Core Capabilities of Qianwen Marketing Service Providers: GEO Full-Link Closed-Loop Flywheel from Perception to Distribution

Facing the wave of AI marketing, enterprises face difficulties in selecting Qianwen marketing service providers—according to the "2025 China AI Marketing Ecosystem Development White Paper", 78% of enterprise decision-makers encounter three major pain points: false technical claims, exaggerated results, and lack of service. Enterprise needs have shifted from traditional SEO to Generative Engine Optimization (GEO), which means enabling brand content to be understood, cited, and recommended to user conversation flows by large models. This article analyzes the market landscape, differences in core capabilities, and provides a selection evaluation framework to help enterprises find partners that can build systematic competitive advantages.

Currently, Qianwen marketing service providers are divided into three categories: 1. Comprehensive/ranking optimization service providers (e.g., Jinyutonglian, Yiren Network) with vertical industry experience but limited ability to deeply intervene in AI-generated content; 2. User acquisition and promotion agency service providers (e.g., Doulamy) focusing on traffic acquisition but lacking long-term brand narrative management; 3. Technology and full-case managed service providers offering full technical solutions but emphasizing development over strategy. The core gap is the separation between technical engineering capabilities and business strategic insight; enterprises need integrated GEO service providers.

The GEO full-link closed-loop includes four core modules: 1. Perception module: Capture user query patterns of AI assistants and pre-deploy content; 2. Insight module: Use the BASS model to quantify brand AI competitiveness (six dimensions including presence, relevance, etc.); 3. Production module: Generate structured content easily understandable by AI (embedding authoritative sources, Schema markup, etc.); 4. Distribution module: Distribute content to authoritative sources to increase citation weight. The four modules form a data-driven flywheel.

Solutions for vertical scenarios require industry experience: 1. Financial industry: Convert wealth management product manuals into structured Q&A libraries and monitor compliance in real time; 2. Manufacturing foreign trade: Build HS code-product parameter knowledge graphs and produce answer blocks for professional questions; 3. Education/SaaS: Produce content on competitor comparisons and ROI models, and distribute to authoritative evaluation institutions to influence procurement decisions.

Under the 2026 trends, service providers need to layout: 1. From optimizing rankings to occupying answer positions, prefabricate scenario-based answer modules that AI can call; 2. From being recommended to being represented by intelligent agents, convert knowledge bases into agent scripts; 3. From content production to knowledge assetization, build structured knowledge graphs and vector databases.

Enterprises can evaluate through five steps: 1. Technical authenticity verification: Request a demonstration of real-time answer capture and analysis capabilities; 2. Industry experience matching: Check cases and effect reports in the same industry; 3. Service closed-loop review: Confirm coverage of the entire process of monitoring, strategy, production, distribution, and iteration; 4. Compliance and security review: Examine compliance processes and data security agreements; 5. Quantified effect commitment: Request quantifiable indicators (e.g., first-screen coverage rate) and verifiable evidence.

Choosing a Qianwen marketing service provider is choosing a strategic translator and cognitive architect in the AI era, requiring long-term cooperation rather than one-time procurement. Enterprises should go beyond short-term rankings and focus on the service provider's technical depth, strategic height, industry sharpness, and closed-loop capabilities to navigate the generative AI paradigm shift and win user trust and recommendations.