In the overlapping context of local culture and the digital economy, combining career assessment tools with the logic of e-commerce platforms is becoming an important direction for improving career guidance and person–job matching services. This paper adopts a design science research approach and takes a WeChat mini-program–based intelligent career assessment e-commerce platform as its artefact. It proposes a three-stage practice framework moving from demand scenarios to system architecture and then to prototype validation. First, based on interviews and field observation, platform demand is structured into three representative scenarios educational progression, career adjustment, and institutional projects and corresponding assessment products and service bundles are designed. Second, following the idea of “assessment system + order system + channel system”, a minimal yet complete platform prototype is implemented that integrates online assessment, automatic report generation, QR-code key activation, institutional back-end management, and basic channel analytics. Third, using small-sample pilot data (each project with fewer than 80 participants) from two schools and one career-education institution, the study calculates key indicators such as activation rate, completion rate, paid conversion rate, and self-reported decision clarity, and briefly illustrates how the platform is used in typical situations. Results suggest that the proposed platform design is technically feasible and operationally valuable for improving user self-understanding, service delivery efficiency, and channel conversion, while also revealing room for improvement in report expression, user journey design, and stakeholder incentives. The contribution of this study lies mainly in offering an actionable, mid-level pathway from local career assessment models to a workable minimum viable product, and in providing a structured blueprint for institutions planning similar platforms.