The Old Way: Manual Categorization
For years, businesses relied on human teams to manually assign products to categories. This often involved:
- Spreadsheets and rule lists.
- Subject matter experts making judgment calls.
- Significant time investment, especially for large or frequently changing catalogs.
- Inconsistencies due to human error or differing interpretations.
While manual effort allows for nuanced understanding, it struggles to scale effectively and maintain consistency.
The New Way: AI-Powered Matching
Artificial intelligence, particularly Natural Language Processing (NLP), has revolutionized product categorization. AI models can:
- Understand Context: Analyze product titles and descriptions to grasp the product's essence.
- Learn Patterns: Identify relationships between product attributes and category structures.
- Process at Scale: Categorize thousands of products far faster than human teams.
- Maintain Consistency: Apply the same logic across the entire catalog, reducing subjective errors.
- Adapt: Learn from feedback and adapt to evolving taxonomies.
Why AI Wins for Most Businesses
- Speed & Efficiency: AI dramatically reduces the time and cost associated with categorization.
- Scalability: Easily handles catalogs of any size, from hundreds to millions of products.
- Accuracy & Consistency: Reduces human error and ensures uniform application of category rules.
- Adaptability: Can be retrained or fine-tuned for new product types or taxonomy changes.
While human oversight might still be valuable for quality control or highly ambiguous products, AI provides a powerful foundation for modern product categorization. Tools like Taxonomy Matcher bring this power to businesses of all sizes.