Frost & Sullivan released the white paper, which finds that China's e-commerce market has entered a 3.0 stage driven by algorithms and AI. Online retail sales approached RMB 16 trillion in 2025. As user growth slows, attention fragments, and content supply expands, brand growth increasingly depends on whether algorithmic systems can see, understand, and consistently select a brand. Platforms now use natural-language and vector-based understanding to interpret consumer tasks, shifting shopping journeys from keyword search toward conversational interaction and delegated execution by AI agents.
The white paper traces the evolution from shelf-based search e-commerce (1.0) and content-driven interest e-commerce (2.0) to AI-powered algorithmic e-commerce (3.0). Platforms first determine what deserves distribution, then identify the appropriate audience, and finally compete on transaction efficiency. Six operating signals - product, content, behavior, transaction, service, and brand - create a continuous learning loop. Brands therefore need machine-readable, cross-verifiable, and continuously updated product knowledge and evidence systems built around semantic relevance, data consistency, and source authority.
For implementation, Zhixing Consulting proposes the SCIEN scientific marketing framework. Scope identifies priority consumer tasks and entry products; Coding converts differentiation and evidence into algorithm-readable expressions; Inflow builds strong brand characteristics across multiple entry points; Engagement develops segment-specific communications; and Network strengthens organizational coordination. The framework supports six capabilities - product, content, data, service, brand, and organization - helping brands move beyond short-term traffic and content production toward stronger cognitive efficiency, knowledge assets, and long-term operating capabilities.
