AI Product Categorization
This guide will help you launch AI categorization to achieve consistently high accuracy and minimal manual adjustments even with a large catalog.
Key Idea
AI delivers the best results when products have high-quality names, logical attribute structure, and pre-cleaned "noise" in the content.
1) When to Use AI Categorization
- Need to quickly process a large new catalog or new supplier.
- Manual categorization takes too much team time.
- Regular product updates require a stable process without "bottlenecks".
- Preparation for Google Merchant: important to reduce the share of incorrect categories.
2) Preparing the Catalog Before Launch
- Clean up names: remove duplicates, service symbols, technical "noise".
- Check the description: 1–2 clear sentences about purpose and features.
- Normalize key attributes (brand, model, series, product type).
- Divide complex groups (auto/electronics/accessories) into separate launch batches.
If there is a lot of "noise" in the names, AI starts to confuse compatibilities and "universal" positions — accuracy drops.
3) Launch Runbook
Run AI on a sample of 100–200 products.
Check accuracy and manually correct the most common types of errors.
Establish verification rules for the team (what must be checked).
Run AI on the next part of the catalog and repeat a brief check.
After stabilization — transition to the full catalog and regular mode.
4) Quality Control: What to Check
Risk Groups
- Similar names
- Universal compatibilities
- Multi-model positions
Category Accuracy
- Check not only the top level
- Control the final subcategory
New Suppliers
- First batches — manual check
- Names often differ from historical data
Stability After Updates
- After mass changes — re-audit the sample
5) Common Errors and How to Fix
Problems → Solutions
- Unclear names → add a key product type ("LED headlight", "charging block", "case").
- Universal description → specify application/compatibility/parameters.
- Mixed products in one group → split the launch batch into separate categories.
- Rare specific items → manually assign a category and use as an example for future checks.