Filtering and Categorizing Data Automatically with n8n

Sometimes the real problem isn’t collecting data, it’s sorting through the noise. That’s exactly what this client was struggling with.

The Goal

They needed a simple but reliable way to pull quotes from an external API, categorize them as either team-related or personal, clean up the data, and send everything to the right Google Sheet, without having to touch it manually.

The Problem

Up until then, they were doing everything by hand. Pulling data, checking each quote, deciding which sheet it should go to, and then copying it over. It worked… but it was painfully slow and easy to mess up.

The Approach

I built an automated flow using n8n.The process starts when the workflow is triggered. It fetches data via an HTTP Request, filters and classifies quotes based on certain keywords, then routes them to either team or personal paths. After a quick data cleanup, each quote lands in the correct Google Sheet.

Tools I Used

n8n for automation
HTTP Request node
IF condition for classification
Merge and Edit Data nodes for data processing
Google Sheets for organized storage

Challenges & Fixes

One of the tricky parts was making the classification consistent, especially with different quote formats. I refined the filtering logic and added a clean-up step to make sure only accurate data goes into the sheet.

The Result

What used to take them hours now happens in seconds with one click. The client told me they finally felt “in control” of their data instead of buried under it.

Who This Helps

This kind of automation fits perfectly for content teams, marketing agencies, community managers, or anyone who works with incoming data that needs sorting and storing fast.

If you're tired of sorting data manually, I’d be happy to help you build something that works while you focus on the bigger stuff.

💬 I’d love to hear your thoughts or collaborate on similar workflows.

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