This article provides a complete, practical walkthrough of the Splitout Code Import Webhook 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:
   Automate Google SERP Tracking for SEO with n8n and ScrapingRobot
   
   Meta Description:
   Learn how to automate Google search results (SERP) tracking using n8n and ScrapingRobot. This guide shows you how to retrieve keyword rankings, analyze organic results, and output structured SEO data—perfect for competition analysis and reporting.
   
   Keywords:
   n8n workflow, SEO automation, SERP tracking, Google Search automation, ScrapingRobot API, keyword ranking, SEO data pipeline, Google SERP parser, n8n SEO, automated SEO report
   
   Third-Party APIs Used:
   
   - ScrapingRobot: Used to retrieve SERPs (Search Engine Results Pages) from Google based on defined keywords.
   
   —
   
   Article:
   
   Automate Google SERP Tracking for SEO with n8n and ScrapingRobot
   
   If you're managing SEO at scale or analyzing ranking data across multiple keywords, manually checking Google results just doesn't cut it. That's where automation tools like n8n and ScrapingRobot come in. In this guide, we’ll explore how an n8n workflow seamlessly retrieves keyword-based search engine results from Google, assigns organic rankings to pages, and organizes the data for deeper SEO insights.
   
   Whether you’re tracking keyword rankings for your site, researching competitors, or comparing organic vs paid results—this automated solution saves time and provides structured, scalable data.
   
   What This Workflow Does
   
   This n8n automation workflow pulls Google search results for a list of specified keywords using ScrapingRobot, a scraping API. The workflow performs several key tasks:
   
   - Loops through a list of SEO keywords
   - Sends API queries to ScrapingRobot to fetch SERP data
   - Extracts organic results and filters empty entries
   - Assigns position numbers to each organic result
   - Outputs the formatted result to your database
   
   The result is a structured dataset where each keyword is mapped to its top-ranking pages and their exact positions in the Google SERP—including title, URL, and snippet.
   
   Let’s break down how this happens inside the workflow.
   
   Step-by-Step: How the Automation Works
   
   1. Initiating the Workflow
   
   The entry point is a Manual Trigger node ("When clicking 'Test workflow'") that kicks off the process either manually or via schedule (if desired).
   
   2. Keyword Sourcing
   
   You can define your SEO terms in two ways:
   - Connect to your existing keyword database (the node hint: “Connect to your own database – ”).
   - Use the built-in Set node titled “Set Keywords to get SERPs for” which contains a sample array like:
     ["constant contact email automation", "business workflow software", "n8n automation"]
   
   3. Keyword Splitting
   
   The “Split out Keywords” node iterates through each keyword, sending them one-by-one into the next stage of the workflow.
   
   4. Fetching Google SERP Data
   
   Each keyword is sent as a query to ScrapingRobot via the “GET SERP” node, using the GoogleScraper module. ScrapingRobot returns SERP data including:
   - Organic results (title, link, snippet)
   - Paid results (ads)
   - Related searches (People Also Ask)
   - Query summary
   
   Note: You’ll need your own ScrapingRobot API key configured in the authentication parameters of this node.
   
   5. Parsing SERP Results
   
   The next Set node (“SERP results”) extracts specific data points from the ScrapingRobot response:
   - organicResults (array)
   - searchQuery (string)
   - paidResults (optional)
   - peopleAlsoAsk (optional)
   
   6. Filtering and Cleaning Results
   
   The workflow splits the organic results into individual items with the “Separate” node. The following filter (“Title <> Empty”) ensures only valid results with a title are used— useful for filtering out irrelevant or malformed data.
   
   7. Assigning SERP Positions
   
   Position tracking is crucial for SEO. The included JavaScript code node (“Assign SERP #pos”) groups results by their related search query and correctly assigns a position number (1–10 or more) based on their order. This mirrors actual ranks on the Google results page.
   
   8. Final Output
   
   Finally, the workflow can be extended to write these results back to your database. The placeholder node “Connect to your own database2” represents the final step — where you’d likely push the structured data to Airtable, Google Sheets, or your internal SEO dashboard.
   
   Why Use This SEO Automation Workflow?
   
   - 🔍 SEO Tracking: Monitor the top-ranking URLs for each of your target keywords over time.
   - 🧠 Competitor Intelligence: Easily identify which websites rank highest and for which queries.
   - 📈 Ranking Reports: Build reports showing rank change, snippet features, ads, and more.
   - 🔁 Scalable Queries: Automate hundreds (even thousands) of keyword checks.
   
   You can also analyze monthly trends by comparing output datasets across time or run the workflow on a recurring schedule to maintain fresh rankings.
   
   Customization Ideas
   
   - Connect input keywords to Google Sheets or Airtable for dynamic keyword management.
   - Modify the result filtering to include only specific domains (e.g., your own or competitors).
   - Output data to CSV, JSON, or real-time dashboards.
   - Expand the workflow to include alerts when ranking drops/change significantly.
   
   Getting Started: Setup Requirements
   
   Before launching this workflow, you’ll need to configure:
   1. A ScrapingRobot account with a valid API key.
   2. An n8n instance, either self-hosted or via n8n.cloud.
   3. Your preferred data source and destination configured in the respective nodes.
   
   Final Thoughts
   
   By combining the low-code power of n8n with the robust scraping capabilities of ScrapingRobot, you can build a powerful SEO dataset—automatically. Whether you're optimizing your site or just out to beat competitors on SERPs, this workflow provides everything you need to scale your keyword tracking with precision.
   
   Built with simplicity and adaptability in mind, this workflow is a solid foundation for any data-driven SEO strategy.
   
   —
   
   Created by Simon @ automake.io | Automating Marketing Workflows Without Code

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.