\n description: subItem.description || null,\n link: subItem.link || null,\n type: \"Organic\" // Assign the value \"Organic\" to the 'Type' field\n });\n }\n }\n}\n\n// Return the structured output\nreturn outputItems;\n"}, "typeVersion": 2}, {"id": "539de144-dc67-4b14-b58e-2896edb1c3e6", "name": "Create Record Within Pinterest Data Table", "type": "n8n-nodes-base.airtable", "position": [260, -140], "parameters": {"base": {"__rl": true, "mode": "list", "value": "appfsNi1QEhw6WvXK", "cachedResultUrl": "https://airtable.com/appfsNi1QEhw6WvXK", "cachedResultName": "Pinterest_Metrics"}, "table": {"__rl": true, "mode": "list", "value": "tbl9Dxdrwx5QZGFnp", "cachedResultUrl": "https://airtable.com/appfsNi1QEhw6WvXK/tbl9Dxdrwx5QZGFnp", "cachedResultName": "Pinterest_Organic_Data"}, "columns": {"value": {"link": "={{ $json.link }}", "type": "={{ $json.type }}", "title": "={{ $json.title }}", "pin_id": "={{ $json.id }}", "created_at": "={{ $json.created_at }}", "description": "={{ $json.description }}"}, "schema": [{"id": "id", "type": "string", "display": true, "removed": false, "readOnly": true, "required": false, "displayName": "id", "defaultMatch": true}, {"id": "pin_id", "type": "string", "display": true, "removed": false, "readOnly": false, "required": false, "displayName": "pin_id", "defaultMatch": false, "canBeUsedToMatch": true}, {"id": "created_at", "type": "string", "display": true, "removed": false, "readOnly": false, "required": false, "displayName": "created_at", "defaultMatch": false, "canBeUsedToMatch": true}, {"id": "title", "type": "string", "display": true, "removed": false, "readOnly": false, "required": false, "displayName": "title", "defaultMatch": false, "canBeUsedToMatch": true}, {"id": "description", "type": "string", "display": true, "removed": false, "readOnly": false, "required": false, "displayName": "description", "defaultMatch": false, "canBeUsedToMatch": true}, {"id": "link", "type": "string", "display": true, "removed": false, "readOnly": false, "required": false, "displayName": "link", "defaultMatch": false, "canBeUsedToMatch": true}, {"id": "type", "type": "string", "display": true, "removed": false, "readOnly": false, "required": false, "displayName": "type", "defaultMatch": false, "canBeUsedToMatch": true}, {"id": "active7DayUsers", "type": "string", "display": true, "removed": true, "readOnly": false, "required": false, "displayName": "active7DayUsers", "defaultMatch": false, "canBeUsedToMatch": true}, {"id": "sessions", "type": "string", "display": true, "removed": true, "readOnly": false, "required": false, "displayName": "sessions", "defaultMatch": false, "canBeUsedToMatch": true}, {"id": "userEngagementDuration", "type": "string", "display": true, "removed": true, "readOnly": false, "required": false, "displayName": "userEngagementDuration", "defaultMatch": false, "canBeUsedToMatch": true}], "mappingMode": "defineBelow", "matchingColumns": ["id"], "attemptToConvertTypes": false, "convertFieldsToString": false}, "options": {}, "operation": "upsert"}, "credentials": {"airtableTokenApi": {"id": "", "name": "[Your airtableTokenApi]"}}, "typeVersion": 2.1}, {"id": "250f5121-437e-4bff-82af-95a156126127", "name": "Pinterest Analysis AI Agent", "type": "@n8n/n8n-nodes-langchain.agent", "position": [540, -440], "parameters": {"text": "You are a data analysis expert. You will pull data from the table and provide any information in regards to trends in the data. \n\nYour output should be suggestions of new pins that we can post to reach the target audiences. \n\nAnalyze the data and just summary of the pin suggestions that the team should build. ", "options": {}, "promptType": "define"}, "typeVersion": 1.7}, {"id": "181e9d89-c0f9-4de2-bdce-9359b967157c", "name": "Pinterest Data Analysis Summary LLM", "type": "@n8n/n8n-nodes-langchain.chainSummarization", "position": [900, -440], "parameters": {"options": {"summarizationMethodAndPrompts": {"values": {"prompt": "=Write a concise summary of the following:\n\n\n\"{{ $json.output }}\"\n\n\nCONCISE SUMMARY:"}}}}, "typeVersion": 2}, {"id": "432e7bd7-36b4-4903-8e93-c8bd6e140a04", "name": "Send Marketing Trends & Pinterest Analysis To Marketing Manager", "type": "n8n-nodes-base.gmail", "position": [1220, -440], "webhookId": "f149c1b5-c028-4dff-9d22-a72951f2ef91", "parameters": {"sendTo": "john.n.foster1@gmail.com", "message": "={{ $json.response.text }}", "options": {}, "subject": "Pinterest Trends & Suggestions"}, "credentials": {"gmailOAuth2": {"id": "", "name": "[Your gmailOAuth2]"}}, "executeOnce": true, "typeVersion": 2.1}, {"id": "dadfb22a-b1d3-459d-a332-5a2c52fd4ca0", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [-740, -320], "parameters": {"color": 5, "width": 280, "height": 440, "content": "Scheduled trigger at 8:00am to start the workflow. \n\nThis can be updated to your schedule preference as an email with marketing trends can be sent to best fit one's schedule. "}, "typeVersion": 1}, {"id": "3b156d97-11bf-4d8a-9bd9-c1e23a0592d8", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [-420, -300], "parameters": {"color": 6, "width": 860, "height": 360, "content": "Scheduled trigger begin process to gather Pinterest Pin data and store them within Airtable. This data can be referenced or analyzed accordingly. \n\n*If you would like to bring in Pinterest Ads data, the data is already labeled as Organic.