Why X‑type vs Y‑type Product Categorization Matters for E‑Commerce User Experience

At the end of last year, XunKong published an article on Tiger Hoo titled "What’s the Difference Between JD.com and Taobao’s Product Categorization?" that highlighted the contrast between X‑type classification (based on product attributes) and Y‑type classification (based on user tags). After reading it, the author, who evaluates user experience for JD.com’s categorization, raised several questions about which users use categories, what classifications satisfy their search needs, and whether X‑type or Y‑type classifications are still suitable in today’s information‑rich environment.

Which users use categorization?

What kind of categorization meets users' search requirements?

Is X‑type classification outdated for the era of information explosion and upgraded consumer expectations?

Can Y‑type classification assist users in finding products?

The core issue is how to structure product categories so that users will actually purchase.

User Paths to Finding Products

Before answering the above questions, we must first consider the usage rate of categorization, which starts with how users look for products.

As online shoppers become more experienced and e‑commerce platforms expand their product assortments, users increasingly rely on search and personalized recommendations, reducing the reliance on category navigation.

Designing Product Categories from User Scenarios

We identified three main user scenarios for category navigation:

Scenario 1 – Fuzzy Selection

Users unfamiliar with a product line (e.g., women looking for office electronics) use categories to quickly locate a relevant product family before further filtering. A clear X‑type classification complemented by a moderate amount of Y‑type classification can aid discovery.

Scenario 2 – Precise Search

Veteran JD.com users who know the site’s taxonomy rely on categories for accurate, high‑precision searches. Precise X‑type categories combined with exact backend SKU paths improve the search experience.

Scenario 3 – Casual Browsing

When users have no specific purchase intent, they browse categories for inspiration or promotions. In this case, X‑type categories are less attractive, and Y‑type classifications can capture attention.

In summary, combining X‑type and Y‑type classifications based on user scenarios satisfies diverse search needs. Standard products benefit from clear X‑type navigation, while non‑standard items should emphasize Y‑type operational tactics.

Common Category‑Operation Misconceptions

Category operation must balance multiple factors:

User side: users' mental models and shopping habits.

Business side: product development status, industry environment, market potential.

Platform side: overall category strategy and roadmap.

Thus, category architecture is a product shaped by these considerations, and decisions often involve trade‑offs.

1. Category Exposure: Full Catalog vs. Highlighted Best‑Sellers

Limited navigation space forces a choice between displaying all categories to build awareness or focusing on a few high‑potential items. Early stages favor full exposure; later stages benefit from deep‑dive promotion of best‑sellers.

2. Category Dimension Setting: Comprehensive vs. Optimized

Backend SKU structures must be comprehensive, but the front‑end category display should prioritize relevance. For example, a “regional specialty” category can be organized by popular provinces rather than broad regions, leading to better user engagement.

3. Virtual Business Operations: Category Thinking vs. Platform Thinking

Virtual services should be linked to related physical categories (e.g., sports equipment and sports services) while also being unified under a platform‑wide virtual category to enhance overall perception.

Improving Category Operation Effectiveness

Key tactics include:

Annual/quarterly category planning to identify strengths, weaknesses, and high‑potential areas, adjusting strategies accordingly.

AB testing to validate which category dimensions drive better traffic and conversion.

Regular category diagnostics through competitor analysis and monthly data monitoring to uncover hidden issues.