Taobao Overhauls Search Function with AI Upgrades

Deep News
Nov 12

On the evening of November 10, just hours before the "11.11" shopping festival, a leading domestic cosmetics brand in Shenzhen closely monitored data on Taobao’s merchant backend. An AI-generated report flagged that their "add-to-cart" volume was 2.3% below the platform average, prompting the AI assistant to recommend price adjustments and keyword optimizations.

Meanwhile, in Beijing, a top pet food company leveraged Taobao’s AI tool "Xiao Wan Assistant" to refine product keywords, incorporating trendy tags like "I-person pet owners" and "Gen Z." They also used AI-generated video tools to create content with themes like "Zelda-style" and "Pokémon ZA-style," driving a 35% year-over-year order increase.

These AI-driven transformations trace back to late 2024, when Taobao initiated a major AI overhaul. Alibaba assigned Zhang Kaifu (alias "Kaifu"), then head of Alibaba International’s AI division, to lead Taobao’s AI evolution. By December 2024, Taobao merged its ad algorithm team with search and recommendation teams under the newly formed "Search & Recommendation Intelligent Products Division" (SRIPD).

The urgency stemmed from user complaints about search inefficiencies, such as irrelevant clothing recommendations and repetitive suggestions. Kaifu’s team faced a dual challenge: upgrading legacy systems while maintaining business stability. "It’s like replacing the engine of a moving ship," Kaifu remarked.

**Core Upgrades**: 1. **Search & Recommendation AI**: Overhauling Taobao’s 22-year-old search infrastructure, including rebuilding its massive product database to be AI-compatible. An AI agent was deployed to automate product tagging, completing the task in six months by August 2025. 2. **AI Tools for Merchants**: Brands gained access to AIGC tools for content creation, with new features rolling out weekly. 3. **AI Shopping Guides**: Enhanced features like "AI-powered price comparisons" in existing tools such as "Pailitao."

**Testing & Deployment**: Taobao adopted a phased rollout, starting with 2% of users for A/B testing. Metrics like user retention and engagement prioritized over flashy AI demos. Cross-functional "super teams" reported directly to Kaifu, fostering innovation without rigid KPIs.

**Results**: By November 2025, AI-driven search improvements boosted ad ROI by 12%, search relevance by 20%, and recommendation click-through rates by over 10%. However, challenges remain, particularly in onboarding traditional merchants (e.g., furniture, hardware) to AI tools.

Alibaba continues to invest heavily in AI talent, targeting young graduates and expanding R&D collaborations with global AI experts. For Taobao, this marks just the beginning of a multi-year AI transformation.

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