How to Optimize Workflows in n8n - Faster & Scalable Automations

Overview

In this lesson, you will learn practical techniques to optimize your n8n workflows, making them faster, more efficient, and scalable. Through a real-world example of processing customer feedback, you’ll see how to identify bottlenecks in an unoptimized workflow and then apply optimization strategies such as reducing redundant nodes, using parallel processing, minimizing API calls, and smartly handling loops and merges.

Why Optimize Your n8n Workflows?

Optimizing workflows is crucial for:

• Improving execution speed
• Reducing resource consumption
• Enhancing scalability for larger datasets
• Lowering API call costs and limits usage

Each node in n8n represents a step in your automation. More nodes and inefficient logic mean longer runtimes and potentially higher operational costs. Understanding how to manage credentials and API calls effectively, as explained in our n8n API, Collaboration & Credential Management lesson, can also help reduce overhead and improve security.

Key Optimization Tips for n8n Workflows

1. Remove Redundant Nodes

• Audit your workflow to eliminate unnecessary steps.
• Each node adds processing time; fewer nodes mean faster execution.
• Consolidate logic where possible (e.g., combine multiple similar operations into one node or use sub-workflows).

2. Use Parallel Processing

• If tasks are independent, run them simultaneously rather than sequentially.
• Example: Sending Slack messages, Notion updates, and Airtable entries can be branched out to run in parallel.
• Remember n8n executes branches from left to right, top to bottom — reorder branches to control execution priority.

3. Minimize API Calls

• Use bulk or batch API endpoints whenever possible.
• Instead of updating records one-by-one, send batches to reduce the number of requests.
• Example: Airtable’s batch API lets you update multiple records in a single call.
• For more details on making efficient HTTP requests, refer to the HTTP Request Node in n8n and the official n8n HTTP Request node documentation{:target="_blank"}.

4. Handle Loops and Merges Efficiently

• Avoid redundant looping over large datasets.
• Use merge nodes to combine datasets smartly instead of fetching or updating records repeatedly.
• Use code nodes to aggregate or summarize data before sending notifications or updates.

Practical Example: Optimizing a Customer Feedback Workflow

You will compare an unoptimized and an optimized workflow for processing customer feedback.

Workflow Scenario

• Daily batch of customer feedback entries is received.
• For each entry:
  • Lookup the customer in CRM.
  • Add a note to their record.
  • Send a thank-you email.
  • Notify support if rating is below 3.

Unoptimized Workflow Breakdown

1. Fetch feedback entries from Google Sheets.
2. Loop over each feedback entry (e.g., 100 items).
3. For each item:
   • Fetch customer record individually.
   • Update customer feedback in Airtable.
   • Send a thank-you email.
   • Evaluate rating and alert support if rating < 3.

Issues:

• Each API call runs per feedback item, causing hundreds of iterations.
• Sequential processing of independent notification nodes.
• Multiple alerts sent for each low rating instead of one combined alert.

Node Execution Count

• For 100 feedback entries, node executions can exceed 400+ due to repeated API calls and loops.

Optimized Workflow Breakdown

1. Fetch all feedback entries at once.
2. Fetch all customer records once.
3. Merge datasets on the email field using the Merge node.
4. Update customer feedback records (still individually in this example, but can be optimized further with batch API).
5. Send personalized thank-you emails (must remain per customer for personalization).
6. Filter low ratings (< 3), then aggregate alerts into a single message using a Code node.
7. Send one support team alert instead of multiple alerts.

Step-by-Step Guide to Build the Optimized Workflow

1. Fetch Feedback and Customer Data

• Use Google Sheets node to get all customer feedback.
• Use Airtable or CRM node to fetch all customer records at once.

// Example: Google Sheets node settings
{
  "resource": "sheet",
  "operation": "read",
  "sheetId": "your-sheet-id",
  "range": "Feedback!A1:F100"
}

2. Merge Feedback with Customer Records

• Add a Merge node.
• Set mode to "Merge By Key".
• Use the common field, e.g., email, to join datasets.

// Merge node example settings
{
  "mode": "mergeByKey",
  "keys": ["email"]
}

For more details on the merge node, check the n8n Merge node documentation{:target="_blank"}.

3. Update Customer Feedback

• Use an Airtable or your CRM's update node.
• Ideally, use batch API to update multiple records in one request.
• If batch API is not available, update records one-by-one.

4. Send Personalized Thank-You Emails

• Use Gmail or Send Email node.
• Loop over each merged item.
• Use expressions to personalize email content:

Subject: Thank you for your feedback, {{$json["name"]}}!
Body: Dear {{$json["name"]}}, thank you for your feedback on {{$json["product"]}}.

5. Filter Low Ratings and Aggregate Alerts

• Use a Filter or IF node to find ratings less than 3.
• Use a Code node to combine all low-rating feedback into a single message.

// Example code node to aggregate alerts
const feedbacks = items.map(item => item.json);
const summary = feedbacks.map(fb => `Customer: ${fb.name}, Rating: ${fb.rating}, Comment: ${fb.comment}`).join('\n');
return [{ json: { summary: `Low Rating Alerts:\n${summary}` } }];

6. Send One Support Alert

• Use Slack or email node to send the aggregated alert message.
• This approach reduces the number of API calls and notification noise significantly.

For workflows involving AI-driven responses or sentiment analysis on feedback, consider integrating with OpenAI APIs as shown in our AI Automation with n8n and OpenAI lesson.

Common Mistakes and Troubleshooting

Mistake 1: Looping Over Each Item Without Batching

• Avoid looping over each item to perform API calls.
• Instead, fetch/update data in bulk or merge datasets first.

Mistake 2: Sequential Execution of Independent Tasks

• Place independent tasks (e.g., notifications) on separate branches for parallel execution.
• Remember execution order is left to right, top to bottom.

Mistake 3: Sending Multiple Alerts Instead of One

• Use code or aggregate nodes to combine multiple alerts into a single notification.
• This reduces API calls and notification noise.

Troubleshooting Tips

• Check node execution counts in n8n to identify bottlenecks.
• Use the "Execute Node" feature to test individual nodes.
• Validate your merge keys carefully to avoid mismatched data.
• Monitor API rate limits for external services when making many calls.

Summary of Optimization Principles

Additional Resources

• n8n Merge Node Documentation
• n8n Looping and Batching Guide
• n8n HTTP Request node documentation

Quick Reference Cheat Sheet

By applying these optimization strategies, your n8n workflows will run more efficiently, handle larger data volumes gracefully, and reduce operational overhead. As shown in the video above, even simple changes like merging datasets and batching API calls can halve the number of node executions and improve performance significantly.