\n\nThis is perfect for those who are creating content calendars to understand content scheduling."}, "typeVersion": 1}, {"id": "65586422-a631-477b-833d-5c445b1be744", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [480, -580], "parameters": {"color": 4, "width": 940, "height": 460, "content": "AI Agent will go through Pinterest Pins and analyze any data and trends to be able to reach target audience. The data is then summarized within the Summary LLM.\n\nThe summarized results are then sent to the Marketing Manager within an email to help lead content creation efforts. "}, "typeVersion": 1}], "active": false, "pinData": {}, "settings": {"executionOrder": "v1"}, "versionId": "d6f64ee7-ae49-4a6b-8bf8-9a709c580357", "connections": {"Airtable2": {"ai_tool": [[{"node": "Pinterest Analysis AI Agent", "type": "ai_tool", "index": 0}]]}, "OpenAI Chat Model": {"ai_languageModel": [[{"node": "Pinterest Analysis AI Agent", "type": "ai_languageModel", "index": 0}]]}, "OpenAI Chat Model1": {"ai_languageModel": [[{"node": "Pinterest Data Analysis Summary LLM", "type": "ai_languageModel", "index": 0}]]}, "Pinterest Analysis AI Agent": {"main": [[{"node": "Pinterest Data Analysis Summary LLM", "type": "main", "index": 0}]]}, "8:00am Morning Scheduled Trigger": {"main": [[{"node": "Pull List of Pinterest Pins From Account", "type": "main", "index": 0}]]}, "Pinterest Data Analysis Summary LLM": {"main": [[{"node": "Send Marketing Trends & Pinterest Analysis To Marketing Manager", "type": "main", "index": 0}]]}, "Update Data Field To Include Organic": {"main": [[{"node": "Create Record Within Pinterest Data Table", "type": "main", "index": 0}, {"node": "Pinterest Analysis AI Agent", "type": "main", "index": 0}]]}, "Pull List of Pinterest Pins From Account": {"main": [[{"node": "Update Data Field To Include Organic", "type": "main", "index": 0}]]}}}How to Import This Workflow
- 1Copy the workflow JSON above using the Copy Workflow JSON button.
- 2Open your n8n instance and go to Workflows.
- 3Click Import from JSON and paste the copied workflow.
Don't have an n8n instance? Start your free trial at n8nautomation.cloud
Related Templates
KB Tool - Confluence Knowledge Base
Quickly retrieve information from your Confluence knowledge base with this n8n workflow. It connects to your Confluence instance via an HTTP Request node, allowing you to query for specific content directly from n8n. This workflow is ideal for support teams needing to rapidly access articles, developers looking up documentation, or anyone who frequently references Confluence pages and wants to integrate that data into other automated processes. By centralizing Confluence queries within n8n, you save significant time and effort previously spent manually navigating and searching, streamlining information retrieval and improving operational efficiency.
Analyze the sentiment of feedback and send a message on Mattermost
Automatically analyze customer feedback sentiment and notify your team on Mattermost with this n8n workflow. This automation connects Typeform submissions directly to Google Cloud Natural Language for sentiment analysis, then routes the results to your Mattermost channel. When a user submits a form through Typeform, the workflow extracts the feedback, sends it to Google Cloud Natural Language for sentiment scoring, and based on that score, sends a message to a designated Mattermost channel, allowing for immediate team awareness of positive, negative, or neutral feedback. This workflow is ideal for product managers, customer support teams, or marketing departments who need to quickly gauge public opinion or customer satisfaction from surveys, support tickets, or product reviews, enabling faster response times to critical feedback and reducing the manual effort of monitoring and reporting. It saves significant time and ensures that important customer insights are never missed, fostering a more responsive and customer-centric operation.
Hacker News Throwback Machine - See What Was Hot on This Day, Every Year!
Discover what was trending on Hacker News on this exact day, every year, with the Hacker News Throwback Machine. This n8n workflow automates the process of fetching historical Hacker News front pages and summarizing the top stories, delivering a daily dose of tech nostalgia directly to your Telegram chat. A Schedule Trigger initiates the workflow, which then dynamically generates a list of past years. For each year, it uses an HTTP Request node to retrieve the Hacker News front page for today's date, then an HTML Extract Details node parses the headlines and links. These headlines are then compiled and fed into a Google Gemini Chat Model via a Basic LLM Chain, which summarizes the most interesting stories. Finally, the summarized insights are sent to your designated Telegram chat, providing a unique historical perspective without any manual effort. This workflow is perfect for tech enthusiasts, developers, or anyone curious about the evolution of tech news, saving significant time and effort compared to manually searching through archives.