03/18/2026
How I Categorized 28,000+ URLs: A Lesson in Scale and Strategy
Managing a few hundred URLs is a task. Managing 28,000+ URLs for a single project is an entirely different beast.
Recently, I took on the challenge of restructuring and categorizing a massive dataset of over 28,000 URLs for a large-scale website. The goal was to improve site architecture, enhance crawlability, and ensure a seamless user journey.
How I approached the task: To tackle this without losing my mind (or accuracy), I moved away from manual sorting and leveraged a mix of Python automation and Advanced Google Sheets filtering. By using scripts to identify patterns in slugs and metadata, I was able to bucket the majority of the URLs into logical categories. The final 10% required a "human-in-the-loop" approach to ensure high-intent pages were perfectly aligned with the new site structure.
3 Key Learning Points from this project:
1️⃣ Automation is a Necessity, Not a Luxury: When dealing with 28k+ data points, manual work is the enemy of consistency. Using Python scripts to automate the heavy lifting saved weeks of manual labor and eliminated human error in repetitive tasks.
2️⃣ Data Integrity Drives SEO: A clean URL architecture is the backbone of Technical SEO. Categorizing these URLs wasn't just about organization; it was about helping search engines understand the site's hierarchy, which directly impacts indexing and rankings.
3️⃣ Scalability Requires Systems: You can't wing a project of this size. I learned that building a repeatable "Categorization Framework" first—defining rules for parent/child categories—is more important than the actual sorting process itself.
Working on large-scale data challenges like this reminds me why I love the intersection of Digital Marketing and Technical Ex*****on. It’s where strategy meets scalability.
Have you ever managed a massive website migration or audit? What was your biggest takeaway? Let’s drop your experience in the comments! 👇
