Strategy Product Management: Philosophy and Methodology for Content Recommendation

The article introduces the role of a strategy product manager, defining it as a product position that seeks global optimal solutions within constraints by driving projects, establishing evaluation systems, and comprehensively assessing project benefits.

It outlines the three main actions: project promotion, evaluation framework design, and thorough benefit assessment, and discusses challenges such as unclear metrics, decision‑maker support, and resource limits.

The piece compares strategy product managers with client‑side product managers and data analysts, highlighting shared skills in SQL, Python/Pandas, statistical knowledge, business acumen, product logic, and soft abilities like curiosity and empathy.

It then presents the “Dao” (values) and “Shu” (methods) of strategy products, including principles such as minimizing user decision‑making, focusing on mass demand, building reusable platforms, hypothesis‑driven data validation, and respecting rules, as well as tactical guidelines like coarse‑to‑fine strategy, MVP, regular expressions, upstream problem solving, and goal‑oriented decision making.

The content community decision framework is described, dividing benefits into six modules (experience and ecosystem for consumption, creation, and commerce) and explaining how to balance commercial pressure with user experience, set OKRs, and conduct multi‑objective experiments.

A Q&A section answers practical questions about the value of strategy product roles, the impact of large language models, trade‑offs between commercial and consumption goals, and the relative importance of creation versus consumption in content platforms.