Automating SEO with n8n: A Blueprint
Most "automation" in SEO is just scheduling social posts. Real automation changes how you process data.
At SomewhatBot, we use n8n to orchestrate complex workflows that would otherwise require a team of three analysts. Here is the exact architecture we use for keyword clustering.
The Workflow Architecture
We don't just "hit an API". We chain them. The process looks like this:
- Ingestion: We pull raw keyword data from Semrush or Ahrefs exports via CSV webhook.
- Enrichment: Each keyword is run through a SERP API to check live difficulty, not the "cached" metric tools give you.
- Clustering: We pass the intent data to an LLM (Claude 3.5 Sonnet) to group them by "User Problem" rather than just lexical similarity.
- Execution: The finalized clusters are pushed directly to our CMS drafting queue.
Why n8n?
Zapier is too expensive at scale. Python scripts are hard to maintain. n8n sits in the "Goldilocks" zone—visual enough to debug quickly, but code-heavy enough to handle complex transformation logic (Javascript) in every node.
Pro Tip
Always use the specific "Switch" node to handle error states. If an API times out, your workflow shouldn't die—it should retry or log the failure to a designated Slack channel.
Want to implement this?
SomewhatBot's "Keyword Research" tool automates the initial data gathering phase described in this article.
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