Mindket

SEO seed keywords generated from your ideal customer profile

Newversion 1 · updated

Overview

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.

At a glance

Runs in
  • n8n Cloud: import the file into a new workflow there
  • Your own n8n server: the same file and steps
  • Another model: replace the Anthropic Chat Model node with any chat model node

Platform

Connects 1 app

How it works

Trigger

Manual start

You start it by hand, and it needs:

  • The product and the customer’s pain points
  • The customer’s goals, current solutions and level of expertise

Actions

  1. The five profile fields are gathered into one item
  2. A Claude model reads the profile and the rules for choosing keywords
  3. The model writes its thoughts and returns an answer list of 15 to 20 keywords
  4. The list is split so that each keyword is its own item

Result

A list of 15 to 20 seed keywords in lowercase, one per item, ready to send to a sheet or a database

Integrations

What you need before you start.

Anthropic

Keyword model

Reads the customer profile and returns the seed keywords.

NeedsAnthropic API key

Workflow check

Checked by Mindket on 13 Nov 2026

Steps
6 steps, starting by hand
AI
1 step calls an AI model: AI Agent
Sign-ins
Signs in to: Anthropic
API keys
No API key is left in the file
Step types
Mindket’s checker reads all 6 of its step types

Read from the workflow’s file, not from a run.

About

What it is

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.

Who it suits

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.

Who uses it, and how
IndustryWho uses itHow they use itExample
SaaSProduct marketersStart a content plan from the customer’s needsA marketer describes a billing tool’s customer and gets 18 head keywords to check.
StartupsFoundersFind the first topics for a blogA founder pastes the customer’s pain points and reads the list before writing.
AgencySEO consultantsDraft seeds for a new client before a deeper studyA consultant fills the five fields from a client call and sends the list to a sheet.
ContentEditorsGet topic ideas that match a reader’s stageAn 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.

Where to use it

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.

  • n8n Cloud: import the file into a new workflow there
  • Your own n8n server: the same file and steps
  • Another model: replace the Anthropic Chat Model node with any chat model node

Setup

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.

What you need first
NeedDetail
n8nOn n8n Cloud or on a server of your own
AnthropicAn API key, or another chat model you prefer
Your customerThe product, their pain points, their goals, how they solve the problem now and how expert they are
  1. In n8n, create a workflow, open its menu, choose Import from File and pick workflow.json.
  2. Add an Anthropic credential and select it in Anthropic Chat Model.
  3. Open Set Ideal Customer Profile (ICP) and replace the five placeholder texts: product, pain points, goals, current solutions and expertise level.
  4. Press Test workflow and read the items that Split Out returns, one per keyword.
  5. Connect Connect to your own database to a Google Sheets, Airtable or database node to keep the list.

How to use it

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.

What to change for a different result
To changeWhere
The kind of businessThe system message and the prompt in AI Agent, which both say B2B SaaS
How many keywordsThe numbers in the rules and the final instruction
The modelAnthropic Chat Model, or another chat model node
Where the keywords goThe Connect to your own database node

Example

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.

For newcomers and experts

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.

Where to look closer
NodeWhat it doesWhat to know
Set Ideal Customer Profile (ICP)Holds the five text fieldsPlaceholders you replace
AI AgentWrites the keywords from the rules in its promptVersion 2.2, with an output parser
Structured Output ParserShapes the reply as thoughts and answerAdded in Mindket’s copy
Split OutMakes one item per keywordReads output.answer

Good to know

The file had a few faults that this copy repairs, and the list is only a model’s suggestion.

  • Agent type: the agent used the Conversational mode, which n8n’s source marks as deprecated. Mindket’s copy is a plain AI Agent on version 2.2
  • Output shape: the old agent returned its JSON as text, so Split Out found no list. Mindket’s copy adds a Structured Output Parser
  • Profile: only the product field reached the model. Mindket’s copy sends all five
  • Model: the node named none, so n8n would use claude-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 2026
  • No data: the list has no volumes or difficulty, so check it in an SEO tool
  • Business type: the wording is for a B2B SaaS company
  • Your data: your customer profile goes to Anthropic
  • Credentials: the JSON holds none

README and files

README

SEO seed keywords generated from your ideal customer profile

An 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.

What is inside

  • 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.

What we changed from the original copy

  • 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.
  • The prompt asks the model for JSON with a 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.
  • The prompt sent only the 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.
  • The sticky note that put a price on a run, written for the old model, now says only that a run is one short model call.
  • The credential links are gone, and the file's name is ours.
  • Nothing else. The rules in the prompt, the system message and the placeholder fields are as the file had them.

Before you start

  • An n8n instance, on n8n Cloud or your own server.
  • An Anthropic API key. You can swap in another chat model if you prefer.
  • A short description of your ideal customer: the product, their pain points, their goals, how they solve the problem now and how expert they are.

Set it up

  1. In n8n, create a workflow, open its menu and choose Import from File. Pick workflow.json.
  2. Add an Anthropic credential and select it in Anthropic Chat Model.
  3. Open Set Ideal Customer Profile (ICP) and replace the five placeholder texts. The fields are product, pain points, goals, current solutions and expertise level.
  4. Press Test workflow and read the items that Split Out returns, one per keyword.
  5. Connect Connect to your own database, which does nothing yet, to a Google Sheets, Airtable or database node to keep the list.

What happens in a run

  1. When clicking ‘Test workflow’ starts the run by hand.
  2. Set Ideal Customer Profile (ICP) holds the five text fields.
  3. Aggregate for AI node gathers them into one data list.
  4. 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.
  5. Structured Output Parser turns the reply into thoughts and an answer list.
  6. Split Out makes one item per keyword, and Connect to your own database passes them on.

What to change

  • The kind of business: the system message and the prompt in AI Agent both say B2B SaaS.
  • How many keywords: the numbers in the rules and in the final instruction. The sticky note says 20 and the prompt asks for 15 to 20.
  • The model: Anthropic Chat Model, or replace it with another chat model node.
  • Where the keywords go: replace Connect to your own database.

Good to know

  • The model suggests keywords. It has no search volume or difficulty data, so check the list in an SEO tool before you plan content around it.
  • The prompt and the rules are written for a B2B SaaS company. A shop or a local service needs its own wording.
  • Two of the numbered rules are both numbered 13 in the prompt. The workflow still runs.
  • Data: your customer profile goes to Anthropic.
  • Cost: one model call per run, billed by Anthropic.
Files
NOTICE.md  616 B
README.md  4 KB
workflow.json  12 KB

3 files, 17 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

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