This article provides a complete, practical walkthrough of the Splitout Aggregate Automate 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:  
   Automating SEO Research: Using AI to Generate B2B Seed Keywords in n8n
   
   Meta Description:  
   Discover how to automate SEO keyword generation using n8n and AI for B2B SaaS businesses. This no-code workflow transforms your Ideal Customer Profile (ICP) into actionable seed keywords using Anthropic’s Claude and LangChain.
   
   Keywords:  
   B2B SEO automation, seed keyword generation, n8n workflow, AI SEO tools, Claude Sonnet 3.5, LangChain n8n, SaaS marketing automation, ICP based SEO, Anthropic API, AI keyword research
   
   Third-Party APIs Used:
   
   - Anthropic Claude (via LangChain LangModel)
   - LangChain for AI agent orchestration
   - Optional: Airtable, Google Sheets, or other databases for exporting results
   
   Article:
   
   Automating SEO Keyword Research: How to Generate 20 Seed Keywords for B2B SaaS Using n8n and AI
   
   Success in Search Engine Optimization (SEO) often begins with identifying the right set of seed keywords – the core terms that reflect what your ideal customers are searching for. For B2B SaaS companies, these keywords form the foundation of a long-term content and SEO strategy. But instead of manually brainstorming them or relying on generic keyword tools, what if you could automate this process using artificial intelligence?
   
   Thanks to n8n, a powerful open-source workflow automation tool, and cutting-edge AI models like Claude from Anthropic, it’s now possible to generate tailored, data-informed seed keywords automatically. This custom n8n workflow showcases how you can convert your Ideal Customer Profile (ICP) into a curated list of 15–20 strategic seed keywords.
   
   Let’s break down how it works.
   
   🧠 Why Seed Keywords Matter for B2B SEO
   
   "Seed keywords" are the cornerstone of your keyword strategy. These high-level topics are essential because:
   
   - They define your topical authority
   - They're used to expand into long-tail keywords
   - They guide your content and marketing roadmaps
   
   In B2B, selecting the right seed terms takes a nuanced understanding of buyer pain points, goals, and industry vocabulary — exactly the kind of information that lives inside your ICP.
   
   This makes the ICP the perfect input for AI-driven keyword generation.
   
   ⚙️ Workflow Overview: From ICP to AI-Generated Keywords
   
   This workflow in n8n is designed to be run manually when needed and includes the following steps:
   
   1. Trigger Input Manually  
      The process starts with a manual trigger. This allows you to run the keyword generation as needed — perhaps after refining or updating your ICP.
   
   2. Enter the Ideal Customer Profile  
      A Set node collects ICP details. You must define:
   
      - Product or service you offer
      - Customer pain points
      - Customer goals
      - Current solutions the customers use
      - Their level of expertise
   
      Example:
      - Product: “Sales automation platform for B2B startups”
      - Pain points: “High churn, inefficient cold outreach”
      - Goals: “Shorten sales cycle, increase demo bookings”
      - Current solutions: “CRM plus cold email tools”
      - Expertise level: “Intermediate”
   
   3. Aggregate the ICP Inputs  
      The data is aggregated into a unified JSON block using the Aggregate node — ready to be fed into an AI model.
   
   4. AI Agent Analyzes the ICP  
      A LangChain Agent node communicates your request to the AI model. It does the heavy cognitive lifting by:
   
      - Understanding the ICP thoroughly
      - Following detailed keyword generation rules
      - Producing 15–20 SEO-ready keyword ideas
   
      The AI considers a host of factors: industry trends, product relevance, buying stage, user intent (informational, transactional, etc.), and more. It outputs the keywords in lowercase, cleanly formatted strings.
   
   5. Output Is Structured and Stored  
      The result is passed to a Split Out node, which handles parsing the array of keywords for further use. You can then connect the output to your own:
   
      - Airtable
      - Google Sheet
      - SQL/NoSQL database
   
      This lets your team instantly access, review, and use the new seed keywords.
   
   🤖 AI Model & Cost Considerations
   
   This workflow uses Anthropic's Claude Sonnet 3.5 through LangChain. You’ll need an API key and account to connect to this powerful large language model (LLM). The estimated API cost per use is around $0.02–$0.05, making it extremely efficient for its strategic value.
   
   📋 Rules for Better Keyword Output
   
   The prompt given to the AI agent includes 13+ detailed rules to ensure actionable keywords. These rules help avoid poor outputs like general phrases ("software") and optimize for:
   
   - Clarity and relevance to ICP
   - Balance between head terms and niche queries
   - Coverage across awareness and decision stages
   - Usage of customer language and industry lingo
   - Location targeting and emerging industry trends 
     
   These rules are what give this workflow an "SEO strategist in a box" feel.
   
   📤 Save or Reuse the Ideas
   
   Once exported to a database or spreadsheet, you can:
   
   - Validate keywords with tools like Ahrefs or SEMrush
   - Group keywords into content clusters
   - Use them in paid ad campaigns
   - Share with content writers or SEO teams
   
   You can even schedule this workflow to auto-run weekly or with every ICP update, creating an evolving SEO strategy that keeps pace with your audience’s needs.
   
   🛠️ Customization and Extensibility
   
   Aside from plugging in your AI API key and database, you can customize:
   
   - The number of keywords generated
   - Prompt structure and rules
   - Type of AI model (OpenAI GPT models are supported too)
   
   Need real-time ICP data? You can connect n8n to your CRM (HubSpot, Salesforce) or Airtable to automatically pull ICP records.
   
   💡 Final Thoughts
   
   This low-code/no-code AI-powered flow empowers marketers, product teams, or founders to move past guesswork in SEO. With just a detailed customer persona and a few clicks, you get battle-tested keyword ideas ready to fuel your content planning, performance marketing, and website optimization.
   
   The future of SEO tools is programmable and personal — and it’s already here.
   
   📎 TL;DR
   
   - 🛠 Tool: n8n + LangChain + Claude AI
   - 🎯 Input: Ideal Customer Profile (ICP)
   - 🔑 Output: 15–20 SEO “seed” keywords for B2B SaaS
   - 💵 Cost: ~$0.02–$0.05 per run
   - ☁️ Export: Connect to Airtable/Sheets/DB
   
   Start turning intelligence into action — one prompt at a time.

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.