This article provides a complete, practical walkthrough of the Splitout Aggregate Create Triggered n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title: Boost Your SEO Strategy: Automate Seed Keyword Generation with AI in n8n
   
   Meta Description: Discover how to use n8n and Anthropic’s Claude AI to automatically generate 15–20 SEO seed keywords based on your Ideal Customer Profile (ICP). Save time, increase accuracy, and scale your SEO research efficiently.
   
   Keywords:
   - SEO automation
   - n8n workflow
   - seed keyword generation
   - B2B SaaS SEO
   - Anthropic Claude API
   - AI-generated keywords
   - ideal customer profile
   - marketing automation
   - Claude Sonnet 3.5
   - n8n AI integration
   
   Third-Party APIs Used:
   - Anthropic Claude API (Claude Sonnet 3.5)
   
   Article:
   
   Automated SEO Seed Keyword Generation Using AI and n8n
   
   Search engine optimization (SEO) is an ever-evolving battle of visibility, strategy, and execution. One crucial foundation of any SEO campaign is identifying the right seed keywords — those essential terms that define the core of your content, guide backlinks, and frame your on-page strategies. But how do you choose 15–20 strategic keywords that align with your Ideal Customer Profile (ICP) — consistently and at scale?
   
   Introducing an automated approach using n8n, Claude Sonnet 3.5 (an AI model from Anthropic), and your brand’s ICP details.
   
   In this article, we’ll walk through how a custom-built n8n workflow streamlines the process of:
   
   - Analyzing your Ideal Customer Profile (ICP),
   - Leveraging a conversational agent AI to extract insights,
   - Generating 15–20 SEO-ready seed keywords,
   - And optionally, storing the results in your database, spreadsheet, or Airtable base.
   
   Let’s dive into this powerful automation.
   
   Understanding the Workflow Overview
   
   This n8n workflow is purpose-built to generate SEO seed keywords for a B2B SaaS product or service. At a high level, the steps are:
   
   1. You manually trigger the workflow;
   2. Define your Ideal Customer Profile (ICP);
   3. Aggregate the ICP data;
   4. Feed the data into Claude Sonnet 3.5 (Anthropic’s AI);
   5. Generate an array of 15–20 head term keywords;
   6. Parse and optionally send the keywords to a connected database or spreadsheet.
   
   Prerequisites
   
   To run this workflow successfully, you’ll need:
   
   - An operational instance of n8n;
   - Access to Anthropic’s Claude API (Sonnet 3.5 model preferred for cost-efficiency);
   - A defined Ideal Customer Profile (specific to your business or product);
   - (Optional) Destination storage like Google Sheets, Airtable, or a custom database.
   
   Step 1: Setting the Ideal Customer Profile
   
   Everything starts with a specific and well-articulated ICP. In the “Set Ideal Customer Profile (ICP)” node, you’re prompted to replace placeholders with accurate information:
   
   - Product Overview
   - Key Pain Points
   - Primary Goals/Objectives
   - Current Solutions
   - Customer Expertise Level
   
   This information reflects the types of problems your leads face, their interests, and how they might search for SaaS solutions.
   
   Step 2: Aggregating ICP Data
   
   The “Aggregate for AI node” combines your ICP inputs into one structured output. This ensures the downstream AI node receives a consolidated data payload — no missing fields, no formatting issues.
   
   Step 3: Conversational AI Analysis
   
   At the core of this workflow is the “AI Agent” connected to Anthropic’s Claude Sonnet 3.5 via the “Anthropic Chat Model” node. This AI model is given a detailed prompt, including specific SEO rules such as:
   
   - Generate head keywords relevant to the ICP’s journey;
   - Balance specificity and breadth;
   - Include varying searches: informational, transactional, commercial;
   - Avoid vague or hyper-competitive terms;
   - Think about related technologies, integrations, and pain-specific phrases.
   
   The agent responds in a structured JSON format with two main keys:
   
   - thoughts: A self-reflective reasoning summary as it generates keywords;
   - answer: The final curated array of 15–20 SEO-ready seed keywords.
   
   Cost wise, each AI run is relatively cheap — approximately $0.02–$0.05 per workflow execution using Claude 3.5.
   
   Step 4: Parsing and Storing Output
   
   Once AI outputs the array, the “Split Out” node breaks apart each keyword from the returned array. You can then route these into your own database, Google Sheet, or Airtable for further manual refinement or direct campaign integration.
   
   A “NoOp” node placeholder helps indicate where to connect your preferred data destination.
   
   Customization Continues
   
   The workflow is designed modularly, so it’s developer-friendly and easily extendable. Add logic to define geographic specifics inside the ICP, reroute data to a CMS, or even change the AI model with ease.
   
   Why Use This Workflow?
   
   - Speed: Drastically cut research time from hours to seconds.
   - Depth: AI considers context, the buyer journey, and even industry trends.
   - Accuracy: Structured, rule-based prompts help eliminate guesswork.
   - Scalability: Generate new keyword lists for multiple ICPs consistently.
   
   Final Thoughts
   
   This AI-powered seed keyword generation workflow doesn’t just automate a tedious marketing task — it gives you a scalable framework for smarter SEO decisions. Whether you’re an early-stage founder, SEO strategist, or digital marketing agency, automating this part of your keyword research helps you stay ahead in a noisy content landscape.
   
   And best of all? It’s open-source and fully customizable through n8n.
   
   So start saving time, driving strategy, and building keyword lists that actually convert — powered by AI.
   
   Try it today with Claude + n8n.
   
   —
   
   If you need help extending this workflow (e.g., integrating Airtable or handling multiple ICPs in a batch), drop a question into the n8n community forums or reach out to your backend engineer.
   
   Happy automating! 🚀

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.