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- n8n-nodes-base.manualTrigger - manualTrigger
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This workflow is provided as-is. Please review and test before using in production.
This template can be used to find the content gaps in your competitors' discourse : identifying the topics they are not yet connecting and giving you an opportunity to fill in this gap with your co...
n8n-nodes-base.manualtrigger, n8n-nodes-base.httprequest, n8n-nodes-base.htmlextract, n8n-nodes-base.merge, n8n-nodes-base.code, n8n-nodes-base.splitinbatches, n8n-nodes-base.stickynote, n8n-nodes-base.googledocs
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by InfraNodus.
Original n8n.io sourceThis template can be used to find the content gaps in your competitors' discourse: identifying the topics they are not yet connecting and giving you an opportunity to fill in this gap with your content and product ideas. It will also generate research questions that will help bridge the gaps and generate new ideas.
The template showcases the use of multiple n8n nodes and processes:
This approach can be very useful for research, marketing, and SEO applications as you can quickly get an overview of the main topics that are available online for a certain niche and understand what is missing.
In the context of SEO, content gaps are usually understood as the topics that your competitors rank for but you do not.
However, it's hard to rank for these topics because there's very high competition. So a much more effective way is to identify the gaps between the topics your competitors are talking about that are not yet bridged in their discourse.
If you address these gaps in your content, you will increase the informational gain that your content offers and also offer a novel perspective while touching upon the topics that are relevant in your field.
For example, if we analyze the top websites for "body and physical practices, fitness, etc." we will see that most of them are talking about the health and fitness aspects and another big topic is the community aspect.
However, there is a gap between the two topics: which means that most of the websites (companies) that talk about this topic don't mention the two in the same context. This might be an opportunity: bridging the gap between health, fitness but also emphasizing the community aspect that comes with a collective practice.
This template consists of the two stages:
Data enrichment of a Google sheet file with a list of your competitors using InfraNodus' GraphRAG to generate topical summaries and graph summaries for every URL you're analyzing.
Insight generation (using InfraNodus to identify the main topical clusters and gaps in those summaries, these insights are then added to the Google sheet file.
Additionally, it contains a sub workflow that you can activate and launch to ask Perplexity model to conduct a market research and find the companies that operate in your field and populate the original Google sheet file.
Here's a description step by step:
You need an InfraNodus GraphRAG API account and key to use this workflow.
body name field.Note: OpenAI key is not required. But you might want to get a Perplexity AI key if you'd like to use the sub-workflow that populates the Google sheet with your competitors' website addresses (if you don't have this list yet).
You can use this same workflow with a Telegram bot or Slack (to be notified of the summaries and ideas).
You can also hook up automated social media content creation workflows in the end of this template, so you can generate posts that are relevant (covering the important topics in your niche) but also novel (because they connect them in a new way).
Check out our n8n templates for ideas at https://n8n.io/creators/infranodus/
Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/20234254556828-Find-Content-Gaps-in-Websites-Market-Research-and-SEO-n8n-Workflow
Also check the full tutorial with a conceptual explanation at https://support.noduslabs.com/hc/en-us/articles/20454382597916-Beat-Your-Competition-Target-Their-Content-Gaps-with-this-n8n-Automation-Workflow
Also check out the video tutorial with a demo:
For support and help with this workflow, please, contact us at https://support.noduslabs.com
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 37 workflow blocks. Download the JSON for the full node graph.
| Workflow | Find Content Gaps in Competitors' Websites with InfraNodus GraphRAG for SEO |
|---|---|
| Complexity | advanced |
| Nodes | 37 |
| Categories | Market Research, AI RAG |
| Author | InfraNodus |
| Published | 26 May 2025 |
Use the JSON export at /data/workflows/4403/4403.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
This template can be used to find the content gaps in your competitors' discourse : identifying the topics they are not yet connecting and giving you an opportunity to fill in this gap with your co...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Market Research, AI RAG use case.