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An n8n workflow that suggests SEO seed keywords. You describe your ideal customer in five short fields, and a Claude model returns 15 to 20 head keywords, one per item, ready to send to a sheet or a database.
SEO seed keywords generated from your ideal customer profile is an n8n workflow in the Marketing & SEO category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page or copy its JSON, then import it into an n8n canvas. Nothing runs until you activate it in n8n.
Manual start
You start it by hand, and it needs:
A list of 15 to 20 seed keywords in lowercase, one per item, ready to send to a sheet or a database
What you need before you start.
Keyword model
Reads the customer profile and returns the seed keywords.
NeedsAnthropic API key
Checked by Mindket on 13 Nov 2026
This n8n workflow suggests SEO seed keywords. You describe your ideal customer in five short text fields, and a Claude model returns a list of 15 to 20 head keywords that cover awareness, consideration and decision searches. One keyword comes out per item, ready to send to a sheet or a database. Eight nodes run it, beside eight sticky notes.
Marketers and founders who are starting an SEO plan and want a first list of topics to research. Skip it if you already have keyword data from an SEO tool, since this list comes from a model and carries no search volume.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| SaaS | Product marketers | Start a content plan from the customer’s needs | A marketer describes a billing tool’s customer and gets 18 head keywords to check. |
| Startups | Founders | Find the first topics for a blog | A founder pastes the customer’s pain points and reads the list before writing. |
| Agency | SEO consultants | Draft seeds for a new client before a deeper study | A consultant fills the five fields from a client call and sends the list to a sheet. |
| Content | Editors | Get topic ideas that match a reader’s stage | An editor asks for terms across awareness and decision searches. |
You need a little n8n: import a file, add an Anthropic credential and fill in five text fields.
Any n8n that can reach Anthropic will run it. It starts by hand, and the keywords end at a placeholder node that you connect to your own store.
Download saves a zip with workflow.json and Mindket’s setup notes in your downloads folder. You need an Anthropic key and a short description of your customer.
| Need | Detail |
|---|---|
| n8n | On n8n Cloud or on a server of your own |
| Anthropic | An API key, or another chat model you prefer |
| Your customer | The product, their pain points, their goals, how they solve the problem now and how expert they are |
workflow.json.Anthropic Chat Model.Set Ideal Customer Profile (ICP) and replace the five placeholder texts: product, pain points, goals, current solutions and expertise level.Split Out returns, one per keyword.Connect to your own database to a Google Sheets, Airtable or database node to keep the list.Fill in the profile and run it. Run it again with a changed profile for another angle, and keep the keywords that make sense to you.
| To change | Where |
|---|---|
| The kind of business | The system message and the prompt in AI Agent, which both say B2B SaaS |
| How many keywords | The numbers in the rules and the final instruction |
| The model | Anthropic Chat Model, or another chat model node |
| Where the keywords go | The Connect to your own database node |
A product marketer fills the fields for an invoicing tool. The product is online invoicing for freelancers, the pain points are late payments and manual chasing, and the customer is a solo designer with little finance knowledge.
The model writes its thoughts first and then returns a list such as “freelance invoicing software” and “how to chase late invoices”. Split Out turns the list into one item per keyword.
If you are new. n8n draws a workflow as boxes joined by lines, and each box, a node, does one job. A seed keyword is a broad search term that you grow into topics later. An AI agent is a node that asks a chat model to answer, and here it also returns its answer in a fixed shape.
For experts. Aggregate for AI node puts the five fields in one data item, and the prompt sends the whole object as JSON text. Structured Output Parser gives the agent a thoughts string and an answer list, so Split Out can read output.answer.
| Node | What it does | What to know |
|---|---|---|
Set Ideal Customer Profile (ICP) | Holds the five text fields | Placeholders you replace |
AI Agent | Writes the keywords from the rules in its prompt | Version 2.2, with an output parser |
Structured Output Parser | Shapes the reply as thoughts and answer | Added in Mindket’s copy |
Split Out | Makes one item per keyword | Reads output.answer |
The file had a few faults that this copy repairs, and the list is only a model’s suggestion.
Split Out found no list. Mindket’s copy adds a Structured Output Parserproduct field reached the model. Mindket’s copy sends all fiveclaude-3-5-sonnet-20240620, which Anthropic retired on 28 October 2025. Mindket’s copy names claude-sonnet-5-5, listed as active on 12 November 2026An n8n workflow that suggests SEO seed keywords. You describe your ideal customer in five short text fields, and a Claude model returns a list of 15 to 20 head keywords that cover awareness, consideration and decision searches. One keyword comes out per item, ready to send to a sheet or a database.
workflow.json: the workflow as n8n exports it, 16 nodes. Eight of them run and eight are sticky notes, three of which are switched off. It holds no credential.README.md: these notes.AI Agent was on version 1.6 in Conversational mode. n8n's source, read on 12 November 2026, marks that mode as deprecated and removed in n8n v3. It is an AI Agent on version 2.2 now.thoughts text and an answer list, and Split Out reads output.answer. The old agent returned that JSON as plain text, so Split Out had no list to split. A new Structured Output Parser node gives the agent that shape, with thoughts as text and answer as a list of strings.product field to the model. The other four fields never reached it. It sends all five now, as JSON text.Anthropic Chat Model named no model, so n8n used the default of its version, claude-3-5-sonnet-20240620. Anthropic retired that model on 28 October 2025 and names claude-sonnet-5-5 as the replacement. The node uses claude-sonnet-5-5, which Anthropic's page lists as active on 12 November 2026.workflow.json.Anthropic Chat Model.Set Ideal Customer Profile (ICP) and replace the five placeholder texts. The fields are product, pain points, goals, current solutions and expertise level.Split Out returns, one per keyword.Connect to your own database, which does nothing yet, to a Google Sheets, Airtable or database node to keep the list.When clicking ‘Test workflow’ starts the run by hand.Set Ideal Customer Profile (ICP) holds the five text fields.Aggregate for AI node gathers them into one data list.AI Agent sends the model the prompt and its numbered rules. They ask for broad head terms, a mix of difficulty and intent, related tools, location terms when they apply and lowercase text with no punctuation. The model writes its ideas first and then the answer.Structured Output Parser turns the reply into thoughts and an answer list.Split Out makes one item per keyword, and Connect to your own database passes them on.AI Agent both say B2B SaaS.Anthropic Chat Model, or replace it with another chat model node.Connect to your own database.NOTICE.md 616 B README.md 4 KB workflow.json 12 KB
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