This n8n workflow is designed to automate the process of analyzing trending topics, generating engaging content, and scheduling posts based on real-time data. The process begins with a scheduled trigger that activates the workflow regularly to ensure up-to-date insights. It pulls trending data from Google Trends for Australia, aggregates the data, and utilizes language models including OpenAI and Google Gemini to analyze trends and generate tailored tweets and content ideas. The workflow features memory buffers to maintain context, auto-corrects and structures generated output for clarity, and finally loops through each content idea to produce multiple outputs. Throughout the process, various sticky notes are used for process notes or debugging. This automation is ideal for social media managers, marketers, and content creators who want to stay ahead of trends and continuously generate fresh engaging content automatically.
Automated Trend Analysis and Content Generation Workflow
Node Count | >20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmChatGoogleGemini, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.outputParserAutofixing, @n8n/n8n-nodes-langchain.outputParserStructured, aggregate, code, googleBigQuery, scheduleTrigger, splitInBatches, stickyNote, twitter, wait |
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