Deep Research - Sales Lead Magnet Agent
VerifiedGenerates research-backed lead magnet articles and saves them to Google Docs.
What this workflow does
This n8n automation uses AI agents and chat models to convert a submitted topic into multiple research queries, gather data from various sources, and automatically produce a formatted Google Doc ready for distribution.
It is designed for sales and marketing professionals who need to quickly create in-depth lead magnets without manual research or document formatting.
Who is this for?
Sales enablement teams, B2B marketers, and independent consultants who need to produce research-backed lead magnets quickly for LinkedIn distribution.
What problem it solves
Creating comprehensive, citation-rich lead magnet articles requires hours of manual research and formatting; this workflow automates the full pipeline from topic input to polished Google Doc.
Live workflow preview
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What it automates
Topic-to-doc in one run
User pastes a sales topic; the workflow returns a ready-to-share Google Doc with chapters, citations, and LinkedIn-optimized structure.
Company-specific research
When a company name is supplied, the agents pull relevant internal context alongside public sources to tailor the magnet.
Multi-chapter content batch
Parallel agents write 8-10 sections simultaneously, then the editor agent merges them into a single cohesive document.
How the workflow works
The 9 nodes in this automation, in order.
- 1Google DrivegoogleDrive
- 2Google DocsgoogleDocs
- 3Codecode
- 4AI Agent@n8n/n8n-nodes-langchain.agent
- 5Anthropic Chat Model@n8n/n8n-nodes-langchain.lmChatAnthropic
- 6Structured Output Parser@n8n/n8n-nodes-langchain.outputParserStructured
- 7Call n8n Workflow Tool@n8n/n8n-nodes-langchain.toolWorkflow
- 8HTTP Request Tool@n8n/n8n-nodes-langchain.toolHttpRequest
- 9OpenRouter Chat Model@n8n/n8n-nodes-langchain.lmChatOpenRouter
Apps & integrations used
How to set up Deep Research - Sales Lead Magnet Agent
- 1Add Google Drive and Google Docs credentials in n8n credentials panel
- 2Connect Anthropic and OpenRouter API keys
- 3Import the workflow JSON and activate the chat trigger node
- 4Map the Structured Output Parser schema to the Query Builder Agent
- 5Configure the Call n8n Workflow Tool nodes for the Research Assistant sub-workflows
- 6Test with a sample topic and verify the final Google Doc is created in the target folder
How to customize this workflow
- →Swap Anthropic for another supported chat model via OpenRouter
- →Change the chat trigger to a webhook or schedule node
- →Add an extra HTTP Request Tool step to post the Doc link to Slack
- →Adjust the Structured Output Parser schema to request more or fewer research queries
Deep Research - Sales Lead Magnet Agent: pros & cons
Pros
- +Parallel AI agents speed up chapter writing
- +Direct Google Docs output removes manual formatting
- +Uses both Anthropic and OpenRouter for model flexibility
- +Structured output keeps research queries consistent
Cons
- –Intermediate setup requires comfort with sub-workflows and parsers
- –No built-in Perplexity node; research relies on HTTP/OpenRouter calls
- –Token usage can be high with multiple agents running in parallel
Frequently asked questions
A fully formatted Google Doc containing a professional lead magnet article with title, chapters, citations, and image placeholders.
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