This article provides a complete, practical walkthrough of the Code Extractfromfile Automation 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:
   Automated Amazon Ads Optimization with AI using n8n and GPT-4
   
   Meta Description:
   Discover how to fully automate your Amazon Ads performance analysis and campaign optimizations using an n8n workflow powered by OpenAI’s GPT-4, Google Drive, and Gmail. Better targeting, smarter bidding—automated.
   
   Keywords:
   Amazon Ads, n8n workflow, automation, GPT-4o, OpenAI, Google Drive, Gmail, campaign optimization, marketing automation, eCommerce advertising, ad performance analysis, PPC automation, keyword bidding, ad targeting
   
   Third-party APIs Used:
   
   1. Google Drive API – to retrieve and download ad reports.
   2. Gmail API – to send email summaries and optimizations.
   3. OpenAI API – via Langchain integration for advanced language model analysis (GPT-4o).
   4. Amazon Ads Console – indirectly via its emailed reports (note: optionally, the Amazon Ads API can be integrated directly).
   
   —
   
   Article:
   
   Automating Amazon Ads Optimization with AI and n8n
   
   In a world where advertising speed and performance matter more than ever, automation is becoming the secret weapon for marketing teams. Amazon advertisers, in particular, wrestle with vast volumes of campaign data—from search terms to budget spend—just to stay competitive. Enter n8n: a powerful automation platform made even stronger by the fusion of GPT-4 insights and real-time data analysis.
   
   This article explores a powerful n8n workflow designed to automate Amazon Sponsored Products ad optimization—saving users hours of manual labor and delivering AI-powered recommendations daily without lifting a finger. Powered by Google Drive, Gmail, and OpenAI’s GPT-4o, the system acts as a virtual campaign manager. Let’s dive into how it works.
   
   Step 1 – Gather the Amazon Ads Reports
   
   The workflow is built around Amazon’s standard Sponsored Products reports, generated via the Amazon Ads Console. You'll need to schedule the following five reports, all covering a 30-day window:
   
   - Search Term Report (Detailed)
   - Targeting Report (Detailed)
   - Campaign Report (Summary)
   - Placement Report (Summary)
   - Budget Report (Summary)
   
   These can be emailed to yourself and uploaded manually or filtered via automation into Google Drive. The workflow watches a designated folder for uploads of .xlsx or .csv file formats. Filenames must follow a predictable pattern with keywords such as “search_term” or “campaign” to be classified correctly.
   
   Step 2 – Smart File Extraction and Data Formatting
   
   Once files are detected in the folder, n8n performs several checks:
   
   - Identifies whether files are .xlsx or .csv based on filename.
   - Extracts data from each file type accordingly.
   - Preserves the original filenames for classification.
   - Merges and categorizes the data using intelligent JavaScript logic to map files to one of five key reporting categories:
     - search_terms
     - campaigns
     - targeting
     - placement
     - budgets
   
   The formatting step is designed to clean and structure the data consistently, preparing it for AI analysis in a JSON-ready structure.
   
   Step 3 – AI-Powered Campaign Analysis with GPT-4o
   
   Here’s where the magic happens. The cleaned datasets are sent directly to a prompt-driven OpenAI GPT-4o language model, which is configured with precise system instructions via Langchain’s integration nodes in n8n.
   
   GPT-4o is instructed to analyze campaign performance across each dimension and return:
   
   - Campaign-level bid adjustments, budget scaling suggestions, ACoS/ROAS estimates, and spend/sales projections.
   - New keyword recommendations (at least five) with exact match and suggested bids, sorted by campaign and ad group.
   - At least three negative keywords to avoid wasted spend.
   - Targeting suggestions such as pausing underperforming placements or increasing bids on high-return targets.
   
   Critically, the output is returned in JSON (not plain text), allowing for seamless downstream automation.
   
   Step 4 – Email the Optimization Instructions
   
   Once the AI response is received and parsed, n8n generates an automated, formatted email summarizing the findings. Key highlights include:
   
   - Total projected daily spend and sales if recommendations are implemented.
   - Campaign-level insights: bid multipliers, placement adjustments, and budget actions.
   - Keyword additions and negatives in context.
   - Suggested targeting tweaks with bid modifiers.
   - ACoS and ROAS calculations per campaign.
   
   This email is sent automatically using Gmail API credentials, delivering a daily dose of optimization guidance that’s both data-driven and fully automated.
   
   Optional Expansion – Amazon Ads API Integration
   
   While the current build depends on reports delivered via email, it includes sticky notes suggesting a high-value upgrade: applying for a developer account to access the Amazon Advertising API. This would allow:
   
   - Auto-generation of reports via API.
   - Direct download and parsing of .gzip report payloads.
   - Full elimination of manual upload or Drive folder dependencies.
   
   With this enhancement, marketers could achieve end-to-end automation—self-healing daily workflows with no human involvement.
   
   Conclusion: Smarter Ads at Scale
   
   This n8n workflow creates a powerful bridge between raw ad data and intelligent campaign management. By embedding GPT-4o into the reporting loop, advertisers unlock massively scalable insights—not just what happened, but what to do next.
   
   Even for non-developers, the visual flow offers intuitive steps to ingest, clean, analyze, and react to Amazon ad performance daily. It saves time, adds precision, and creates a unique competitive edge.
   
   If you’re managing Sponsored Products at scale and tired of reactive optimization, this workflow is your roadmap to proactive AI-powered marketing. Automation. Intelligence. Performance—on autopilot.
   
   —
   
   Want help setting up this workflow or customizing it for your use case? Contact us or explore more AI-integrated automations at n8n.io.

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.