Categorization and Tagging

Categorization and Tagging

Proper categorization improves both AI retrieval accuracy and customer self-service browsing.

Category vs. Tag

Categories are hierarchical and exclusive. An article belongs to one category. Tags are flat and non-exclusive. An article can have multiple tags.

Example:

• Category: Billing > Invoices
• Tags: payment, receipt, PDF, download, tax

Building Your Taxonomy

Start with a customer-centric taxonomy based on what customers are trying to do:

Tier 1 (Top-Level Categories) Keep to 5-8 maximum. More creates decision fatigue.

Tier 2 (Subcategories) 2-6 per top-level category. Only create subcategories when a top-level category exceeds 15 articles.

Example taxonomy:

Account
  ├── Login & Security
  ├── Profile Settings
  └── Team Management
Billing
  ├── Plans & Pricing
  ├── Invoices
  └── Refunds
Product
  ├── Dashboard
  ├── Integrations
  └── API

Tagging Strategy

Use these tag types:

• Feature tags: dashboard, API, widget, reports
• Action tags: setup, configure, troubleshoot, migrate
• Audience tags: admin, agent, developer, end-user
• Status tags: new-feature, deprecated, beta

AI Retrieval Impact

Good categorization improves AI chatbot accuracy because:

1. The AI can narrow search scope to relevant categories
2. Related articles surface as follow-up suggestions
3. Confidence scores increase when matches are category-specific

Maintenance Rules

• Review taxonomy quarterly as your product evolves
• Merge categories with fewer than 3 articles
• Split categories with more than 20 articles
• Audit tags monthly — remove unused tags and consolidate synonyms
• Assign a category owner responsible for accuracy

Mapping Customer Language

Customers rarely use your internal terminology. Create a synonym map:

Add these synonyms as tags to improve AI matching.

Next up: How to measure whether your knowledge base is actually working.