Getting Started with Taxonomy Matcher

Before You Start

You'll need your product data in CSV format. The required columns are:

• id — a unique identifier for each product
• title — the product name
• description — a text description of the product

Use semicolons (;) as the delimiter. Here's a minimal example:

id;title;description
101;Organic Cotton T-Shirt;Soft, breathable crew-neck t-shirt made from 100% organic cotton. Available in black, white, and navy.
102;Wireless Noise-Cancelling Headphones;Over-ear headphones with active noise cancellation, Bluetooth 5.0, and 30-hour battery life.
103;Cast Iron Skillet 12 inch;Pre-seasoned cast iron skillet suitable for stovetop, oven, and campfire cooking.

Better descriptions lead to better matches. A title like "Widget X-500" with no description gives the AI very little to work with. Adding details like "stainless steel kitchen timer with magnetic back and loud alarm" makes a significant difference.

For more detail on formatting, see the CSV formatting guide.

Step 1: Upload Your Data

Go to the Matcher page and choose how to input your data:

• Paste CSV data directly into the text area — useful for quick tests or small batches
• Upload a CSV file — better for larger datasets

The system will parse your data and show you a preview of the products it found.

Step 2: Choose a Taxonomy

By default, Taxonomy Matcher uses the Google Product Taxonomy — a hierarchy of 6,000+ categories maintained by Google. This is the right choice if you're selling through Google Shopping, or if you need a general-purpose category system.

If you sell on a specific marketplace (Amazon, Otto, etc.) or use your own internal categories, you can upload a custom taxonomy as a .txt file. Each line should be one category path, with levels separated by >:

Electronics > Computers > Laptops
Electronics > Computers > Desktops
Electronics > Audio > Headphones

See the custom taxonomy guide for formatting details.

Step 3: Configure Options

Before starting, you can optionally enable:

• Hierarchical categorization — narrows down categories level by level for better accuracy (recommended for large taxonomies)
• AI image generation — generates product images from descriptions using Gemini AI
• Title and description optimization — suggests improved product text for SEO

Each option consumes credits.

Step 4: Run the Matcher

Click Start Matching. The AI processes each product, and you'll see real-time progress as categories are assigned.

Processing time depends on the number of products and options enabled. A batch of 100 products with standard matching typically takes 1-2 minutes.

Step 5: Review and Export

Once processing completes, you'll see results in a table showing each product alongside its matched category and confidence score.

From here you can:

• Download as CSV — for importing into your feed management tool, Shopify, WooCommerce, etc.
• Download as JSON or XML — for programmatic integration
• View on your Dashboard — access previous results anytime under your match history

Results are saved to your account, so you can come back to them later without re-running the match.

Tips for Better Results

• Write descriptive titles. "Blue Widget" is hard to categorize. "Bluetooth Wireless Speaker, Portable, Waterproof, 10W" is easy.
• Include key attributes in descriptions. Material, intended use, target audience, and product type all help the AI make accurate decisions.
• Start with a small test. Try 10-20 products first to verify accuracy before processing your full catalog.
• Use hierarchical matching for taxonomies with many categories — it consistently produces more specific results.