This n8n workflow automates the process of qualifying dealer leads by capturing input via a webhook, analyzing and processing the data, and storing results in a Google Sheet. The process begins with a webhook trigger that receives lead information, which is then split into manageable chunks for further analysis. Using natural language processing (NLP) and embedding techniques, the workflow assesses the lead’s details, stores contextual vectors, and performs similarity searches to generate relevant responses. The AI-powered agent interprets the data to determine lead quality, providing actionable insights. Finally, the workflow logs all activities and results into a dedicated Google Sheet for record-keeping and follow-up. This setup is ideal for automotive or product dealerships seeking automated lead qualification to improve sales efficiency.
Dealer Lead Qualification Workflow
Node Count | 11 – 20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.embeddingsCohere, @n8n/n8n-nodes-langchain.lmChatHf, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStorePinecone, googleSheets, stickyNote, webhook |
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