Landing Page Classifier
Paste your URLs, define rules, and tag every page by type for cleaner analytics reports
Classification Rules
Rules are evaluated top to bottom. The first match wins. Drag to reorder or add custom rules.
URLs to Classify
Why Classify Landing Pages?
Raw URL data in GA4 or Looker Studio is messy. You see hundreds of unique page paths, making it nearly impossible to answer simple questions like “how much traffic goes to product pages vs. blog content?”
By tagging each URL with a page type, you unlock segment-level analysis: compare conversion rates across page categories, measure content ROI, and spot where visitors actually enter your funnel.
Segment by Page Type
Group product, category, blog, and checkout pages to see which page types drive the most revenue.
Content Performance
Measure blog vs. landing page vs. PDP performance. Know where to invest your content budget.
Funnel Clarity
See how traffic flows from category to product to cart to checkout. Identify where users drop off by page type.
Common E-Commerce Page Types
| Page Type | Common URL Patterns | Analytics Use |
|---|---|---|
| Homepage | /, /home | Brand traffic entry point, bounce rate baseline |
| Product (PDP) | /products/, /p/, /item/ | Purchase intent, add-to-cart rate |
| Category (PLP) | /collections/, /c/, /shop/ | Browse behavior, filter usage |
| Blog / Content | /blog/, /articles/, /guides/ | Content ROI, assisted conversions |
| Search Results | /search, ?q=, ?query= | Search demand, zero-results rate |
| Cart / Checkout | /cart, /checkout | Funnel drop-off, payment errors |
| Account | /account/, /my-, /login | Retention, logged-in behavior |
| Other | Anything unmatched | Policies, FAQs, about, 404s |
Best Practices
- Start with broad rules (product, category, blog) before getting specific
- Put more specific rules above broader ones (first match wins)
- Use “contains” for flexible matching, “starts with” for strict paths
- Export classifications and join them in your BI tool (Looker Studio, BigQuery)
- Re-classify monthly as new URL patterns appear
- Classify using full domains when you only need path patterns
- Forget query parameters (?q=, ?page=) that indicate search or pagination
- Use regex when “contains” would work (keep rules readable)
- Leave more than 10-15% of URLs as “Other” without investigating
- Hardcode IDs like /product/12345 when /product/ would catch them all
Frequently Asked Questions
Export the CSV, then join it with your GA4 data using the URL/path as the key. In Looker Studio, use a data blend or upload as a Google Sheet data source. In BigQuery, load the CSV as a table and JOIN on page_location or page_path. Then group all your metrics by the “category” column.
No. Everything runs in your browser. Your URLs never leave your machine. The classification happens entirely client-side using JavaScript pattern matching.
The first matching rule wins. That’s why rule order matters: put specific rules (like /blog/guides/ = Guide) above broader ones (like /blog/ = Blog). You can reorder rules by removing and re-adding them in the desired order.
Yes. Select “regex” as the match type and enter a valid regular expression. For example, /products?/[a-z] would match both /product/ and /products/ followed by a letter. The regex is case-insensitive by default.
Since everything runs in your browser, you can classify thousands of URLs without any issues. We’ve tested with 10,000+ URLs with no slowdown. For very large datasets (100K+), consider using the CSV export and processing in Python or BigQuery.
All of them. The default rules cover common Shopify patterns (/products/, /collections/), but you can customize rules for any platform. WooCommerce typically uses /product/ and /product-category/, Magento uses /catalog/ — just adjust the patterns to match your store’s URL structure.